Do you need data sets for all publicly traded U.S. companies and all non-U.S. firms with market caps greater than $5 as of January 1, 2010? Aswath Damodaran, professor of finance at the Stern School of Business (NYU), provides this information in downloadable excel spreadsheets on the "updated data" tab. He also has a broad range of other older data sets available on this page such as Jensen’s alpha and R-squared values by industry for the years 2002-2008 and total beta by industry sector (1998-2008). And on the "spreadsheets" tab he has a wealth of valuation spreadsheets.
At Ernie Chan’s blog there is "incontrovertible" evidence that averaging-in should not work as well as a link to an Excel version of the ADF (Augmented Dickey Fuller—if you have to ask, you probably don’t need it) test for cointegration. In both cases there are valuable comments.
From SSRN comes a paper “A Comparison of Quantitative and Qualitative Hedge Funds,” that claims that quantitative hedge funds outperform.
The EDHEC-Risk Institute features a downloadable paper
“Risk Control through Dynamic Core-Satellite Portfolios of ETFs: Applications to Absolute Return Funds and Tactical Asset Allocation.”
And if you need a break from numbers, here’s a brilliant musical admissions video (and of course I’m not biased or anything), “That’s Why I Chose Yale.” For three years I was dean of Morse College, one of the twelve residential colleges, so this video made me quite nostalgic.
See you Monday morning.
Saturday, January 30, 2010
Friday, January 29, 2010
Ponzi’s foray into foreign exchange
Charles Ponzi’s “untrodden path to fabulous wealth” took him into the world of foreign exchange via international reply coupons. These coupons, issued by the post offices of most countries, were prepaid postage. For instance, a coupon from Spain read: “This coupon [purchased for 30 centavos] may be exchanged at any post-office of any country in the Universal Postal Union for a postal stamp of the value of 25 centimes, or its equivalent.” (p. 104) Thirty centavos were nominally equivalent to 6 cents; 25 centimes, 5 cents.
Ponzi calculated that he could make a modest profit on Spanish coupons. “The peseta . . . was then quoted at 15 cents . . . instead of 20 cents, its par value. A little figuring disclosed that, at that rate, six and two-thirds pesetas could be bought for one dollar. Since a peseta was made up of 100 centavos, six and two-thirds pesetas were equal to 666 centavos. It didn’t take much to find out that with 666 centavos, I could have bought at any Spanish post-office 22 . . . coupons which I could exchange in the United States for a 5 cent stamp each. Or, $1.10.” (p. 105)
Admittedly, a 10% margin wasn’t spectacular. But other currencies were more debased. The Italian lira was quoted at 5 cents instead of 20 cents. “A dollar would have brought 20 lire, or 2,000 centesimi. With 2,000 centesimi,” Ponzi wrote, “I could have obtained 66 coupons at 30 centesimi each. Or enough coupons to obtain in exchange for them at the Boston post-office $3.30 of 5 cent stamps. A gross profit of 230%.” (p. 105)
This scheme was not illegal, but it obviously had to be carried out on a grand scale to bring in substantial profits. The Boston postal inspector was skeptical, so Ponzi explained his business plan in more detail. “Assume . . . that France needs fifteen million dollars of francs. I borrow in this country one million dollars at 50% interest.... The million dollars, at the current rate of exchange, is equal to fifteen millions of francs. I send a draft of it to the French government with the understanding that France will issue to me 50,000,000 of international reply coupons. France can obtain the coupons from the Universal Postal Union on open account. As soon as I receive the coupons, I exchange them here for stamps. Then I sell the stamps at a 10% discount. Let us assume that I pay also a 10% commission to the agents who have been instrumental in obtaining for me one million dollars from the public.” (p. 127) So, Ponzi explained, he would get $2,250,000 from the sale of the discounted stamps, pay $1 million in principal and $500,000 in interest to his noteholders and $100,000 to agents, with a gross profit for himself of $650,000.
And, as Ponzi continued to explain, the Universal Postal Union ledger would show the U.S. with a $2.5 million credit and France with a $3 million debit. “Why three million dollars? Because the coupons cost the French government 15,000,000 francs payable in gold, at their gold parity of 5 francs to the dollar. While they didn’t cost me but one million dollars, at the current exchange rate of 15 francs to the dollar. The difference between what France must pay and what the United States can collect, represents the charges of the Universal Postal Union for the service.” (pp. 127-28)
Although France is facing a $2 million shortfall as a result of this transaction, it can finance it through a bond issue. Ponzi calculated that France would actually realize a profit of $1.2 million on a twenty-year bond and France’s bondholders would earn $1.8 million. In brief, everybody makes money—Ponzi’s noteholders with their 50% return in 45 days, the United States post office that presumably turns a profit on the sale of $2.5 million worth of stamps, the Universal Postal Union ($500,000 in fees), those who buy stamps from Ponzi at a discount, the French government, and holders of the French bonds. All participants in Ponzi’s business deal get a free lunch.
Unfortunately there was no free lunch for Ponzi’s investors. He had counted on a limitless supply of international reply coupons but in fact was able to buy very few. As he wrote, “If [people] gave a thought at all to the coupons, they must have got dizzy figuring how many of them I needed to justify what I was doing. In fact, my visible resources then were in excess of $5,000,000. Assuming I earned two cents on each coupon, I should have had to handle over 250,000,000 of them! It was absurd. There were not that many in the world. There had never been that many. It would have taken months to print them.” (p. 153)
And so an extravagant but legal business plan quickly morphed into what the world now knows as a Ponzi scheme.
* * *
Postscript: Charles Ponzi entered the banking business after the creation of the Federal Reserve (1913) and before the FDIC (1933). He believed that bank depositors were not getting a fair deal. “They were at the mercy of the board of directors who might and might not be honest men. . . . The depositors . . . were not receiving adequate returns for the risks they were incurring.” (p. 197) He came up with an idea for bank reform. Addressing the executive committee of Hanover Trust Company, he outlined his idea. Let me quote him in full.
“It occurs to me that this committee has supreme control over the millions which our depositors have intrusted to this bank. We may or may not exercise control judiciously. If we do, we earn some extra stock dividends. If we don’t, we might lose not over twice the amount of our buildings, or $800,000 while our depositors may lose several millions. The greater risk is theirs. Theirs is the greater loss. Yet, when all goes well, we only pay them about 4% a year. The situation seems unfair. I would be in favor of extending to depositors greater privileges and larger returns. For instance, I suggest that the depositors be permitted to elect a certain number of directors. They have a right to know what is being done at these meetings. In addition, I suggest that stockholders be paid a definite dividend of 7%, the same as the depositors are being paid 4%. All net earnings in excess of that should be equally prorated between stockholders and depositors. In other words, I advocate profit sharing banking.” (pp. 197-98)
The committee endorsed Ponzi’s plan. They subsequently invited all the financial editors of Boston papers to a meeting to explain this plan. But the newspapermen were beholden to the “Boston banking machinery”; they “knew only too well which side of their bread was buttered. In fact, the next day they reported that, after consulting with their managing editors, they couldn’t publicly endorse my plan.” (p. 198) Although Ponzi was prepared to publicize the plan with “his own” money, the law was closing in; his idea for banking reform remains but a footnote in off-beat financial history.
Ponzi calculated that he could make a modest profit on Spanish coupons. “The peseta . . . was then quoted at 15 cents . . . instead of 20 cents, its par value. A little figuring disclosed that, at that rate, six and two-thirds pesetas could be bought for one dollar. Since a peseta was made up of 100 centavos, six and two-thirds pesetas were equal to 666 centavos. It didn’t take much to find out that with 666 centavos, I could have bought at any Spanish post-office 22 . . . coupons which I could exchange in the United States for a 5 cent stamp each. Or, $1.10.” (p. 105)
Admittedly, a 10% margin wasn’t spectacular. But other currencies were more debased. The Italian lira was quoted at 5 cents instead of 20 cents. “A dollar would have brought 20 lire, or 2,000 centesimi. With 2,000 centesimi,” Ponzi wrote, “I could have obtained 66 coupons at 30 centesimi each. Or enough coupons to obtain in exchange for them at the Boston post-office $3.30 of 5 cent stamps. A gross profit of 230%.” (p. 105)
This scheme was not illegal, but it obviously had to be carried out on a grand scale to bring in substantial profits. The Boston postal inspector was skeptical, so Ponzi explained his business plan in more detail. “Assume . . . that France needs fifteen million dollars of francs. I borrow in this country one million dollars at 50% interest.... The million dollars, at the current rate of exchange, is equal to fifteen millions of francs. I send a draft of it to the French government with the understanding that France will issue to me 50,000,000 of international reply coupons. France can obtain the coupons from the Universal Postal Union on open account. As soon as I receive the coupons, I exchange them here for stamps. Then I sell the stamps at a 10% discount. Let us assume that I pay also a 10% commission to the agents who have been instrumental in obtaining for me one million dollars from the public.” (p. 127) So, Ponzi explained, he would get $2,250,000 from the sale of the discounted stamps, pay $1 million in principal and $500,000 in interest to his noteholders and $100,000 to agents, with a gross profit for himself of $650,000.
And, as Ponzi continued to explain, the Universal Postal Union ledger would show the U.S. with a $2.5 million credit and France with a $3 million debit. “Why three million dollars? Because the coupons cost the French government 15,000,000 francs payable in gold, at their gold parity of 5 francs to the dollar. While they didn’t cost me but one million dollars, at the current exchange rate of 15 francs to the dollar. The difference between what France must pay and what the United States can collect, represents the charges of the Universal Postal Union for the service.” (pp. 127-28)
Although France is facing a $2 million shortfall as a result of this transaction, it can finance it through a bond issue. Ponzi calculated that France would actually realize a profit of $1.2 million on a twenty-year bond and France’s bondholders would earn $1.8 million. In brief, everybody makes money—Ponzi’s noteholders with their 50% return in 45 days, the United States post office that presumably turns a profit on the sale of $2.5 million worth of stamps, the Universal Postal Union ($500,000 in fees), those who buy stamps from Ponzi at a discount, the French government, and holders of the French bonds. All participants in Ponzi’s business deal get a free lunch.
Unfortunately there was no free lunch for Ponzi’s investors. He had counted on a limitless supply of international reply coupons but in fact was able to buy very few. As he wrote, “If [people] gave a thought at all to the coupons, they must have got dizzy figuring how many of them I needed to justify what I was doing. In fact, my visible resources then were in excess of $5,000,000. Assuming I earned two cents on each coupon, I should have had to handle over 250,000,000 of them! It was absurd. There were not that many in the world. There had never been that many. It would have taken months to print them.” (p. 153)
And so an extravagant but legal business plan quickly morphed into what the world now knows as a Ponzi scheme.
* * *
Postscript: Charles Ponzi entered the banking business after the creation of the Federal Reserve (1913) and before the FDIC (1933). He believed that bank depositors were not getting a fair deal. “They were at the mercy of the board of directors who might and might not be honest men. . . . The depositors . . . were not receiving adequate returns for the risks they were incurring.” (p. 197) He came up with an idea for bank reform. Addressing the executive committee of Hanover Trust Company, he outlined his idea. Let me quote him in full.
“It occurs to me that this committee has supreme control over the millions which our depositors have intrusted to this bank. We may or may not exercise control judiciously. If we do, we earn some extra stock dividends. If we don’t, we might lose not over twice the amount of our buildings, or $800,000 while our depositors may lose several millions. The greater risk is theirs. Theirs is the greater loss. Yet, when all goes well, we only pay them about 4% a year. The situation seems unfair. I would be in favor of extending to depositors greater privileges and larger returns. For instance, I suggest that the depositors be permitted to elect a certain number of directors. They have a right to know what is being done at these meetings. In addition, I suggest that stockholders be paid a definite dividend of 7%, the same as the depositors are being paid 4%. All net earnings in excess of that should be equally prorated between stockholders and depositors. In other words, I advocate profit sharing banking.” (pp. 197-98)
The committee endorsed Ponzi’s plan. They subsequently invited all the financial editors of Boston papers to a meeting to explain this plan. But the newspapermen were beholden to the “Boston banking machinery”; they “knew only too well which side of their bread was buttered. In fact, the next day they reported that, after consulting with their managing editors, they couldn’t publicly endorse my plan.” (p. 198) Although Ponzi was prepared to publicize the plan with “his own” money, the law was closing in; his idea for banking reform remains but a footnote in off-beat financial history.
Thursday, January 28, 2010
Schwed, Where Are the Customers’ Yachts?
It was the end of the work day, time to kick back and read something. My alternatives were a paper on a strategy for portfolio risk management and Fred Schwed’s 1940 book Where Are the Customers’ Yachts? (republished by Fraser Publishing Company in 1985). Want to guess the winner?
Fred Schwed, Jr., first of all, doesn’t seem to be a pseudonym because the book’s copyright was renewed by Harriet Wolf Schwed. Perhaps if you’re saddled with a name like Fred Schwed you’ve got to be funny. There’s no question this is one funny book! He skewers everyone—and, yes, the same “everyones” who are still around. Well, that’s not quite accurate. He has a soft spot for the 1940 equivalent of the high frequency trader as well as the specialist. And he rallies to the defense of the “black-hearted” short seller.
Schwed’s primary targets are the market soothsayers. In his attack he is agnostic as to method; statisticians, tape readers, chartists, fundamental analysts, and all those up the chain in retail brokerage are treated with roughly equal contempt. The yacht-less customers, especially those who use leverage, don’t escape unscathed either.
Without further ado, let me quote three passages to give you a sense of the book’s timeliness and humor.
Heading the Wall Street hierarchy is “the conservative banker [who] says ‘yes’ only a few times a year. His rule is that he reserves his yesses for organizations so wealthy that if he said ‘no,’ some other banker would quickly say ‘yes.’ . . . In times of stress, when everybody needs money, he strives to avoid lending to anybody, but usually makes an exception of the United States government. Likewise, in prosperous times he is a mighty liberal lender—so liberal that years later unfriendly committees ask him what he thought he was thinking about, and he is unable to remember clearly.” (pp. 30-31)
“Most of the great speculators either ended their days in penury or came sickeningly close to it one or more times. An interesting exception was Hetty Green, who never took a backward step. She started rich and soon got richer, and after that she got richer and richer. But Mrs. Green was something of a realist, being both a woman and a miser. Few great speculators are either.” (p. 163)
“Investment and speculation are said to be two different things, and the prudent man is advised to engage in the one and avoid the other. This is something like explaining to the troubled adolescent that Love and Passion are two different things. He perceives that they are different, but they don’t seem quite different enough to clear up his problems.” (p. 171)
Fred Schwed, Jr., first of all, doesn’t seem to be a pseudonym because the book’s copyright was renewed by Harriet Wolf Schwed. Perhaps if you’re saddled with a name like Fred Schwed you’ve got to be funny. There’s no question this is one funny book! He skewers everyone—and, yes, the same “everyones” who are still around. Well, that’s not quite accurate. He has a soft spot for the 1940 equivalent of the high frequency trader as well as the specialist. And he rallies to the defense of the “black-hearted” short seller.
Schwed’s primary targets are the market soothsayers. In his attack he is agnostic as to method; statisticians, tape readers, chartists, fundamental analysts, and all those up the chain in retail brokerage are treated with roughly equal contempt. The yacht-less customers, especially those who use leverage, don’t escape unscathed either.
Without further ado, let me quote three passages to give you a sense of the book’s timeliness and humor.
Heading the Wall Street hierarchy is “the conservative banker [who] says ‘yes’ only a few times a year. His rule is that he reserves his yesses for organizations so wealthy that if he said ‘no,’ some other banker would quickly say ‘yes.’ . . . In times of stress, when everybody needs money, he strives to avoid lending to anybody, but usually makes an exception of the United States government. Likewise, in prosperous times he is a mighty liberal lender—so liberal that years later unfriendly committees ask him what he thought he was thinking about, and he is unable to remember clearly.” (pp. 30-31)
“Most of the great speculators either ended their days in penury or came sickeningly close to it one or more times. An interesting exception was Hetty Green, who never took a backward step. She started rich and soon got richer, and after that she got richer and richer. But Mrs. Green was something of a realist, being both a woman and a miser. Few great speculators are either.” (p. 163)
“Investment and speculation are said to be two different things, and the prudent man is advised to engage in the one and avoid the other. This is something like explaining to the troubled adolescent that Love and Passion are two different things. He perceives that they are different, but they don’t seem quite different enough to clear up his problems.” (p. 171)
Wednesday, January 27, 2010
If it ain’t broke
I subscribe to the free newsletter “a phrase a week.” The origin of this past week’s clichéd phrase, “if it ain’t broke, don’t fix it,” stunned me. I was sure it went pretty far back in down home American linguistic history. On the contrary. Apparently the author was Bert Lance, OMB director in the Carter administration. He was quoted in 1977 as saying that he could “save Uncle Sam billions if he [could] get the government to adopt a simple motto: ‘If it ain’t broke, don’t fix it.’”
This 33-year-old piece of advice might be good for government, but I don’t think it would serve the trader well. The phrase, as parsed by the newsletter, means “If something is working adequately well, leave it alone.” But if a trading plan is working adequately well, it could presumably work better and it could start to crack at any time. Markets have a penchant for wrecking the best laid plans. The trading plan shouldn’t be scuttled, but the trader should always be stress testing it and working around the edges looking for ways to improve it. She should be in constant search of new trade ideas and new strategies for order entry and risk management that might complement or tweak those in the “adequate” plan. “Fixing” a trading plan doesn’t cost scads of money, only time.
In fact, in the world of finance we might adopt a much less punchy phrase: If you don’t fix it—and keep fixing it, you might end up broke. As we know only too well from the recent Wall Street debacle, some things that weren’t at first glance obviously ”broke” couldn’t be fixed; others cost Uncle Sam billions to “fix,” at least temporarily. Unless you have a very generous uncle who will bail you out when your trading plan loses more money than you anticipated, keep fixing, fixing, fixing.
This 33-year-old piece of advice might be good for government, but I don’t think it would serve the trader well. The phrase, as parsed by the newsletter, means “If something is working adequately well, leave it alone.” But if a trading plan is working adequately well, it could presumably work better and it could start to crack at any time. Markets have a penchant for wrecking the best laid plans. The trading plan shouldn’t be scuttled, but the trader should always be stress testing it and working around the edges looking for ways to improve it. She should be in constant search of new trade ideas and new strategies for order entry and risk management that might complement or tweak those in the “adequate” plan. “Fixing” a trading plan doesn’t cost scads of money, only time.
In fact, in the world of finance we might adopt a much less punchy phrase: If you don’t fix it—and keep fixing it, you might end up broke. As we know only too well from the recent Wall Street debacle, some things that weren’t at first glance obviously ”broke” couldn’t be fixed; others cost Uncle Sam billions to “fix,” at least temporarily. Unless you have a very generous uncle who will bail you out when your trading plan loses more money than you anticipated, keep fixing, fixing, fixing.
Tuesday, January 26, 2010
Charles Ponzi, from riches to ruination
After years in the United States and a series of dashed dreams Charles Ponzi hit upon a foreign exchange scheme, the international reply coupon. In my next post I’ll describe how it worked in more detail. For now let’s get on with the biographical story.
Ponzi, as usual, needed money, about $50, to fund his reply coupon business, so he created yet another firm with the imposing name Securities Exchange Company. (Presumably he didn’t refer to it as the SEC; the U.S. Securities and Exchange Commission was created by congressional act in 1934, fifteen years after Ponzi’s business. As became evident with the Madoff scam, it might have profited from studying a little more closely the Securities Exchange Company.) Ponzi launched the business with a promissory note to the creditor who had been hounding him to pay on his office furniture. And then he borrowed from the public at large in amounts starting at $10 against the promissory notes of the Securities Exchange Company. The idea was that he would use the proceeds to buy coupons. In 45 days he would repay the notes at 50% interest.
At the beginning of 1920 Ponzi had 18 investors for a total of $1,770. When he paid his early investors $2,478 on their original investment, word of this get-rich-quick scheme spread quickly. By the end of July there were 30,219 investors holding notes of the Securities Exchange Company for nearly $15 million.
Soon enough Ponzi decided that “it had gotten to be sort of monotonous to watch my clerks fill the waste baskets with green-backs after the cash drawers were full.” (p. 140) He set his sights on acquiring banks. His first target was Hanover Trust, the bank that had refused his loan request for $2,000. His strategy was to maintain a large “dormant” account (somewhere in the neighborhood of $500,000), surreptitiously buy up small lots of stock by paying a few dollars over market, and elicit support from the Italian stockholders who had a large minority stake in the bank. Then he confronted the officers of the bank, asking to buy enough shares to control the bank. They naturally refused. So he pulled out his big gun and started to write out a check for his balance. The bankers said that they weren’t that liquid, that they would have to dispose of some securities, probably at a loss, to honor Ponzi’s check. Finally they reached a compromise, offering to sell Ponzi 1,500 shares. They counted on the Italian shareholders to support them, as they always had. But now they were pledged to Ponzi. “Half an hour later,” Ponzi wrote, “I left the Hanover Trust. . . . The bank was mine!” (p. 146)
Ponzi went on a shopping spree, buying real estate, mortgages, interests in banks and a construction company; he even bought the Napoli Macaroni Company. He had a sardine factory in Maine and a meat packing plant in Kansas City. And he offered $200 million for 1,800 ships from the government’s merchant fleet, saying that he would pay cash within 30 days of acceptance of his bid.
The problem—and Ponzi always had monumental problems—was that he wasn’t getting any coupons. “In fact, he confessed, “after the first lot, I had not been able to buy any more. Except in small quantities. For no other reason than the existing supply was not sufficient to meet the increased demand. They had to be ordered from the Universal Postal Union. But the moment the postal administrations of the various countries concerned began to notice an unusual activity in coupons, the cat was out of the bag. One by one they took steps to suspend the sale of coupons.” (p. 153)
Ponzi was spending as if his company were debt free. And he was tap dancing to buy time. He faced law suits, he survived a run, but finally he became the target of federal and state law officials. Soon enough the jig was up. An official audit showed that Ponzi was about $4 million short and he was placed under arrest.
He pled guilty to federal charges and was sentenced to five years in the Plymouth County Jail. Two years later the state trial began in which Ponzi was charged with 12 counts of larceny; the jury acquitted him. He earned early release from jail in 1924 only to face a second round of state charges; the trial resulted in a hung jury. The third time around, in 1925, the state brought four more counts of larceny against Ponzi, and this time he was not so lucky. The jury convicted him and the judge handed down a sentence of up to nine years. Ponzi was, however, free on appeal.
So what did Ponzi do? He got into the Florida real estate development business, but that didn’t go well. His reputation, it seems, had preceded him. The state of Florida brought charges against him for failing to file some mandatory state papers; he was tried and sentenced to a year of hard labor. Ponzi, getting ever more desperate, faked his suicide; the result was another jail term in Texas, then extradition to Boston to face his sentence of seven to nine years. Seven years later, in 1934, he was freed only to be rearrested by immigration officials and promptly deported to Italy. He died in Rio de Janeiro in 1949.
(After a brief hiatus to pursue a couple of other topics, I will return to Ponzi’s foray into the world of foreign exchange with a postscript on his idea for bank reform.)
Ponzi, as usual, needed money, about $50, to fund his reply coupon business, so he created yet another firm with the imposing name Securities Exchange Company. (Presumably he didn’t refer to it as the SEC; the U.S. Securities and Exchange Commission was created by congressional act in 1934, fifteen years after Ponzi’s business. As became evident with the Madoff scam, it might have profited from studying a little more closely the Securities Exchange Company.) Ponzi launched the business with a promissory note to the creditor who had been hounding him to pay on his office furniture. And then he borrowed from the public at large in amounts starting at $10 against the promissory notes of the Securities Exchange Company. The idea was that he would use the proceeds to buy coupons. In 45 days he would repay the notes at 50% interest.
At the beginning of 1920 Ponzi had 18 investors for a total of $1,770. When he paid his early investors $2,478 on their original investment, word of this get-rich-quick scheme spread quickly. By the end of July there were 30,219 investors holding notes of the Securities Exchange Company for nearly $15 million.
Soon enough Ponzi decided that “it had gotten to be sort of monotonous to watch my clerks fill the waste baskets with green-backs after the cash drawers were full.” (p. 140) He set his sights on acquiring banks. His first target was Hanover Trust, the bank that had refused his loan request for $2,000. His strategy was to maintain a large “dormant” account (somewhere in the neighborhood of $500,000), surreptitiously buy up small lots of stock by paying a few dollars over market, and elicit support from the Italian stockholders who had a large minority stake in the bank. Then he confronted the officers of the bank, asking to buy enough shares to control the bank. They naturally refused. So he pulled out his big gun and started to write out a check for his balance. The bankers said that they weren’t that liquid, that they would have to dispose of some securities, probably at a loss, to honor Ponzi’s check. Finally they reached a compromise, offering to sell Ponzi 1,500 shares. They counted on the Italian shareholders to support them, as they always had. But now they were pledged to Ponzi. “Half an hour later,” Ponzi wrote, “I left the Hanover Trust. . . . The bank was mine!” (p. 146)
Ponzi went on a shopping spree, buying real estate, mortgages, interests in banks and a construction company; he even bought the Napoli Macaroni Company. He had a sardine factory in Maine and a meat packing plant in Kansas City. And he offered $200 million for 1,800 ships from the government’s merchant fleet, saying that he would pay cash within 30 days of acceptance of his bid.
The problem—and Ponzi always had monumental problems—was that he wasn’t getting any coupons. “In fact, he confessed, “after the first lot, I had not been able to buy any more. Except in small quantities. For no other reason than the existing supply was not sufficient to meet the increased demand. They had to be ordered from the Universal Postal Union. But the moment the postal administrations of the various countries concerned began to notice an unusual activity in coupons, the cat was out of the bag. One by one they took steps to suspend the sale of coupons.” (p. 153)
Ponzi was spending as if his company were debt free. And he was tap dancing to buy time. He faced law suits, he survived a run, but finally he became the target of federal and state law officials. Soon enough the jig was up. An official audit showed that Ponzi was about $4 million short and he was placed under arrest.
He pled guilty to federal charges and was sentenced to five years in the Plymouth County Jail. Two years later the state trial began in which Ponzi was charged with 12 counts of larceny; the jury acquitted him. He earned early release from jail in 1924 only to face a second round of state charges; the trial resulted in a hung jury. The third time around, in 1925, the state brought four more counts of larceny against Ponzi, and this time he was not so lucky. The jury convicted him and the judge handed down a sentence of up to nine years. Ponzi was, however, free on appeal.
So what did Ponzi do? He got into the Florida real estate development business, but that didn’t go well. His reputation, it seems, had preceded him. The state of Florida brought charges against him for failing to file some mandatory state papers; he was tried and sentenced to a year of hard labor. Ponzi, getting ever more desperate, faked his suicide; the result was another jail term in Texas, then extradition to Boston to face his sentence of seven to nine years. Seven years later, in 1934, he was freed only to be rearrested by immigration officials and promptly deported to Italy. He died in Rio de Janeiro in 1949.
(After a brief hiatus to pursue a couple of other topics, I will return to Ponzi’s foray into the world of foreign exchange with a postscript on his idea for bank reform.)
Monday, January 25, 2010
Who was Charles Ponzi?
Recently I received a copy of the autobiographical The Rise of Mr. Ponzi (Despair, Ink., 2009) as a present. The book includes Ponzi’s own account of his life between his arrival in Boston from Italy in 1903 and his arrest in 1920 as well as a lengthy piece by Chuck Bougir. Bougir completes Ponzi’s life story and offers a sympathetic analysis of this “financial genius.”
Ponzi’s story is complicated, so I’ve decided to devote three posts to it. Today I will summarize his checkered life in North America up to the time of the international reply coupon scheme for which he is best known. In a second post I’ll cover the brief period from his wild success to his 1920 arrest as well as the events leading up to his eventual deportation in 1934. Finally I’ll look in more detail at his foray into the foreign exchange market. (These summaries, of course, can’t capture the richness of the original text.)
Ponzi, a mere 5’2” in stature, disembarked in Boston “bedecked in expensive clothes of the latest European cut and followed down the gang-plank by a couple of stewards laden with several pieces of baggage. . . labeled ‘First Class’” (p. 10) but with only $2.50 in his pocket. He had started out with $200 but lost most of it to a card shark onboard.
For four years after his arrival Ponzi went from city to city and from menial job to menial job. Finally he traveled to Montreal and, five minutes after entering the Banco Zarossi, was signed on as a clerk. Life was looking up for Ponzi. But soon enough Zarossi, the bank's proprietor, started to “invest” in other businesses. “The new enterprises needed money. And he began to dip into his depositors’ accounts; the same old story of a lot of bank executives.” (p. 16) Enter another shady character, a charge of forgery, and Ponzi ended up in the St. Vincent de Paul Penitentiary where he spent almost two years. Once released, he decided to leave Montreal for upstate New York. With him on the train were five Italian immigrants whom he had been asked to look after. The U.S immigration service was vigilant; it hauled Ponzi and the five immigrants off the train once it crossed the border. Ponzi was accused of smuggling aliens, the five men were held as material witnesses, and in the end Ponzi was sentenced to a two-year stint in a Georgia penitentiary.
The big house in Atlanta was a gilded cage, “the potential abode of every big man in the country . . . from cabinet members and members of Congress to national bank officials and postal clerks.” (p. 45) One of his fellow inmates was Charles W. Morse, the banker and stock market manipulator who was a leading actor in the Panic of 1907. Morse had been given a 15-year sentence but received a presidential pardon after only a little more than two years. The news accounts of his release referred to his ill health (apparently brought about by eating soap and other stuff): “may live only few weeks,” “too weak to be removed from sick ward,” “pardoned in death’s shadow.” Morse lived another 21 years!
Ponzi served his full term and was released in July 1912. Some more jobs in the South and finally back to Boston in January 1917 as a “foreign correspondent” for an export company. By then Ponzi was 35 years old, had been in the U.S. for 13 years, and had little to show for his life. Two years later, “tired of working for expectations that didn’t pay either my rent or my grocery bills,” (p. 94) Ponzi left his job and set out on his own. He rented an office even though he didn’t have a business. When the building in which that office was located was taken over for renovation he moved to “a dingy, little office on the fifth floor” of the Niles Building on School Street, across the alley from City Hall. “The necessary furniture and equipment, such as desks, chairs, typewriters, files and even a multigraph, came from instalment houses. Books, directories, etc., some from my house and some from second-hand book stores. I put in a phone. A supply of engraved stationery. And had a sign painted on the door serving notice to the world that Charles Ponzi was an exporter and importer.” (p. 95)
The problem was that Ponzi had no clients. He wanted to become a commission agent for domestic and foreign firms but needed a way to reach prospects. He decided to publish a free trade publication that would be subsidized by advertising, some of it targeted. “The Trader’s Guide” would be put out by “The Bostonian Advertising & Publishing Company.” “A long name which only meant an additional sign on the door and new letterheads.” (p. 98) Unfortunately Ponzi needed funding to launch the guide and could find it nowhere. “In a moment of despair” he applied for a $2,000 loan at the Hanover Trust Company. The bank president summarily denied his loan request, and soon enough The Trader’s Guide was but another dashed dream.
But Ponzi was energized by the bank president’s remark that his account was “more of a bother than a benefit to us.” A few months later Charles Ponzi owned the bank “lock, stock and barrel” (p. 102) and had the satisfaction of blocking a motion to raise the president’s salary.
(to be continued)
Ponzi’s story is complicated, so I’ve decided to devote three posts to it. Today I will summarize his checkered life in North America up to the time of the international reply coupon scheme for which he is best known. In a second post I’ll cover the brief period from his wild success to his 1920 arrest as well as the events leading up to his eventual deportation in 1934. Finally I’ll look in more detail at his foray into the foreign exchange market. (These summaries, of course, can’t capture the richness of the original text.)
Ponzi, a mere 5’2” in stature, disembarked in Boston “bedecked in expensive clothes of the latest European cut and followed down the gang-plank by a couple of stewards laden with several pieces of baggage. . . labeled ‘First Class’” (p. 10) but with only $2.50 in his pocket. He had started out with $200 but lost most of it to a card shark onboard.
For four years after his arrival Ponzi went from city to city and from menial job to menial job. Finally he traveled to Montreal and, five minutes after entering the Banco Zarossi, was signed on as a clerk. Life was looking up for Ponzi. But soon enough Zarossi, the bank's proprietor, started to “invest” in other businesses. “The new enterprises needed money. And he began to dip into his depositors’ accounts; the same old story of a lot of bank executives.” (p. 16) Enter another shady character, a charge of forgery, and Ponzi ended up in the St. Vincent de Paul Penitentiary where he spent almost two years. Once released, he decided to leave Montreal for upstate New York. With him on the train were five Italian immigrants whom he had been asked to look after. The U.S immigration service was vigilant; it hauled Ponzi and the five immigrants off the train once it crossed the border. Ponzi was accused of smuggling aliens, the five men were held as material witnesses, and in the end Ponzi was sentenced to a two-year stint in a Georgia penitentiary.
The big house in Atlanta was a gilded cage, “the potential abode of every big man in the country . . . from cabinet members and members of Congress to national bank officials and postal clerks.” (p. 45) One of his fellow inmates was Charles W. Morse, the banker and stock market manipulator who was a leading actor in the Panic of 1907. Morse had been given a 15-year sentence but received a presidential pardon after only a little more than two years. The news accounts of his release referred to his ill health (apparently brought about by eating soap and other stuff): “may live only few weeks,” “too weak to be removed from sick ward,” “pardoned in death’s shadow.” Morse lived another 21 years!
Ponzi served his full term and was released in July 1912. Some more jobs in the South and finally back to Boston in January 1917 as a “foreign correspondent” for an export company. By then Ponzi was 35 years old, had been in the U.S. for 13 years, and had little to show for his life. Two years later, “tired of working for expectations that didn’t pay either my rent or my grocery bills,” (p. 94) Ponzi left his job and set out on his own. He rented an office even though he didn’t have a business. When the building in which that office was located was taken over for renovation he moved to “a dingy, little office on the fifth floor” of the Niles Building on School Street, across the alley from City Hall. “The necessary furniture and equipment, such as desks, chairs, typewriters, files and even a multigraph, came from instalment houses. Books, directories, etc., some from my house and some from second-hand book stores. I put in a phone. A supply of engraved stationery. And had a sign painted on the door serving notice to the world that Charles Ponzi was an exporter and importer.” (p. 95)
The problem was that Ponzi had no clients. He wanted to become a commission agent for domestic and foreign firms but needed a way to reach prospects. He decided to publish a free trade publication that would be subsidized by advertising, some of it targeted. “The Trader’s Guide” would be put out by “The Bostonian Advertising & Publishing Company.” “A long name which only meant an additional sign on the door and new letterheads.” (p. 98) Unfortunately Ponzi needed funding to launch the guide and could find it nowhere. “In a moment of despair” he applied for a $2,000 loan at the Hanover Trust Company. The bank president summarily denied his loan request, and soon enough The Trader’s Guide was but another dashed dream.
But Ponzi was energized by the bank president’s remark that his account was “more of a bother than a benefit to us.” A few months later Charles Ponzi owned the bank “lock, stock and barrel” (p. 102) and had the satisfaction of blocking a motion to raise the president’s salary.
(to be continued)
Sunday, January 24, 2010
Risk and time
Irving Fisher, the Yale economics professor most widely remembered for his unfortunate prediction a few days before the crash of 1929 that “stock prices have reached what looks like a permanently high plateau,” published a classic the following year. In today’s post I’m going to look at the relationship between risk and time as described in The Theory of Interest as Determined by Impatience to Spend Income and Opportunity to Invest It (Macmillan, 1930). Don’t start yawning; this is weird psychological stuff! Richard Thaler wrote a short paper, “Irving Fisher: Modern Behavioral Economist," touching on some of these themes.
Fisher equates time preference with human impatience. The impatient man wants income now; the patient man is willing to wait for deferred income. The degree of a person’s impatience depends on four factors: (1) the size of his expected real income stream, (2) its time shape (constant, increasing, decreasing, fluctuating), (3) its composition (food, shelter, education, amusement), and (4) its probability, or degree of risk or uncertainty.
The first factor, size, is fairly straightforward. “In general, it may be said that, other things being equal, the smaller the income, the higher the preference for present over future income; that is, the greater the impatience to acquire income as early as possible.” (p. 72) The time shape of a person’s projected income stream cannot be easily quantified, but here’s the gist. A person who is poor and has no obvious prospects for a change in his situation, one for whom “poverty bears down heavily on all portions of [his] expected life,” wants immediate income even more than future income. A person who has a meager income but expects to double it in ten years is impatient to realize these future earnings. “He may, in fact, borrow money to eke out this year’s income and promise repayments out of his supposedly more abundant income ten years later.” On the other hand, a person approaching retirement may want “to save from his present abundance in order to provide for coming needs.” (p. 74) The third factor, composition, is not critical to Fisher’s theory, so he passes over it quickly. But then there is risk.
Most people view risk or uncertainty as greater in the distant future than in the immediate future, damping down impatience; they save for a rainy day. Occasionally risk is higher in the near term than in the perceived distant future—during a strike, for instance, thus enhancing a person’s impatience. But what if risk applies to all periods alike, from the immediate to the remote? Fisher writes: “Such a general risk . . . explains why the bondholder is content with a lower average return than the stockholder. The bondholder chooses fixed and certain income rather than a variable and uncertain one, even if the latter is, on the average, larger. In short, a risky income, if the risk applies evenly to all parts of the income stream, is equivalent to a low income. And, since a low income, as we have seen, tends to create a high impatience, risk, if distributed in time, uniformly or fairly so, tends to raise impatience.” (p. 78). I assume he means that the investor faced with a risky income (minimally) withdraws his dividends as they are issued and reinvests none of them.
Fisher acknowledges that there are “exceptional individuals of the gambler type in whom caution is absent or perverted. Upon these, risk will have quite the opposite effects. Some persons who like to take great speculative chances are likely to treat the future as though it were especially well endowed, and are willing to sacrifice a large amount of their exaggerated expectations for the sake of a relatively small addition to their present income. In other words, they will have a high degree of impatience. The same individuals, if receiving an income which is risky for all periods of time alike, might, contrary to the rule, have, as a result, a low instead of a high degree of impatience.” (p. 79)
Admittedly, by the time this book appeared Fisher might not have been in the best of moods. And after this week’s market correction perhaps many long-only investors are starting to become impatient. Is this the start of a major breakdown? I have no idea. Whatever the case, I find Fisher’s description of investment income as similar to the income of the fated pauper decidedly downbeat.
Fisher equates time preference with human impatience. The impatient man wants income now; the patient man is willing to wait for deferred income. The degree of a person’s impatience depends on four factors: (1) the size of his expected real income stream, (2) its time shape (constant, increasing, decreasing, fluctuating), (3) its composition (food, shelter, education, amusement), and (4) its probability, or degree of risk or uncertainty.
The first factor, size, is fairly straightforward. “In general, it may be said that, other things being equal, the smaller the income, the higher the preference for present over future income; that is, the greater the impatience to acquire income as early as possible.” (p. 72) The time shape of a person’s projected income stream cannot be easily quantified, but here’s the gist. A person who is poor and has no obvious prospects for a change in his situation, one for whom “poverty bears down heavily on all portions of [his] expected life,” wants immediate income even more than future income. A person who has a meager income but expects to double it in ten years is impatient to realize these future earnings. “He may, in fact, borrow money to eke out this year’s income and promise repayments out of his supposedly more abundant income ten years later.” On the other hand, a person approaching retirement may want “to save from his present abundance in order to provide for coming needs.” (p. 74) The third factor, composition, is not critical to Fisher’s theory, so he passes over it quickly. But then there is risk.
Most people view risk or uncertainty as greater in the distant future than in the immediate future, damping down impatience; they save for a rainy day. Occasionally risk is higher in the near term than in the perceived distant future—during a strike, for instance, thus enhancing a person’s impatience. But what if risk applies to all periods alike, from the immediate to the remote? Fisher writes: “Such a general risk . . . explains why the bondholder is content with a lower average return than the stockholder. The bondholder chooses fixed and certain income rather than a variable and uncertain one, even if the latter is, on the average, larger. In short, a risky income, if the risk applies evenly to all parts of the income stream, is equivalent to a low income. And, since a low income, as we have seen, tends to create a high impatience, risk, if distributed in time, uniformly or fairly so, tends to raise impatience.” (p. 78). I assume he means that the investor faced with a risky income (minimally) withdraws his dividends as they are issued and reinvests none of them.
Fisher acknowledges that there are “exceptional individuals of the gambler type in whom caution is absent or perverted. Upon these, risk will have quite the opposite effects. Some persons who like to take great speculative chances are likely to treat the future as though it were especially well endowed, and are willing to sacrifice a large amount of their exaggerated expectations for the sake of a relatively small addition to their present income. In other words, they will have a high degree of impatience. The same individuals, if receiving an income which is risky for all periods of time alike, might, contrary to the rule, have, as a result, a low instead of a high degree of impatience.” (p. 79)
Admittedly, by the time this book appeared Fisher might not have been in the best of moods. And after this week’s market correction perhaps many long-only investors are starting to become impatient. Is this the start of a major breakdown? I have no idea. Whatever the case, I find Fisher’s description of investment income as similar to the income of the fated pauper decidedly downbeat.
Saturday, January 23, 2010
Geography lessons
One of the perks of writing a blog is that your knowledge of geography improves. Google Analytics provides a map overlay of visitors to the blog, and it’s always fun to use that map to test geographical skills. Some days it’s easy, other days quite challenging.
Since this blog’s launch back in July of 2009 visitors have come from 88 countries. In order of number of visits here they are: United States, Canada, United Kingdom, Singapore, India, Switzerland, Australia, Netherlands, Spain, Sweden, Germany, Romania, Thailand, Italy, Belgium, Denmark, France, Brazil, Hong Kong, Malaysia, Greece, Lebanon, Israel, New Zealand, Japan, Portugal, Ireland, Indonesia, Poland, Norway, South Korea, Russia, South Africa, Slovenia, Hungary, Czech Republic, Vietnam, Mexico, Finland, Taiwan, Turkey, Philippines, Austria, Bulgaria, Costa Rica, United Arab Emirates, Saudi Arabia, Latvia, Argentina, Bermuda, Nepal, British Virgin Islands, Luxembourg, Estonia, Oman, Nigeria, Slovakia, Kuwait, Egypt, Cyprus, Trinidad and Tobago, Dominican Republic, Malta, Peru, Iran, Chile, Jamaica, Mongolia, Honduras, Tunisia, Iceland, Bosnia and Herzegovina, Colombia, Croatia, Ecuador, Kenya, Venezuela, Macedonia, Mauritius, Greenland, Tanzania, Lithuania, Serbia, Georgia, Jordan, Bolivia, Pakistan, and the Solomon Islands.
Striking in its absence is China. Perhaps, though I highly doubt it, it was included in the “not set” category; the “not sets” fell in between Greece and Lebanon. I assume that Reading the Markets simply belongs to some subset (Google blogs?) of the internet that is being blocked in China. It would be far too depressing to think that out of the gargantuan Chinese population not a single solitary soul ever read my sterling prose.
Since this blog’s launch back in July of 2009 visitors have come from 88 countries. In order of number of visits here they are: United States, Canada, United Kingdom, Singapore, India, Switzerland, Australia, Netherlands, Spain, Sweden, Germany, Romania, Thailand, Italy, Belgium, Denmark, France, Brazil, Hong Kong, Malaysia, Greece, Lebanon, Israel, New Zealand, Japan, Portugal, Ireland, Indonesia, Poland, Norway, South Korea, Russia, South Africa, Slovenia, Hungary, Czech Republic, Vietnam, Mexico, Finland, Taiwan, Turkey, Philippines, Austria, Bulgaria, Costa Rica, United Arab Emirates, Saudi Arabia, Latvia, Argentina, Bermuda, Nepal, British Virgin Islands, Luxembourg, Estonia, Oman, Nigeria, Slovakia, Kuwait, Egypt, Cyprus, Trinidad and Tobago, Dominican Republic, Malta, Peru, Iran, Chile, Jamaica, Mongolia, Honduras, Tunisia, Iceland, Bosnia and Herzegovina, Colombia, Croatia, Ecuador, Kenya, Venezuela, Macedonia, Mauritius, Greenland, Tanzania, Lithuania, Serbia, Georgia, Jordan, Bolivia, Pakistan, and the Solomon Islands.
Striking in its absence is China. Perhaps, though I highly doubt it, it was included in the “not set” category; the “not sets” fell in between Greece and Lebanon. I assume that Reading the Markets simply belongs to some subset (Google blogs?) of the internet that is being blocked in China. It would be far too depressing to think that out of the gargantuan Chinese population not a single solitary soul ever read my sterling prose.
Davies, The Rules of Winning Chess
For those who enjoyed my posts on Joshua Waitzkin’s The Art of Learning here’s a review with many comments, compliments of Victor Niederhoffer, of The Rules of Winning Chess by Nigel Davies. I haven’t read the book myself, but I thought I’d pass along the link.
Friday, January 22, 2010
The long-term effects of making decisions when you’re upset
Dan Ariely, a behavioral economist and author of Predictably Irrational, has an interesting column in the most recent Harvard Business Review. Entitled “The Long-Term Effects of Short-Term Emotions,” he recounts the results of an experiment he conducted with Eduardo Andrade. The hypothesis they wanted to test was whether poor, emotionally driven decisions guide later so-called rational decisions.
They showed one group of subjects a film clip designed to annoy them, the other group a happy clip. Immediately afterward everyone played the ultimatum game in which the investigators, who have $20, offer the movie watcher a portion of the money. Sometimes the split is even, other times the movie watcher gets less than half. The movie watcher can either accept or reject the offer. If he rejects it, both sides get nothing.
Predictably, those who had just been annoyed rejected far more offers than those who saw the happy clip. The investigators then waited until the emotions evoked by the clips had subsided to the point of irrelevance. Nonetheless, the group that had been annoyed initially still rejected far more offers.
Ariely brings this home to the financial and business world. “So now I’m thinking of the manager whose personal portfolio loses 10% of its value in a week. . . . He’s frustrated, angry, nervous—and all the while, he’s making decisions about the day-to-day operations of his group. If he’s forced to attend to these issues right after he looks at his portfolio, he’s liable to make poor decisions, colored by his inner turmoil. Worse, though, those poor decisions become part of the blueprint for his future decisions—part of what his brain considers ‘the way to act.’”
Apparently, “as research going back to Festinger’s cognitive dissonance theory suggests, the problem with emotional decisions is that our actions loom larger than the conditions under which the decisions were made. When we confront a situation, our mind looks for a precedent among past actions without regard to whether a decision was made in emotional or unemotional circumstances. Which means we end up repeating our mistakes, even after we’ve cooled off.”
This research could go a long way toward explaining why traders keep repeating their mistakes. Early on, perhaps, they nervously exited a trade the moment it went ever so slightly against them. The trade then turned around, annoying them. Perhaps they then took a trade in the opposite direction, with the same effect. They got even more annoyed and reversed once again. This bad trading practice might then become entrenched in their repertoire. Unfortunately, the best Ariely has to offer, but maybe it’s good enough, is to “take a deep breath. Count backward from 10 (or 10,000). Wait until you’ve cooled off. Sleep on it. If you don’t, you may regret it. Many times over.”
* * *
Sometimes even I listen to my own “advice” column. I intended to post this piece yesterday morning. However, a dead internet connection didn’t start the day off well. At least this time a Comcast tech was here by 11:30 a.m. And, unlike the last one, he was both competent and thorough. After all the in-house fixes failed, he went up the pole hidden among the trees and found that the signal was horribly degraded. He replaced the antediluvian hardware on the pole and ran a new line to the house. Well, that seems to have solved the problem although tomorrow a bucket truck will come out to the road to check the signal at that level. Moreover, it seems that at my leisure I can visit the Comcast store in New Haven and swap out my Docsis 3 modem for the new and improved Docsis 4 variety which features three frequencies instead of one. Let’s just hope it’s not three ways to fail.
The upshot? The market sank without my assistance. By the time I was back online I decided I wasn’t fit for any serious work. No sense compounding the morning’s frustration with bad trading in the afternoon.
They showed one group of subjects a film clip designed to annoy them, the other group a happy clip. Immediately afterward everyone played the ultimatum game in which the investigators, who have $20, offer the movie watcher a portion of the money. Sometimes the split is even, other times the movie watcher gets less than half. The movie watcher can either accept or reject the offer. If he rejects it, both sides get nothing.
Predictably, those who had just been annoyed rejected far more offers than those who saw the happy clip. The investigators then waited until the emotions evoked by the clips had subsided to the point of irrelevance. Nonetheless, the group that had been annoyed initially still rejected far more offers.
Ariely brings this home to the financial and business world. “So now I’m thinking of the manager whose personal portfolio loses 10% of its value in a week. . . . He’s frustrated, angry, nervous—and all the while, he’s making decisions about the day-to-day operations of his group. If he’s forced to attend to these issues right after he looks at his portfolio, he’s liable to make poor decisions, colored by his inner turmoil. Worse, though, those poor decisions become part of the blueprint for his future decisions—part of what his brain considers ‘the way to act.’”
Apparently, “as research going back to Festinger’s cognitive dissonance theory suggests, the problem with emotional decisions is that our actions loom larger than the conditions under which the decisions were made. When we confront a situation, our mind looks for a precedent among past actions without regard to whether a decision was made in emotional or unemotional circumstances. Which means we end up repeating our mistakes, even after we’ve cooled off.”
This research could go a long way toward explaining why traders keep repeating their mistakes. Early on, perhaps, they nervously exited a trade the moment it went ever so slightly against them. The trade then turned around, annoying them. Perhaps they then took a trade in the opposite direction, with the same effect. They got even more annoyed and reversed once again. This bad trading practice might then become entrenched in their repertoire. Unfortunately, the best Ariely has to offer, but maybe it’s good enough, is to “take a deep breath. Count backward from 10 (or 10,000). Wait until you’ve cooled off. Sleep on it. If you don’t, you may regret it. Many times over.”
* * *
Sometimes even I listen to my own “advice” column. I intended to post this piece yesterday morning. However, a dead internet connection didn’t start the day off well. At least this time a Comcast tech was here by 11:30 a.m. And, unlike the last one, he was both competent and thorough. After all the in-house fixes failed, he went up the pole hidden among the trees and found that the signal was horribly degraded. He replaced the antediluvian hardware on the pole and ran a new line to the house. Well, that seems to have solved the problem although tomorrow a bucket truck will come out to the road to check the signal at that level. Moreover, it seems that at my leisure I can visit the Comcast store in New Haven and swap out my Docsis 3 modem for the new and improved Docsis 4 variety which features three frequencies instead of one. Let’s just hope it’s not three ways to fail.
The upshot? The market sank without my assistance. By the time I was back online I decided I wasn’t fit for any serious work. No sense compounding the morning’s frustration with bad trading in the afternoon.
Wednesday, January 20, 2010
Saliba, Options Strategies for Directionless Markets
Some months ago I reviewed Anthony J. Saliba’s Option Spread Strategies. The book I’m looking at today has a more limited focus, as the full title indicates--Option Strategies for Directionless Markets: Trading with Butterflies, Iron Butterflies, and Condors (Bloomberg Press, 2008). The bonus is an interview with Saliba about the evolution of the options markets and how he traded butterflies.
The book is designed for someone who has a grasp of some of the fundamental building blocks of options trading—puts, calls, and vertical spreads. No knowledge of the Greeks is required because the author spends two chapters dealing with them. In the first chapter he provides an overview; in the second he shows how the Greeks impact butterflies.
The bulk of the book describes the structure of butterflies and condors and their variants such as iron butterflies and condors, broken-wing butterflies, pterodactyls, and iron pterodactyls. A single chapter is devoted to strategy application. Risk management is for the most part ignored.
This is a basic book that in its title purports to offer strategies for directionless markets. But, curiously enough, the strategy chapter analyzes not so much directionless markets as markets in transition. The summary statement reads in part: “The key to all of the butterfly (condor) strategies discussed in this chapter is capturing a transition, a particular change in market conditions that adds to the value of a long butterfly or condor position. By correctly anticipating a change in market conditions, whether it is the underlying’s price, time until expiration, or a decline in implied volatility levels, the trader may be able to realize a profit from a properly placed long butterfly or condor position.” (p. 143) This is a far cry from the common notion that butterflies and condors are appropriate for markets that are going nowhere. Even though we know that butterflies and condors are flexible positions that can easily be structured to reflect a directional bias and adjusted in response to a change in conditions, Saliba doesn’t devote enough space to this topic. The reader who is enough of a novice to need an introduction to the Greeks is going to be mighty confused by this chapter.
The book is beautifully laid out, with ample figures to illustrate the author’s points. It is designed for the student, with exercises, quizzes, and a final exam. In the final analysis, however, the reader is barely equipped to paper trade; no reader should consider himself ready to put his money on the line trading butterflies and condors until he’s done a lot more studying and practicing.
The book is designed for someone who has a grasp of some of the fundamental building blocks of options trading—puts, calls, and vertical spreads. No knowledge of the Greeks is required because the author spends two chapters dealing with them. In the first chapter he provides an overview; in the second he shows how the Greeks impact butterflies.
The bulk of the book describes the structure of butterflies and condors and their variants such as iron butterflies and condors, broken-wing butterflies, pterodactyls, and iron pterodactyls. A single chapter is devoted to strategy application. Risk management is for the most part ignored.
This is a basic book that in its title purports to offer strategies for directionless markets. But, curiously enough, the strategy chapter analyzes not so much directionless markets as markets in transition. The summary statement reads in part: “The key to all of the butterfly (condor) strategies discussed in this chapter is capturing a transition, a particular change in market conditions that adds to the value of a long butterfly or condor position. By correctly anticipating a change in market conditions, whether it is the underlying’s price, time until expiration, or a decline in implied volatility levels, the trader may be able to realize a profit from a properly placed long butterfly or condor position.” (p. 143) This is a far cry from the common notion that butterflies and condors are appropriate for markets that are going nowhere. Even though we know that butterflies and condors are flexible positions that can easily be structured to reflect a directional bias and adjusted in response to a change in conditions, Saliba doesn’t devote enough space to this topic. The reader who is enough of a novice to need an introduction to the Greeks is going to be mighty confused by this chapter.
The book is beautifully laid out, with ample figures to illustrate the author’s points. It is designed for the student, with exercises, quizzes, and a final exam. In the final analysis, however, the reader is barely equipped to paper trade; no reader should consider himself ready to put his money on the line trading butterflies and condors until he’s done a lot more studying and practicing.
Tuesday, January 19, 2010
Evaluating a trading system
We’ve designed a trading system, we’ve optimized it, and we’ve tested its forecasting strength. (See the two previous posts: Degrees of freedom—KISS and Optimization. Are we there yet? No. We still have to look at performance metrics to determine whether we have a system to which we are willing to commit cold hard cash. If, for instance, profits look great but drawdowns are outsized, perhaps it’s not the system for us.
There are a whole host of performance metrics available, some trying to improve on the classic Sharpe ratio which penalizes upside and downside volatility equally. To measure risk-adjusted returns we have, among others, the Sortino ratio and the omega ratio.
Jaekle and Tomasini in Trading Systems suggest some general principles at play in choosing performance metrics. First, any indicator we use must always compare return to risk. Second, it should be normalized so it can be used across asset classes or trading systems. Net profit, the authors point out, has neither of these features. So those hawkers of black box systems who claim a 244% return or the ads that say “turn $10,000 into $68,769 in only six weeks” are, at the very least, not using acceptable performance metrics. Third, a performance indicator should indicate how consistent the system is. No one wants a system that made a ton of money ten years ago and has lost money every year since.
The authors tout an indicator included in the Trade Station report known as the RINA Index. It “represents the reward-risk ratio per one unit of time and it compares the ‘select net profit’ (net profit minus the positive and negative outlier trades, that is minus the abnormal trades that overcome the three standard deviation limit away from the average) divided by the average drawdown and again divided by the percentage of time in the market indicator. This indicator should always be over 30 and the higher the better.” (p. 32) Who am I to criticize? But this is not a stand-alone indicator; we can’t simply ignore outliers, however we choose to deal with them.
Perhaps the simplest way to evaluate a trading system is to look at the equity line which should grow fairly smoothly without many deep drawdowns. “Personally,” the authors continue, “we also appreciate many ‘flat times’, that is parts of the equity line that are horizontal: it means that no trading was done in that period since a filter took the system out of the market. We believe that there is no need to trade continuously and a good system should know when there is some edge to be exploited over the markets and conversely when it is more appropriate to sit on the sidelines.” (pp. 32-33)
* * *
Over the course of three posts I’ve outlined elements involved in designing and testing a trading system. I have just skimmed the surface. There are many resources available that dig deeper. Among them,
Bandy, Howard. Quantitative Trading Systems—Practical Methods for Design Testing and Validation (using Amibroker)
Carstens, Henry. “Introduction to Testing Trading Ideas.” Available online, along with a host of other pieces
Hill, John R., George Pruit, and Lundy Hill. The Ultimate Trading Guide
Jaekle, Urban and Emilio Tomasini. Trading Systems—A New Approach to System Development and Portfolio Optimisation
Jonelis, John. “Building a System” (using MetaStock). Available online, along with several other articles
Pardo, Robert. The Evaluation and Optimization of Trading Strategies
Stridsman, Thomas. Trading Systems and Money Management
Stridsman, Thomas. Trading Systems That Work
I’m sure I’ve missed some vital literature; feel free to add to my mini-bibliography.
And if you want to see brilliant trading system design in action go to CSS Analytics and its quant links.
There are a whole host of performance metrics available, some trying to improve on the classic Sharpe ratio which penalizes upside and downside volatility equally. To measure risk-adjusted returns we have, among others, the Sortino ratio and the omega ratio.
Jaekle and Tomasini in Trading Systems suggest some general principles at play in choosing performance metrics. First, any indicator we use must always compare return to risk. Second, it should be normalized so it can be used across asset classes or trading systems. Net profit, the authors point out, has neither of these features. So those hawkers of black box systems who claim a 244% return or the ads that say “turn $10,000 into $68,769 in only six weeks” are, at the very least, not using acceptable performance metrics. Third, a performance indicator should indicate how consistent the system is. No one wants a system that made a ton of money ten years ago and has lost money every year since.
The authors tout an indicator included in the Trade Station report known as the RINA Index. It “represents the reward-risk ratio per one unit of time and it compares the ‘select net profit’ (net profit minus the positive and negative outlier trades, that is minus the abnormal trades that overcome the three standard deviation limit away from the average) divided by the average drawdown and again divided by the percentage of time in the market indicator. This indicator should always be over 30 and the higher the better.” (p. 32) Who am I to criticize? But this is not a stand-alone indicator; we can’t simply ignore outliers, however we choose to deal with them.
Perhaps the simplest way to evaluate a trading system is to look at the equity line which should grow fairly smoothly without many deep drawdowns. “Personally,” the authors continue, “we also appreciate many ‘flat times’, that is parts of the equity line that are horizontal: it means that no trading was done in that period since a filter took the system out of the market. We believe that there is no need to trade continuously and a good system should know when there is some edge to be exploited over the markets and conversely when it is more appropriate to sit on the sidelines.” (pp. 32-33)
* * *
Over the course of three posts I’ve outlined elements involved in designing and testing a trading system. I have just skimmed the surface. There are many resources available that dig deeper. Among them,
Bandy, Howard. Quantitative Trading Systems—Practical Methods for Design Testing and Validation (using Amibroker)
Carstens, Henry. “Introduction to Testing Trading Ideas.” Available online, along with a host of other pieces
Hill, John R., George Pruit, and Lundy Hill. The Ultimate Trading Guide
Jaekle, Urban and Emilio Tomasini. Trading Systems—A New Approach to System Development and Portfolio Optimisation
Jonelis, John. “Building a System” (using MetaStock). Available online, along with several other articles
Pardo, Robert. The Evaluation and Optimization of Trading Strategies
Stridsman, Thomas. Trading Systems and Money Management
Stridsman, Thomas. Trading Systems That Work
I’m sure I’ve missed some vital literature; feel free to add to my mini-bibliography.
And if you want to see brilliant trading system design in action go to CSS Analytics and its quant links.
Monday, January 18, 2010
Trading and poker
Some time back Bloomberg ran an article inelegantly titled “Harvard Poker Pro Says Texas Hold ‘Em Can Teach Traders to Fold.” The article quotes Aaron Brown, author of The Poker Face of Wall Street and risk manager at AQR Capital Management. Brown suggests that professional poker players would most likely be better than average traders. “They know to push when they have an edge and they know how not to bust, and that’s a tough combination to find.”
What other qualities do successful professional poker players share with successful traders? According to financial recruiters, a “rational approach toward risk, speedy decision-making under pressure, discipline and a well-trained memory.” Brandon Adams, who teaches behavioral finance at Harvard, stresses the intelligence, self-control, and confidence of successful card players. Moreover, he continues, “in poker, people are used to not sitting back and waiting for the fat pitch. They’re used to skirting the edge of ruin and they learn the tools of how to do that.”
Whether playing poker hones the kinds of skills necessary for trading success or whether successful poker players and successful traders are simply cut from the same psychological cloth I don’t know. But Susquehanna International Group obviously thinks that poker is a good training tool. They have been using poker to teach their new traders for over twenty years.
I suppose this is the appropriate place to call attention to Larry W. Phillips’ book The Tao of Poker: 285 Rules to Transform Your Game and Your Life (Adams Media, 2003) available as a bargain book on Amazon for $3.98. I came across this book by chance a year or two ago when I was looking for something else and consider it a serendipitous find.
What other qualities do successful professional poker players share with successful traders? According to financial recruiters, a “rational approach toward risk, speedy decision-making under pressure, discipline and a well-trained memory.” Brandon Adams, who teaches behavioral finance at Harvard, stresses the intelligence, self-control, and confidence of successful card players. Moreover, he continues, “in poker, people are used to not sitting back and waiting for the fat pitch. They’re used to skirting the edge of ruin and they learn the tools of how to do that.”
Whether playing poker hones the kinds of skills necessary for trading success or whether successful poker players and successful traders are simply cut from the same psychological cloth I don’t know. But Susquehanna International Group obviously thinks that poker is a good training tool. They have been using poker to teach their new traders for over twenty years.
I suppose this is the appropriate place to call attention to Larry W. Phillips’ book The Tao of Poker: 285 Rules to Transform Your Game and Your Life (Adams Media, 2003) available as a bargain book on Amazon for $3.98. I came across this book by chance a year or two ago when I was looking for something else and consider it a serendipitous find.
Sunday, January 17, 2010
“Floored”
Friday night was the Chicago premiere of “Floored,” a documentary about trading in the pits and the transition to electronic trading. Bloomberg did both a story and a very interesting video interview (click on the "video" tab above the story); in addition there’s a trailer on the Floored site. I doubt that the film will be coming to a theater near you any time soon. Most likely it will eventually be available in some kind of electronic format. But for the time being take advantage of these two sources.
Saturday, January 16, 2010
Adversity, with a touch of humor
Those of you who wait breathlessly for my early morning posts may have noticed that yesterday I showed up mid-afternoon. Here’s the story. On Thursday I received a Demotivator calendar as an appropriately humorous belated birthday present. (I may have many endearing qualities, but I’m no Little Mary Sunshine, as I refer to Christina Romer.) For those of you who have no clue what a Demotivator calendar is go to despair.com.
The theme for January was adversity. I wrote a thank you e-mail and hit the “send” button, at which point adversity struck! My internet connection went down, the e-mail remained but a draft.
I did the standard homeopathic remedy to restore the connection, to no avail. A phone call to Comcast proved fruitless; the best they could do was schedule an appointment for Sunday morning. My admittedly exaggerated protests that thousands of people depend on me fell on deaf ears.
Friday morning I plugged in my modem and my router, both of which had remained disconnected overnight so they could repent and reform. When I opened up my browser I got an installation screen for Comcast internet service. Hmm, a second way to fail. Another phone call, many fruitless stabs at restoring service. I pretty well reconciled myself to over two days of internet cold turkey.
But I have perseverance, described by the folks at Despair as “the courage to ignore the obvious wisdom of turning back.” By Friday afternoon I was also getting antsy. I had sold some stuff ahead of the Intel earnings, so I wasn’t overly distressed by the market downdraft. But I normally follow the markets tick by tick (well, as least when I’m not indulging in ways to twiddle your thumbs, and even they require an internet connection); reading a dull financial book was a very poor substitute.
I didn’t have a game plan, I just thought I’d reboot the computer that’s hard-wired to my cable modem and then—well, I wasn’t sure what. Contrary to everything we’ve been taught (the insanity, for instance, of doing the same thing over and over and expecting different results) the computer offered up Comcast’s home page. It’s not my normal home page, but no matter. The modem data lights started flashing wildly. Life had returned to normal.
Two problems remain. First, I have no idea why the connection went down and why it was restored. So I haven’t cancelled Sunday’s service call because I think it’s time for the ghostbusters. More important, I realize that my contingency plans are horribly defective. I need a fallback, preferably not one of those antiquated dial-up plans. I’m open to suggestions.
The theme for January was adversity. I wrote a thank you e-mail and hit the “send” button, at which point adversity struck! My internet connection went down, the e-mail remained but a draft.
I did the standard homeopathic remedy to restore the connection, to no avail. A phone call to Comcast proved fruitless; the best they could do was schedule an appointment for Sunday morning. My admittedly exaggerated protests that thousands of people depend on me fell on deaf ears.
Friday morning I plugged in my modem and my router, both of which had remained disconnected overnight so they could repent and reform. When I opened up my browser I got an installation screen for Comcast internet service. Hmm, a second way to fail. Another phone call, many fruitless stabs at restoring service. I pretty well reconciled myself to over two days of internet cold turkey.
But I have perseverance, described by the folks at Despair as “the courage to ignore the obvious wisdom of turning back.” By Friday afternoon I was also getting antsy. I had sold some stuff ahead of the Intel earnings, so I wasn’t overly distressed by the market downdraft. But I normally follow the markets tick by tick (well, as least when I’m not indulging in ways to twiddle your thumbs, and even they require an internet connection); reading a dull financial book was a very poor substitute.
I didn’t have a game plan, I just thought I’d reboot the computer that’s hard-wired to my cable modem and then—well, I wasn’t sure what. Contrary to everything we’ve been taught (the insanity, for instance, of doing the same thing over and over and expecting different results) the computer offered up Comcast’s home page. It’s not my normal home page, but no matter. The modem data lights started flashing wildly. Life had returned to normal.
Two problems remain. First, I have no idea why the connection went down and why it was restored. So I haven’t cancelled Sunday’s service call because I think it’s time for the ghostbusters. More important, I realize that my contingency plans are horribly defective. I need a fallback, preferably not one of those antiquated dial-up plans. I’m open to suggestions.
Friday, January 15, 2010
What could Goldman Sachs do for you?
Traders are rightly envious of the outsized profits Goldman Sachs manages to achieve on its proprietary trading desks. But how would the investor have fared had he followed Goldman’s focus list? Or what if you had hired Goldman Sachs Asset Management to steer your investments through troubled waters? In both cases I’m looking at returns from 2008.
(click to enlarge)
First, the Wall Street Journal published a table summarizing the 6-, 12-, 36-, and 60-month returns of the focus lists of 14 brokerage firms. I’m not sure whether in Goldman’s case the so-called focus list was its conviction buy list. But, however defined, following Goldman’s advice would have led an investor to underperform the total return of the S&P 500 in 2008. The S&P was down 37%; Goldman was down 43.71%, the second worst one-year performance of the lot. Over the course of five years, for the period ending December 31, 2008, it outperformed the S&P 500 Total Return index but still had negative returns.
Second, let’s look at what Goldman Sachs Asset Management accomplished for a prize client, the Goldman Sachs Foundation. Here I’m taking my data from Felix Salmon's Reuter’s blog. I have better things to do with my time than reading the foundation’s 297-page 2008 tax return.
The foundation had $269 million in assets at the beginning of 2008, made charitable disbursements of $22 million, and ended the year with $161 million. Let’s simplify calculations and consider two alternative scenarios, neither reflective of reality. First, let's assume that the fund started with $247 million (that is, that it made all its grants on the first day of the year—or, more accurately, just before midnight at the end of 2007, but let’s not nitpick). The management firm charged a 1.4% fee ($3,864,540) to steer the fund to a loss of 34.8%. Second, we can improve the performance metrics if we assume that the foundation made no grants at all, started the year with $269 million and ended with $183 million. In this case the managers lost only 32%. Admittedly, in both cases the management team outperformed the 37% loss of the S&P 500 Total Return index, but you’d think they might have done better for one of their own!
(click to enlarge)
First, the Wall Street Journal published a table summarizing the 6-, 12-, 36-, and 60-month returns of the focus lists of 14 brokerage firms. I’m not sure whether in Goldman’s case the so-called focus list was its conviction buy list. But, however defined, following Goldman’s advice would have led an investor to underperform the total return of the S&P 500 in 2008. The S&P was down 37%; Goldman was down 43.71%, the second worst one-year performance of the lot. Over the course of five years, for the period ending December 31, 2008, it outperformed the S&P 500 Total Return index but still had negative returns.
Second, let’s look at what Goldman Sachs Asset Management accomplished for a prize client, the Goldman Sachs Foundation. Here I’m taking my data from Felix Salmon's Reuter’s blog. I have better things to do with my time than reading the foundation’s 297-page 2008 tax return.
The foundation had $269 million in assets at the beginning of 2008, made charitable disbursements of $22 million, and ended the year with $161 million. Let’s simplify calculations and consider two alternative scenarios, neither reflective of reality. First, let's assume that the fund started with $247 million (that is, that it made all its grants on the first day of the year—or, more accurately, just before midnight at the end of 2007, but let’s not nitpick). The management firm charged a 1.4% fee ($3,864,540) to steer the fund to a loss of 34.8%. Second, we can improve the performance metrics if we assume that the foundation made no grants at all, started the year with $269 million and ended with $183 million. In this case the managers lost only 32%. Admittedly, in both cases the management team outperformed the 37% loss of the S&P 500 Total Return index, but you’d think they might have done better for one of their own!
Thursday, January 14, 2010
Reminiscences of a Stock Operator, annotated edition
Tuesday was a glorious day for me the book lover if not for the markets. Early in the morning I finished one of the best novels I’ve read in a long time. When the markets closed I trudged up my long driveway for the mail. Among all the junk in the mailbox was a package from Wiley that UPS was too lazy to deliver properly. Inside was Edwin Lefèvre’s Reminiscences of a Stock Operator with New Commentary and Insights on the Life and Times of Jesse Livermore (Wiley, 2010). Jon D. Markman did the extensive annotations, and Paul Tudor Jones wrote both a foreword and an “afterword.”
I never write a review before I’ve actually read the entire book, but here I’m making an exception. Of course, I read the original Lefèvre book. And I read the fascinating Paul Tudor Jones contributions to this book. What I described as an afterword is really a series of extended responses to questions Markman posed. But so far I’ve only started reading what is essentially an entirely new book.
Don’t be put off by the word “annotated.” This book doesn’t have those fussy little sidenotes that explain words you don’t know or things you don’t care about. What Markman has done is to provide the historical context for the fictionalized Livermore reminiscences. There are profiles of major traders and financiers, accounts of deals that succeeded and deals gone bad, and throughout a running biography of the real, as opposed to the fictionalized, Livermore. There are pictures, charts, and newspaper clippings.
As for the format, it’s a large 8” x 10”. Essentially it’s laid out in two columns, but often the annotations span the entire page.
This book is a gem. I am absolutely thrilled to have it, and I can’t imagine any trader not having it in his library. Find any excuse to buy it! At under $25 on Amazon, the excuse can be pretty darned flimsy.
I never write a review before I’ve actually read the entire book, but here I’m making an exception. Of course, I read the original Lefèvre book. And I read the fascinating Paul Tudor Jones contributions to this book. What I described as an afterword is really a series of extended responses to questions Markman posed. But so far I’ve only started reading what is essentially an entirely new book.
Don’t be put off by the word “annotated.” This book doesn’t have those fussy little sidenotes that explain words you don’t know or things you don’t care about. What Markman has done is to provide the historical context for the fictionalized Livermore reminiscences. There are profiles of major traders and financiers, accounts of deals that succeeded and deals gone bad, and throughout a running biography of the real, as opposed to the fictionalized, Livermore. There are pictures, charts, and newspaper clippings.
As for the format, it’s a large 8” x 10”. Essentially it’s laid out in two columns, but often the annotations span the entire page.
This book is a gem. I am absolutely thrilled to have it, and I can’t imagine any trader not having it in his library. Find any excuse to buy it! At under $25 on Amazon, the excuse can be pretty darned flimsy.
Wednesday, January 13, 2010
Openings, middlegames, and endgames
Josh Waitzkin, in The Art of Learning, points out the pitfalls of focusing on openings to the exclusion of the rest of the chess game. “There is a vast body of theory,” he writes, “that begins from the starting position of all chess games, and it is very tempting to teach children openings right off the bat, because built into this theoretical part of the game there are many imbedded traps, land mines that allow a player to win quickly and easily—in effect, to win without having to struggle to win.” What’s wrong with beginning with the beginning? “The answer is quicksand. Once you start with openings, there is no way out. Lifetimes can be spent memorizing and keeping up with the evolving Encyclopedia of Chess Openings (ECO). They are an addiction, with perilous psychological effects.” (p. 35)
Waitzkin claims that a person learning a new skill should lay a “solid foundation by studying positions of reduced complexity (endgame before opening)” and clear principles. For instance, when the six-year-old Josh was learning chess his mentor started with just three pieces on the board—king and pawn against king. “Over time,” he says, he “gained an excellent intuitive feel for the power of the king and the subtlety of the pawn.” “Layer by layer,” Waitzkin continues, “we built up my knowledge and my understanding of how to transform axioms into fuel for creative insight. Then we turned to rook endings, bishop endings, knight endings, . . . exploring the operating principles behind positions that I might never see again. This method of study gave me a feeling for the beautiful subtleties of each chess piece, because in relatively clear-cut positions I could focus on what was essential. I was also gradually internalizing a marvelous methodology of learning—the play between knowledge, intuition, and creativity.” (pp. 33-34)
Those students who focused on openings tried to win fast. If they weren’t triumphant quickly, however, they got into trouble. They didn’t know how to navigate through a middlegame, especially not Josh’s complicated middlegames. They were “crippled by the horizon imposed on them by their teachers.” (p. 38)
The parallels to trading should be apparent. Beginning traders are transfixed with entries. They rarely think about exits, let along how they’re going to get from entry to exit. Often they simply invert an entry to define an exit, as if entering and exiting a trade were simply two sides of the same coin. (Yes, I know that even some advanced systems proceed this way.) Short of learning a few ground rules about stops, they figure that the middle will pretty well take care of itself.
We need not overcomplicate trading, but it’s imperative to focus on what really matters. We have to learn to trade in such a way that we’re more than snipers. (The high-frequency crowd is pretty well controlling that space.) We have to be prepared for a struggle. We have to learn when to defend our position, when to become aggressive, and when to walk away. I suggest that the least critical part of the trade is the entry and the hardest part of the trade is the middle. So why not start with the end game?
* * *
This will be my last post on The Art of Learning. For those who missed the earlier installments, here they are:
Two approaches to learning
Losing to win, investment in loss, not repeating mistakes
Using adversity
Growth in mastery, the hermit crab between shells
Matching style to temperament
Waitzkin claims that a person learning a new skill should lay a “solid foundation by studying positions of reduced complexity (endgame before opening)” and clear principles. For instance, when the six-year-old Josh was learning chess his mentor started with just three pieces on the board—king and pawn against king. “Over time,” he says, he “gained an excellent intuitive feel for the power of the king and the subtlety of the pawn.” “Layer by layer,” Waitzkin continues, “we built up my knowledge and my understanding of how to transform axioms into fuel for creative insight. Then we turned to rook endings, bishop endings, knight endings, . . . exploring the operating principles behind positions that I might never see again. This method of study gave me a feeling for the beautiful subtleties of each chess piece, because in relatively clear-cut positions I could focus on what was essential. I was also gradually internalizing a marvelous methodology of learning—the play between knowledge, intuition, and creativity.” (pp. 33-34)
Those students who focused on openings tried to win fast. If they weren’t triumphant quickly, however, they got into trouble. They didn’t know how to navigate through a middlegame, especially not Josh’s complicated middlegames. They were “crippled by the horizon imposed on them by their teachers.” (p. 38)
The parallels to trading should be apparent. Beginning traders are transfixed with entries. They rarely think about exits, let along how they’re going to get from entry to exit. Often they simply invert an entry to define an exit, as if entering and exiting a trade were simply two sides of the same coin. (Yes, I know that even some advanced systems proceed this way.) Short of learning a few ground rules about stops, they figure that the middle will pretty well take care of itself.
We need not overcomplicate trading, but it’s imperative to focus on what really matters. We have to learn to trade in such a way that we’re more than snipers. (The high-frequency crowd is pretty well controlling that space.) We have to be prepared for a struggle. We have to learn when to defend our position, when to become aggressive, and when to walk away. I suggest that the least critical part of the trade is the entry and the hardest part of the trade is the middle. So why not start with the end game?
* * *
This will be my last post on The Art of Learning. For those who missed the earlier installments, here they are:
Two approaches to learning
Losing to win, investment in loss, not repeating mistakes
Using adversity
Growth in mastery, the hermit crab between shells
Matching style to temperament
Tuesday, January 12, 2010
Success breeds success; with failure it’s just try, try again
On December 1 I wrote about trading and the problem of random reinforcement, one of my more popular posts. But what happens in those areas of trading that don’t fall prey to the random reinforcement of the markets? That is, what happens when we are actually rewarded for doing something right and not rewarded or punished for doing something wrong?
A column by Scott Berinato in the latest Harvard Business Review looks at a study of monkey learning where reinforcement was not random: the monkey was rewarded if he did a certain task correctly and got no reward if he did it incorrectly. Importantly, the researchers expanded the literature by monitoring the brain activity of the monkey both during and after he performed the task.
Old saws are often true. In this case, that success breeds success. After the monkey performed the task correctly “neurons in the prefrontal cortex and striatum, where the brain tracks success and failure, sharpened their tuning.” Moreover, the changes lingered for several seconds, “making brain activity more efficient the next time the monkey did the task. Thereafter, each success was processed more efficiently. That is, the monkey had learned.”
After failure, however, there was little change in brain activity. The brain stored no information about what had gone wrong, even though the task was simple in structure: if A, then x; if B, then y. There weren’t exactly 1000 ways to fail. But the brain didn’t know what to store, so the monkey didn’t learn from his failure. “The monkey just tried, tried again.”
Indeed, this is the problem with failing. In most cases if we knew why we failed, we probably wouldn’t have failed in the first place. If we take a second stab at the problem without knowing what went wrong the first time around, assuming that we are bright (or sane) enough not to do exactly the same failing thing again, we probably won’t be any better off. Think about trying to solve the Rubik’s cube without a game plan or an online cheat sheet. It’s just the poor failing monkey at work again.
So if, to make this research relevant to everyday trading decisions, we’re confronted with the problem of random reinforcement in our individual trades and if we can’t make sense of many of our non-random failures, the only thing we can hang onto are our non-random successes. Well, that’s not the end of the world. We all have some successes—from clicking on the right button to enter a trade to controlling risk appropriately. And success (with practice) breeds success, though of course it never manages to eliminate non-random failures.
Also, on the bright side, since we aren’t monkeys we can read about how to do things. Want to install a lock and haven’t a clue how? The Internet will provide instructions. Want to build a trading system and don’t know where to start? Again, there are lots of resources, from books to web sites to blog posts! So we don’t always have to be on the frontier; we don’t have to be Edisons discovering a thousand ways not to do something. We’ll still have plenty of non-random failures, many of which we won’t learn from. But between successes and instructions to prevent failure we’re a lot better off than the laboratory monkey.
Monday, January 11, 2010
Optimization
I have decried curve fitting in previous posts but have never taken a serious look at optimization. Jaekle and Tomasini in Trading Systems (2009) contend that everybody optimizes in one way or another. The question is how well they do it. Done well, it is useful in system trading; by contrast, “its aberration, namely curve fitting or over-optimisation” has no forecasting power.
So how do we go about optimizing a promising system and checking it for robustness? First of all, we have to respect the constraints of degrees of freedom, described in an earlier post. We want to keep the number of inputs, conditions, and variables as small as possible. If we have multiple inputs that need to be optimized, it’s best to test one or two per turn while all other inputs are kept static. Second, we must decide on the size of the steps in our optimization software. For instance, a system developer who wants to optimize both a short-term moving average (say, 1 to 20 periods) and a long-term moving average (20 to 200) should try to match as closely as possible the relative step size between the two averages. In this case we could use a step of 2 for the short-term and a step of 20 for the long-term moving average.
Once having optimized a system, we have to decide whether it is robust on its surface and, if it is, what its most robust input values are. If “the average results are positive then we can assume that the trading system is a robust one. If you are more statistically inclined you can also subtract the standard deviation (or a multiple of it) from the average net profit and check if the average net profit remains positive in this case.” (p. 23) Assuming that the system is robust, we are looking for that area of the profit chart where profit tops and, even as we change inputs, profit remains almost constant. That is, we want a plateau, not a spike. (By the way, we don’t have to optimize for profit; we might want to optimize for minimum drawdown.)
We’re not finished yet, not by a long shot. We need to assess the forecasting power of the system on out-of-sample data. The quick, easy, and increasingly obsolete way to check is to apply the optimized system on data we kept outside the optimization process (usually 10% to 20% of the data window). If it performs in a similar fashion on the unseen data, it is robust.
The more efficient, more precise testing method is walk forward analysis, which can either be rolling or anchored. Let’s look at an example of rolling walk forward optimization. Assume that we used data from the years 2003 through 2005 for our initial optimization. Then we see how the system performs in 2006. The next step is to walk forward a year, using data from 2004 through 2006, re-optimize and apply the best parameters from this period to 2007. Add the performance results of 2007 to those of 2006. Continue to walk forward to the 2005-2007 period and apply the best parameters to 2008. We now have a three-year out-of-sample track record that has adapted to market changes. The results from this three-year period are, in effect (as long as we include realistic slippage and commissions figures), “real-time” results.
Of course, nothing is ever straightforward in trading. In doing a walk forward analysis, how long a study period should we use, how long an application period? What should we choose as our measure of performance? And a caveat: if the markets are fickle, we can change our parameters just in time to have our system underperform in the market’s new phase.
So how do we go about optimizing a promising system and checking it for robustness? First of all, we have to respect the constraints of degrees of freedom, described in an earlier post. We want to keep the number of inputs, conditions, and variables as small as possible. If we have multiple inputs that need to be optimized, it’s best to test one or two per turn while all other inputs are kept static. Second, we must decide on the size of the steps in our optimization software. For instance, a system developer who wants to optimize both a short-term moving average (say, 1 to 20 periods) and a long-term moving average (20 to 200) should try to match as closely as possible the relative step size between the two averages. In this case we could use a step of 2 for the short-term and a step of 20 for the long-term moving average.
Once having optimized a system, we have to decide whether it is robust on its surface and, if it is, what its most robust input values are. If “the average results are positive then we can assume that the trading system is a robust one. If you are more statistically inclined you can also subtract the standard deviation (or a multiple of it) from the average net profit and check if the average net profit remains positive in this case.” (p. 23) Assuming that the system is robust, we are looking for that area of the profit chart where profit tops and, even as we change inputs, profit remains almost constant. That is, we want a plateau, not a spike. (By the way, we don’t have to optimize for profit; we might want to optimize for minimum drawdown.)
We’re not finished yet, not by a long shot. We need to assess the forecasting power of the system on out-of-sample data. The quick, easy, and increasingly obsolete way to check is to apply the optimized system on data we kept outside the optimization process (usually 10% to 20% of the data window). If it performs in a similar fashion on the unseen data, it is robust.
The more efficient, more precise testing method is walk forward analysis, which can either be rolling or anchored. Let’s look at an example of rolling walk forward optimization. Assume that we used data from the years 2003 through 2005 for our initial optimization. Then we see how the system performs in 2006. The next step is to walk forward a year, using data from 2004 through 2006, re-optimize and apply the best parameters from this period to 2007. Add the performance results of 2007 to those of 2006. Continue to walk forward to the 2005-2007 period and apply the best parameters to 2008. We now have a three-year out-of-sample track record that has adapted to market changes. The results from this three-year period are, in effect (as long as we include realistic slippage and commissions figures), “real-time” results.
Of course, nothing is ever straightforward in trading. In doing a walk forward analysis, how long a study period should we use, how long an application period? What should we choose as our measure of performance? And a caveat: if the markets are fickle, we can change our parameters just in time to have our system underperform in the market’s new phase.
Sunday, January 10, 2010
Neanderthals and traders
The other night PBS aired “The Human Spark.” (An online video is available.) A main theme was why the Neanderthals died out. Altogether the Neanderthals lasted some 200,000 years, migrating from Africa to Europe; after about a 40,000-year stay in Europe, they were no more.
Researchers suggest that one problem with the Neanderthals was that they exhibited a remarkable tenacity; they didn’t change. Put less strongly, they were flexible but not innovative. They picked from the same tool kit over and over again.
It’s important to note that they survived for a long time stuck firmly in their, by today’s standards, unhealthful Neanderthal rut—for instance, eating only meat and avoiding everything with roots in the ground as well as readily available fish. But eventually they disappeared from the face of the earth.
I bring up the Neanderthals because of parallels to traders who follow a common piece of advice. To wit, stick to your trading plan but be flexible. It’s not important here to comment on the difficulty of being both dogged and flexible. Presumably the Neanderthals managed, so I guess we can too. The problem is that very few people can win in the long run if they remain squarely within the confines of a routine.
Traders should set aside a little time, at least once a week, to think about the markets from a different perspective. To investigate a different trading vehicle. Or to rethink risk management. There are many possibilities. The trader need not shift his strategy, assuming it’s working. But he should be aware of ways in which even a winning strategy can be enhanced and should be prepared for the time that his strategy starts to be battered.
Who wants to be compared to a Neanderthal? Worse, who wants to share their fate?
Researchers suggest that one problem with the Neanderthals was that they exhibited a remarkable tenacity; they didn’t change. Put less strongly, they were flexible but not innovative. They picked from the same tool kit over and over again.
It’s important to note that they survived for a long time stuck firmly in their, by today’s standards, unhealthful Neanderthal rut—for instance, eating only meat and avoiding everything with roots in the ground as well as readily available fish. But eventually they disappeared from the face of the earth.
I bring up the Neanderthals because of parallels to traders who follow a common piece of advice. To wit, stick to your trading plan but be flexible. It’s not important here to comment on the difficulty of being both dogged and flexible. Presumably the Neanderthals managed, so I guess we can too. The problem is that very few people can win in the long run if they remain squarely within the confines of a routine.
Traders should set aside a little time, at least once a week, to think about the markets from a different perspective. To investigate a different trading vehicle. Or to rethink risk management. There are many possibilities. The trader need not shift his strategy, assuming it’s working. But he should be aware of ways in which even a winning strategy can be enhanced and should be prepared for the time that his strategy starts to be battered.
Who wants to be compared to a Neanderthal? Worse, who wants to share their fate?
Saturday, January 9, 2010
Nonrandom random generators
I often glean insights from odd sources. Over the holidays I read Pythagoras’ Revenge (Princeton University Press, 2009), a mathematical mystery by Arturo Sangalli. His goal was not to write the best mystery ever (he didn’t) but to introduce mathematical concepts, “some of them rather challenging and with philosophical undertones, in an entertaining way.” (p. ix)
One of these concepts is that “all random number algorithms being used in computer programs are in fact only pseudo random, and not simply for lack of ingenuity on the part of the mathematicians who created them but due to the existence of an essential barrier inherent in the concept of ‘randomness’ itself.” The problem is this: randomness is equivalent to incompressibility. That is, there is no shorter way to describe a random binary sequence than to list all its bits. So “any sequence s whose bits are obtained by executing a computer program is automatically compressible (for the program is a compressed version of s) and hence it is nonrandom.” (p. 72)
I doubt that this nonrandom quality of so-called random generators will create dramatic errors in trading algorithms; we don’t use particularly long sequences. The problem arises when “billions of those random numbers are employed to simulate the evolution of a complex system.” In this case “the accuracy of the final results may directly depend on the quality of the ‘randomness’ built into the program.” (p. 71)
But even though we shouldn’t lie awake at night worrying about the reliability of the random generators we use, I thought this point was worth sharing. I for one love tramping around in the world of paradoxes and quasi-paradoxes.
One of these concepts is that “all random number algorithms being used in computer programs are in fact only pseudo random, and not simply for lack of ingenuity on the part of the mathematicians who created them but due to the existence of an essential barrier inherent in the concept of ‘randomness’ itself.” The problem is this: randomness is equivalent to incompressibility. That is, there is no shorter way to describe a random binary sequence than to list all its bits. So “any sequence s whose bits are obtained by executing a computer program is automatically compressible (for the program is a compressed version of s) and hence it is nonrandom.” (p. 72)
I doubt that this nonrandom quality of so-called random generators will create dramatic errors in trading algorithms; we don’t use particularly long sequences. The problem arises when “billions of those random numbers are employed to simulate the evolution of a complex system.” In this case “the accuracy of the final results may directly depend on the quality of the ‘randomness’ built into the program.” (p. 71)
But even though we shouldn’t lie awake at night worrying about the reliability of the random generators we use, I thought this point was worth sharing. I for one love tramping around in the world of paradoxes and quasi-paradoxes.
Friday, January 8, 2010
Matching style to temperament
Josh Waitzkin, in The Art of Learning, fleshes out the oft-repeated advice that your trading style has to match your temperament with autobiographical reflections on his ups and downs in chess. Between the ages of nine and seventeen he won eight individual National Championship titles and had many team chess achievements. “A key ingredient to my success in those years was that my style on the chessboard was a direct expression of my personality. It is my nature to revel in apparent chaos. . . . [A]s a young competitor I would guide critical chess games into positions of tremendous complexity with the confidence that I would be able to sort through the mayhem more effectively than my opponents.” (p. 41)
With the release of Searching for Bobby Fischer, Josh Waitzkin’s life started to change. First, he was becoming distracted by the fans. Second, he began training with a new Grandmaster who was “a systematic strategist with a passion for slow, subtle maneuvering.” He wanted Josh to become more like Anatoly Karpov and less like Bobby Fischer, more cold-blooded and less wild. He wanted Josh to give up his natural voice. As a result, the author says, he lost his “center of gravity as a competitor.” (p. 87) Perhaps, as he later came to think, he had been offered a rare opportunity to grow, but the fact was that “the effects of moving away from my natural voice as a competitor were particularly devastating.” (pp. 88-89)
Reflecting on how he came to be distanced (or distance himself) from chess, Waitzkin shares some hard-earned thoughts. “To my mind,” he writes, “the fields of learning and performance are an exploration of greyness—of the in-between. There is the careful balance of pushing yourself relentlessly, but not so hard that you melt down. Muscles and minds need to stretch to grow, but if stretched too thin, they will snap. A competitor needs to be process-oriented, always looking for stronger opponents to spur growth, but it is also important to keep on winning enough to maintain confidence. We have to release our current ideas to soak in new material, but not so much that we lose touch with our unique natural talents. Vibrant, creative idealism needs to be tempered by a practical, technical awareness.” (p. 88)
Read this last paragraph more than once. Josh Waitzkin lived these words.
With the release of Searching for Bobby Fischer, Josh Waitzkin’s life started to change. First, he was becoming distracted by the fans. Second, he began training with a new Grandmaster who was “a systematic strategist with a passion for slow, subtle maneuvering.” He wanted Josh to become more like Anatoly Karpov and less like Bobby Fischer, more cold-blooded and less wild. He wanted Josh to give up his natural voice. As a result, the author says, he lost his “center of gravity as a competitor.” (p. 87) Perhaps, as he later came to think, he had been offered a rare opportunity to grow, but the fact was that “the effects of moving away from my natural voice as a competitor were particularly devastating.” (pp. 88-89)
Reflecting on how he came to be distanced (or distance himself) from chess, Waitzkin shares some hard-earned thoughts. “To my mind,” he writes, “the fields of learning and performance are an exploration of greyness—of the in-between. There is the careful balance of pushing yourself relentlessly, but not so hard that you melt down. Muscles and minds need to stretch to grow, but if stretched too thin, they will snap. A competitor needs to be process-oriented, always looking for stronger opponents to spur growth, but it is also important to keep on winning enough to maintain confidence. We have to release our current ideas to soak in new material, but not so much that we lose touch with our unique natural talents. Vibrant, creative idealism needs to be tempered by a practical, technical awareness.” (p. 88)
Read this last paragraph more than once. Josh Waitzkin lived these words.
Thursday, January 7, 2010
Degrees of freedom--KISS
I’m not the person you would ever hire to design a trading system, mainly because my programming skills are (being kind to myself) modest. But I think it’s critically important for every trader and investor, whatever his style, to know in principle how to go about developing a trading system. I plan to write a short series of posts on this topic geared to the intelligent novice. Today’s theme is the statistical concept of degrees of freedom.
“Degrees of freedom” is defined mathematically as the rank of a quadratic form. Well, that gets us nowhere fast. The statistical definition isn’t much better: the number of values in the final calculation of a statistic that are free to vary. But we know that the concept is critical in system development. Ralph Vince put it succinctly if not elegantly: “The key to ensure that you have a positive mathematical expectancy in the future is to not restrict your system’s degrees of freedom.” (The Mathematics of Money Management, p. 19)
Urban Jaekle and Emilio Tomasini, in Trading Systems: A New Approach to System Development and Portfolio Optimisation (Harriman House, 2009) tackle this subject from enough points of view that eventually even the most statistically challenged should understand the relevance of this concept in developing a trading system. First, a feeble statistical joke. A married man comments: “There is only one subject, my wife, and my degree of freedom is zero. I should increase my ‘sample size’ by looking at other women.” (p. 16) Second, building on this joke, an illustration by Robert Schulle: “In a scatter plot when there is only one data point, you cannot make any estimation of the regression line. The line can go in any direction . . . Here you have no degrees of freedom . . . for estimation (this may remind you of the joke about the married man). In order to plot a regression line you must have at least two data points (a wife and a mistress). In this case you have one degree of freedom for estimation. . . . In other words, the degree of freedom tells you the number of useful data for estimation. However, when you have two data points only, you can always join them to be a straight regression line and get a perfect correlation. . . Thus the lower the degree of freedom is, the poorer the estimation is.” (p. 17)
What the concept of the degrees of freedom is expressing in a rigorous way is the intuitive notion that the larger the sample size and the smaller the number of variables the better the estimation. Generally, the authors state, “less than 90% remaining degrees of freedom is considered too few.”
Let’s consider some examples so that we have a better idea of how to calculate degrees of freedom for practical purposes. We have a trading strategy that uses a 20-day average of highs and a 60-day average of lows and we’re working with a data sample of three years of highs, lows, opens, and closing prices for a total of 3120 data points (260 days per year x 3 x 4). The 20-day average uses 21 degrees of freedom (20 highs plus 1 more as a rule); the 60-day average uses 61 degrees of freedom (60 lows plus 1 as a rule). The total is 82 degrees of freedom. In percentage terms we’re using 2.6% degrees of freedom (82/3120), leaving 97.4% degrees of freedom. This sample size is adequate to the trading strategy.
Degrees of freedom don’t double count. For instance, if you are using a 5-day and a 10-day moving average of closes you would consume only 12 data points. The 5-day moving average is included in the 10-day moving average. So count only 10 plus 2 rules.
In brief, in order to produce a statistically reliable historical simulation you have match system complexity to sample size. Or, as Vince argues, “You want to keep your system’s degrees of freedom as high as possible to ensure the positive mathematical expectation in the future. This is accomplished not only by eliminating, or at least minimizing, the number of optimizable parameters, but also by eliminating, or at least minimizing, as many of the system rules as possible. Every parameter you add, every rule you add, every little adjustment and qualification you add to your system diminishes its degrees of freedom. Ideally, you will have a system that is very primitive and simple, and that continually grinds out marginal profits over time. . . . [I]t is important that you realize that it really doesn’t matter how profitable the system is, so long as it is profitable. The money you will make trading will be made by how effective the money management you employ is.” (p. 19)
“Degrees of freedom” is defined mathematically as the rank of a quadratic form. Well, that gets us nowhere fast. The statistical definition isn’t much better: the number of values in the final calculation of a statistic that are free to vary. But we know that the concept is critical in system development. Ralph Vince put it succinctly if not elegantly: “The key to ensure that you have a positive mathematical expectancy in the future is to not restrict your system’s degrees of freedom.” (The Mathematics of Money Management, p. 19)
Urban Jaekle and Emilio Tomasini, in Trading Systems: A New Approach to System Development and Portfolio Optimisation (Harriman House, 2009) tackle this subject from enough points of view that eventually even the most statistically challenged should understand the relevance of this concept in developing a trading system. First, a feeble statistical joke. A married man comments: “There is only one subject, my wife, and my degree of freedom is zero. I should increase my ‘sample size’ by looking at other women.” (p. 16) Second, building on this joke, an illustration by Robert Schulle: “In a scatter plot when there is only one data point, you cannot make any estimation of the regression line. The line can go in any direction . . . Here you have no degrees of freedom . . . for estimation (this may remind you of the joke about the married man). In order to plot a regression line you must have at least two data points (a wife and a mistress). In this case you have one degree of freedom for estimation. . . . In other words, the degree of freedom tells you the number of useful data for estimation. However, when you have two data points only, you can always join them to be a straight regression line and get a perfect correlation. . . Thus the lower the degree of freedom is, the poorer the estimation is.” (p. 17)
What the concept of the degrees of freedom is expressing in a rigorous way is the intuitive notion that the larger the sample size and the smaller the number of variables the better the estimation. Generally, the authors state, “less than 90% remaining degrees of freedom is considered too few.”
Let’s consider some examples so that we have a better idea of how to calculate degrees of freedom for practical purposes. We have a trading strategy that uses a 20-day average of highs and a 60-day average of lows and we’re working with a data sample of three years of highs, lows, opens, and closing prices for a total of 3120 data points (260 days per year x 3 x 4). The 20-day average uses 21 degrees of freedom (20 highs plus 1 more as a rule); the 60-day average uses 61 degrees of freedom (60 lows plus 1 as a rule). The total is 82 degrees of freedom. In percentage terms we’re using 2.6% degrees of freedom (82/3120), leaving 97.4% degrees of freedom. This sample size is adequate to the trading strategy.
Degrees of freedom don’t double count. For instance, if you are using a 5-day and a 10-day moving average of closes you would consume only 12 data points. The 5-day moving average is included in the 10-day moving average. So count only 10 plus 2 rules.
In brief, in order to produce a statistically reliable historical simulation you have match system complexity to sample size. Or, as Vince argues, “You want to keep your system’s degrees of freedom as high as possible to ensure the positive mathematical expectation in the future. This is accomplished not only by eliminating, or at least minimizing, the number of optimizable parameters, but also by eliminating, or at least minimizing, as many of the system rules as possible. Every parameter you add, every rule you add, every little adjustment and qualification you add to your system diminishes its degrees of freedom. Ideally, you will have a system that is very primitive and simple, and that continually grinds out marginal profits over time. . . . [I]t is important that you realize that it really doesn’t matter how profitable the system is, so long as it is profitable. The money you will make trading will be made by how effective the money management you employ is.” (p. 19)
Wednesday, January 6, 2010
Growth in mastery, the hermit crab between shells
Josh Waitzkin in The Art of Learning invokes a marvelous image to describe the growth process. The hermit crab protects itself with a salvaged shell it carries on its back. As it grows it has to find a larger shell; it never fits into the same shell for more than a few days. “So the slow, lumbering creature goes on a quest for a new home. If an appropriate new shell is not found quickly, a terribly delicate moment of truth arises. A soft creature that is used to the protection of built-in armor must now go out into the world, exposed to predators in all its mushy vulnerability.” The only way the hermit crab can avoid replacing its first second-hand shell with a second second-hand shell is by becoming anorexic, “starving itself so it doesn’t grow to have to find a new shell.” (p. 33)If traders are to increase their mastery, they have step up from under their protective shells and expose themselves to unfamiliar, potentially dangerous conditions. Enough said. Others have written volumes on the topic, but I just loved the image.
Tuesday, January 5, 2010
Bromma, How to Make Money in Alternative Investments
I come from a family that never invested a penny in the stock market. They were risk averse and distrustful of Wall Street. Nonetheless, they managed to increase their wealth bit by bit through a combination of frugality and assorted no- to low-risk schemes. For instance, when silver started to appreciate in value my father would go every night to someone he knew who had vending machines and buy the day’s take. My parents would then sort through the coins looking for silver, sell the silver coins to a dealer, and deposit the remainder in the bank. This was an absolutely no-risk strategy on which they got a handsome return. They were, of course, sorely disappointed when silver cratered, but all they lost was a source of income, not invested money.
I thought of them when reading Hubert and Lisa Moren Bromma’s book How to Make Money in Alternative Investments (McGraw-Hill, 2010). The Brommas outline an assortment of methods for making money outside the traditional markets. For instance, they describe opportunities in private lending and business-to-business cash flows, in precious metals and natural resources (including green investments), and in real estate (domestic and international). These investments can be made through an IRA or 401(k), though currently only 1.5% of all the money in retirement accounts is devoted to anything other than stocks, bonds, mutual funds, and CDs.
The book is an occasional eye-opener for the naïve. For instance, the authors describe how a person could get involved in floor plan auto financing. That is, he would lend money to a used car dealer to buy cars at auction; as the dealer sells each car he pays off the loan and gets title to the car. This business at the retail level can be even sleazier than we might imagine. The authors describe the operations of one used car lot. The lot owner would buy a car at auction for $400 and would then sell it for $1,600 with $400 down and the remaining $1,200 financed at the highest rate allowable under state usury laws—say two years at 21%. He broke even the minute the car left the lot. Since the used car dealer didn’t run any credit checks, he ended up repossessing about 75 percent of the cars he sold. No problem; he just resold them under the same terms—another guaranteed $400 profit and a shot at getting at least some of the $1,200 he financed.
The Brommas stress the importance of due diligence in making any of the investments they describe in their book. For instance, purchasing tax liens can be a good investment for someone with a modest amount of cash. You will normally get a handsome interest rate and can expect to be paid in the vast majority of cases because the property owner can’t sell the property until he pays off the tax lien. But you have to make sure that there are no legal complications or environmental issues that could snarl the investment.
This book opens the door to a world beyond the normal financial markets and offers the investor some opportunities for genuine diversification. I found it a refreshing break from the run-of-the-mill investing books.
I thought of them when reading Hubert and Lisa Moren Bromma’s book How to Make Money in Alternative Investments (McGraw-Hill, 2010). The Brommas outline an assortment of methods for making money outside the traditional markets. For instance, they describe opportunities in private lending and business-to-business cash flows, in precious metals and natural resources (including green investments), and in real estate (domestic and international). These investments can be made through an IRA or 401(k), though currently only 1.5% of all the money in retirement accounts is devoted to anything other than stocks, bonds, mutual funds, and CDs.
The book is an occasional eye-opener for the naïve. For instance, the authors describe how a person could get involved in floor plan auto financing. That is, he would lend money to a used car dealer to buy cars at auction; as the dealer sells each car he pays off the loan and gets title to the car. This business at the retail level can be even sleazier than we might imagine. The authors describe the operations of one used car lot. The lot owner would buy a car at auction for $400 and would then sell it for $1,600 with $400 down and the remaining $1,200 financed at the highest rate allowable under state usury laws—say two years at 21%. He broke even the minute the car left the lot. Since the used car dealer didn’t run any credit checks, he ended up repossessing about 75 percent of the cars he sold. No problem; he just resold them under the same terms—another guaranteed $400 profit and a shot at getting at least some of the $1,200 he financed.
The Brommas stress the importance of due diligence in making any of the investments they describe in their book. For instance, purchasing tax liens can be a good investment for someone with a modest amount of cash. You will normally get a handsome interest rate and can expect to be paid in the vast majority of cases because the property owner can’t sell the property until he pays off the tax lien. But you have to make sure that there are no legal complications or environmental issues that could snarl the investment.
This book opens the door to a world beyond the normal financial markets and offers the investor some opportunities for genuine diversification. I found it a refreshing break from the run-of-the-mill investing books.
Monday, January 4, 2010
Using adversity
Josh Waitzkin learned to push himself. With seven weeks to go until he was scheduled to defend his U.S. Push Hands middleweight championship he decided to enter the super heavyweight division of a regional tournament for some extra training. He weighed in at 170 pounds, his opponent at 230 pounds. With only a minute to go the opponent broke Josh’s hand.
Despite the doctor’s pronouncement that there was no chance he could compete at the Nationals because, although his hand might heal in six weeks, his arm would have atrophied from its immobilization from the elbow down, Josh was determined. He was back in training the day after he got his cast. Initially, he didn’t do the usual sort of physical training. Instead, he worked on heightening his sensitivity to “incoming power and intention.” He concentrated on the mental side of his game.
Then he worked to cultivate his weaker side so that his left hand could do everything. He came to realize that if he could control two of his opponent’s limbs with one of his, he could easily use his other arm for “free-pickings.” This principle, he suggests, applies not only to nearly all contact sports but to chess as well: “Any moment that one piece can control, inhibit, or tie down two or more pieces, a potentially critical imbalance is created on the rest of the board.” (p. 130) By extension, the principle can even be applied in art of negotiation or in war. Or, in the financial markets, call it the principle of leverage.
Finally he used intense visualization practice to try to keep his right arm strong. Four days before the Nationals the doctor cleared him to compete; his bone had knit, and he had barely atrophied at all. Slightly favoring his newly empowered left arm, he won the Nationals.
What is the moral of this story? Waitzkin says that one thing he has learned as a competitor is that “there are clear distinctions between what it takes to be decent, what it takes to be good, what it takes to be great, and what it takes to be among the best.” He says that in order to be among the best he has to “take risks others would avoid, always optimizing the learning potential of the moment and turning adversity to [his] advantage.” Adversity, real or even imagined, can become a “tremendous source of creative inspiration.” It raises us out of routines in which we are simply going through the motions. It forces us to “get imaginative.” It keeps our minds engaged, searching.
I realize that many traders have disaster drills, but, however important they are, they are often no more than a series of standard responses—the same kinds of responses that fire departments teach. How many traders have thought through possible adjustments to or hedges of their positions in response to some adversity? How do you dig yourself out of a hole? What if the number of trades you made had to be cut in half? What if your dog decided you needed to get up regularly at 4 a.m.? There are lots of scenarios we can envision that might just help take us to the next level of mastery.
Despite the doctor’s pronouncement that there was no chance he could compete at the Nationals because, although his hand might heal in six weeks, his arm would have atrophied from its immobilization from the elbow down, Josh was determined. He was back in training the day after he got his cast. Initially, he didn’t do the usual sort of physical training. Instead, he worked on heightening his sensitivity to “incoming power and intention.” He concentrated on the mental side of his game.
Then he worked to cultivate his weaker side so that his left hand could do everything. He came to realize that if he could control two of his opponent’s limbs with one of his, he could easily use his other arm for “free-pickings.” This principle, he suggests, applies not only to nearly all contact sports but to chess as well: “Any moment that one piece can control, inhibit, or tie down two or more pieces, a potentially critical imbalance is created on the rest of the board.” (p. 130) By extension, the principle can even be applied in art of negotiation or in war. Or, in the financial markets, call it the principle of leverage.
Finally he used intense visualization practice to try to keep his right arm strong. Four days before the Nationals the doctor cleared him to compete; his bone had knit, and he had barely atrophied at all. Slightly favoring his newly empowered left arm, he won the Nationals.
What is the moral of this story? Waitzkin says that one thing he has learned as a competitor is that “there are clear distinctions between what it takes to be decent, what it takes to be good, what it takes to be great, and what it takes to be among the best.” He says that in order to be among the best he has to “take risks others would avoid, always optimizing the learning potential of the moment and turning adversity to [his] advantage.” Adversity, real or even imagined, can become a “tremendous source of creative inspiration.” It raises us out of routines in which we are simply going through the motions. It forces us to “get imaginative.” It keeps our minds engaged, searching.
I realize that many traders have disaster drills, but, however important they are, they are often no more than a series of standard responses—the same kinds of responses that fire departments teach. How many traders have thought through possible adjustments to or hedges of their positions in response to some adversity? How do you dig yourself out of a hole? What if the number of trades you made had to be cut in half? What if your dog decided you needed to get up regularly at 4 a.m.? There are lots of scenarios we can envision that might just help take us to the next level of mastery.
Sunday, January 3, 2010
“Or else”—the yurt
In The Daily Trading Coach Brett Steenbarger wrote about the power of “or else” in motivating action. Well, for those of you who have made resolutions about your trading for 2010, here’s an “or else” article you might consider compliments of The New York Times. Think about waking up in a yurt in a remote town in Alaska (no roads to anywhere, not even a bridge to nowhere) still able to access your trading account via broadband but without running water (hence no shower or toilet). The inside temperature is freezing; the wood stove that needs to be fed every 15 to 30 minutes doesn’t exactly make the yurt toasty. You’re neither Mongolian nor Eskimo; you’re part of an overeducated family of three, including an 11-month-old son, who manages to live on about $15,000 a year.Since I’ve just gone through a series of brushes with Alaskan yurt existence—first an iced vent stack that made the upstairs toilet and shower unusable for several days, then a loss of heat fortunately resolved by the heating oil company in a few hours, and finally the standard winter problem of the long, impassable driveway—I have absolutely no romantic notions of living in the Alaska wilderness. For me this particular yurt is a powerful “or else” image! What’s yours?
Come tomorrow I'll go back to my serious self. Here's what's planned: more insights from Josh Waitzkin on learning, a short series on system development, a couple of research findings from behavioral finance and psychology, and a look at a new book on alternative investments. So, as they say, stay tuned.
Saturday, January 2, 2010
Stamps and the proposed trader tax
With the exception of one very black swan (I was a cheerleader in the ninth grade—and considered it one of my greatest accomplishments) I have always been something of a nerd. I say “something of” because I don’t consider myself a nerd. Nerds to my mind are the quants of the world—mathematicians and computer scientists. I just spend more time thinking than average folk. I think about Bach, growing dill, chaos. I’m a hopelessly eclectic intellectual.
Did I ever stand a chance of being anything else? Here’s a picture of me as an overly serious, chubby 19-month-old. I’m now older and skinnier but remain far too serious and am still not exactly a fashion plate.
One manifestation of my intellectual eclecticism is a stamp collection that is more attractive and hence hugely less valuable than Bill Gross’s. One thing I never collected was tax stamps, but when I saw the Designing Better Futures article I was intrigued. Nick Gogerty revisits the history of stock, commodity, and derivatives transaction taxes by looking at tax stamps. It’s both fascinating and scary. Take a look.
Did I ever stand a chance of being anything else? Here’s a picture of me as an overly serious, chubby 19-month-old. I’m now older and skinnier but remain far too serious and am still not exactly a fashion plate.One manifestation of my intellectual eclecticism is a stamp collection that is more attractive and hence hugely less valuable than Bill Gross’s. One thing I never collected was tax stamps, but when I saw the Designing Better Futures article I was intrigued. Nick Gogerty revisits the history of stock, commodity, and derivatives transaction taxes by looking at tax stamps. It’s both fascinating and scary. Take a look.
Friday, January 1, 2010
Happy 2010!
For those of you who enjoy Maira Kalman's work, here is the final installment of "And the Pursuit of Happiness," which will appear as a book in October 2010. It's a wonderful way to kick off the new year.
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