Monday, May 31, 2010
NAAIM papers
For those in the U.S. experiencing withdrawal symptoms as the result of a three-day weekend and for everybody else with a little bit of time on his hands, here's a set of papers submitted for the NAAIM 2010 Wagner Award, all downloadable. Thanks to Mebane Faber's World Beta blog for the heads up.
Friday, May 28, 2010
Backtesting data
A change of pace from my usual posts, but I recently saw a note from someone looking for the best tick by tick data available for backtesting. He was willing to lay out a lot of money for the data, yet he didn’t have the wherewithal to capture this level of granularity in his live trading. So what’s the point? He might come up with a great system, but if he’s trading from a home computer with a cable modem he’ll either never see those ticks (since some data providers don’t update with every tick) or experience so much latency that his trades will bear no resemblance to those in his backtest.
It’s better to keep things consistent: if the broker through whom you execute your trades also provides intraday data, trade and backtest with this price data. And be realistic about the kinds of fills you can expect. If, for instance, you're trading off a volume chart instead of a time chart and your signal fires on the first bar of, let's say, five trending bars that occur in the course of a minute, do you really think you'll be filled anywhere close to your signal?
It’s better to keep things consistent: if the broker through whom you execute your trades also provides intraday data, trade and backtest with this price data. And be realistic about the kinds of fills you can expect. If, for instance, you're trading off a volume chart instead of a time chart and your signal fires on the first bar of, let's say, five trending bars that occur in the course of a minute, do you really think you'll be filled anywhere close to your signal?
Foster, Ticker Technique
Let me start by saying that I have no idea who authored Ticker Technique: The Art of Tape Reading (Traders Press, 2005). The book was originally published in 1965, but its focal point (part two of four parts) is an updated version of Orline D. Foster’s 1935 Ticker Technique. The other three parts expand on tape reading and include contributions by Herbert Liesner and Don Worden. Whoever the author was, he/she helped keep the tradition of tape reading alive and well.
Foster’s piece is only about 25 pages long, but it is both a first-rate introduction to tape reading for the novice and a quick refresher course for the technical trader. He writes about price, volume, breadth, and timing, all within the context of accumulation and distribution.
I’m not going to rehash the ideas presented in this book. If you’re familiar with them I would bore you; if you’re not I would lose you. Let me simply say that if you’re short on bookshelf space, you could most likely profit from replacing almost any of your more recent trading books with this one.
Foster’s piece is only about 25 pages long, but it is both a first-rate introduction to tape reading for the novice and a quick refresher course for the technical trader. He writes about price, volume, breadth, and timing, all within the context of accumulation and distribution.
I’m not going to rehash the ideas presented in this book. If you’re familiar with them I would bore you; if you’re not I would lose you. Let me simply say that if you’re short on bookshelf space, you could most likely profit from replacing almost any of your more recent trading books with this one.
Thursday, May 27, 2010
Can a trader’s life be meaningful?
[A prefatory meta-note: I personally have issues with what I’m writing here, but I know that many traders struggle to justify their chosen career path. So here, for those of you who suffer pangs of angst, is a philosopher’s (not my) take on your (and my) life.]
Susan Wolf, author of Meaning in Life and Why It Matters (Princeton University Press, 2010), would, I suspect, struggle in passing judgment on a trader’s life. She sets forth two criteria for meaningfulness. First, a person must love something and, second, it must be worthy of love. “Essentially, the idea is that a person’s life can be meaningful only if she cares fairly deeply about some thing or things, only if she is gripped, excited, interested, engaged, or . . . if she loves something—as opposed to being bored by or alienated from most or all that she does. Even a person who is so engaged, however, will not live a meaningful life if the objects or activities with which she is so occupied are worthless. A person who loves smoking pot all day long, or doing endless crossword puzzles, [or worse, as the author adds in a personal confession later in the text, doing Sudokus] and has the luxury of being able to indulge in this without restraint does not thereby make her life meaningful.” (p. 9) The things and activities we care about must link us to our world in a positive way.
As paradigms of a meaningful life, we might nominate Gandhi, Einstein, or Cézanne. They all actively engaged in projects of worth. Sisyphus is usually portrayed as the exemplar of a meaningless existence.
What kinds of things give meaning to life? The activities that engage us must have a value that “is in part independent of one’s own attitude to it.” (p. 37) But who’s to say which projects are independently valuable? Wolf answers, “No one in particular.” And yet “whether a life is meaningful has specifically to do with whether one’s life can be said to be worthwhile from an external point of view. A meaningful life is one that would not be considered pointless or gratuitous, even from an impartial perspective.” (p. 42)
I fear that the trader is quickly starting to look more and more like Sisyphus. But, wait, there’s hope! Wolf, struggling with the question of objective value and trying to distance herself from a narrow academic perspective, suggests that “almost anything to which a significant number of people have shown themselves to be deeply attached over a significant length of time, has or relates to some positive value.” (p. 128) Trading certainly has a long tradition and has attracted a sizable community.
Perhaps in that respect trading can be compared to basketball. Wolf writes: “Presumably, there is nothing especially valuable about a group of people running around, trying to throw a ball into a hoop, while another group runs around trying to stop them. Nor does the adoption of extra rules, constraining the moves that are permitted, lift their running around into the category of practices that in themselves the participants have reason to be proud of from a detached perspective. Even if basketball, removed or abstracted from its now established place in our culture, is not an objectively valuable activity in itself, it provides an opportunity for much that is of value. It provides an opportunity for the cultivation and exercise of skill and virtue, for the building of relationships, and for the communion that comes from enthusiasm for and immersion in a shared activity.” (p. 129)
In brief, according to Wolf we can freely admit that in and of itself scalping ticks in the e-mini S&P is a pretty worthless activity. (Of course, worthless does not mean profitless.) But, done with passion and ever-increasing skill, it can nevertheless be the lynchpin of a meaningful life.
Susan Wolf, author of Meaning in Life and Why It Matters (Princeton University Press, 2010), would, I suspect, struggle in passing judgment on a trader’s life. She sets forth two criteria for meaningfulness. First, a person must love something and, second, it must be worthy of love. “Essentially, the idea is that a person’s life can be meaningful only if she cares fairly deeply about some thing or things, only if she is gripped, excited, interested, engaged, or . . . if she loves something—as opposed to being bored by or alienated from most or all that she does. Even a person who is so engaged, however, will not live a meaningful life if the objects or activities with which she is so occupied are worthless. A person who loves smoking pot all day long, or doing endless crossword puzzles, [or worse, as the author adds in a personal confession later in the text, doing Sudokus] and has the luxury of being able to indulge in this without restraint does not thereby make her life meaningful.” (p. 9) The things and activities we care about must link us to our world in a positive way.
As paradigms of a meaningful life, we might nominate Gandhi, Einstein, or Cézanne. They all actively engaged in projects of worth. Sisyphus is usually portrayed as the exemplar of a meaningless existence.
What kinds of things give meaning to life? The activities that engage us must have a value that “is in part independent of one’s own attitude to it.” (p. 37) But who’s to say which projects are independently valuable? Wolf answers, “No one in particular.” And yet “whether a life is meaningful has specifically to do with whether one’s life can be said to be worthwhile from an external point of view. A meaningful life is one that would not be considered pointless or gratuitous, even from an impartial perspective.” (p. 42)
I fear that the trader is quickly starting to look more and more like Sisyphus. But, wait, there’s hope! Wolf, struggling with the question of objective value and trying to distance herself from a narrow academic perspective, suggests that “almost anything to which a significant number of people have shown themselves to be deeply attached over a significant length of time, has or relates to some positive value.” (p. 128) Trading certainly has a long tradition and has attracted a sizable community.
Perhaps in that respect trading can be compared to basketball. Wolf writes: “Presumably, there is nothing especially valuable about a group of people running around, trying to throw a ball into a hoop, while another group runs around trying to stop them. Nor does the adoption of extra rules, constraining the moves that are permitted, lift their running around into the category of practices that in themselves the participants have reason to be proud of from a detached perspective. Even if basketball, removed or abstracted from its now established place in our culture, is not an objectively valuable activity in itself, it provides an opportunity for much that is of value. It provides an opportunity for the cultivation and exercise of skill and virtue, for the building of relationships, and for the communion that comes from enthusiasm for and immersion in a shared activity.” (p. 129)
In brief, according to Wolf we can freely admit that in and of itself scalping ticks in the e-mini S&P is a pretty worthless activity. (Of course, worthless does not mean profitless.) But, done with passion and ever-increasing skill, it can nevertheless be the lynchpin of a meaningful life.
Wednesday, May 26, 2010
Apropos of nothing
“Philosophy, even the philosophy of human values—and for that matter the search after knowledge and understanding in general—needs practical justification like a fish needs a bicycle.”
--Nomy Arpaly, commenting in Susan Wolf’s Meaning in Life and Why It Matters (about which much more tomorrow)
--Nomy Arpaly, commenting in Susan Wolf’s Meaning in Life and Why It Matters (about which much more tomorrow)
A question about CME order execution
After reading Chasing the Same Signals I started thinking about order execution, about which I know next to nothing. So I went to the CME site to educate myself. Alas, I’m still ignorant.
In a study dating from March 2009 the CME analyzed immediately executable orders--that is, orders that can be at least partially executed at the time they reach the central limit order book. One finding puzzled me: “order quantities between six and 49 contracts are being executed with lower market impact than orders of five or fewer contracts.” Market impact means “the difference between the middle of the market at the time of the order’s arrival and the order’s execution price, or the average execution price in the event of fills at different prices.”
The fact that the small trader often doesn’t get the best price is not a function of speed of execution. Orders to buy or sell between one and five contracts were filled within 30 milliseconds after their arrival at CME Globex 86% of the time and within 50 milliseconds 91% of the time. Orders for six to ten contracts were filled within 30 milliseconds 85% of the time and within 50 milliseconds 93% of the time. As order size increased so did average fill time.
Why do the smallest traders not get the best price? Perhaps they’re simply addicted to market orders and by definition always give up the spread. Perhaps CME’s matching algorithms tilt in favor of the larger trader, with FIFO being the default for small size. The upshot is that I don’t know the answer. I’m sure that many of my readers are more knowledgeable on this score than I am; if so, please share.
In a study dating from March 2009 the CME analyzed immediately executable orders--that is, orders that can be at least partially executed at the time they reach the central limit order book. One finding puzzled me: “order quantities between six and 49 contracts are being executed with lower market impact than orders of five or fewer contracts.” Market impact means “the difference between the middle of the market at the time of the order’s arrival and the order’s execution price, or the average execution price in the event of fills at different prices.”
The fact that the small trader often doesn’t get the best price is not a function of speed of execution. Orders to buy or sell between one and five contracts were filled within 30 milliseconds after their arrival at CME Globex 86% of the time and within 50 milliseconds 91% of the time. Orders for six to ten contracts were filled within 30 milliseconds 85% of the time and within 50 milliseconds 93% of the time. As order size increased so did average fill time.
Why do the smallest traders not get the best price? Perhaps they’re simply addicted to market orders and by definition always give up the spread. Perhaps CME’s matching algorithms tilt in favor of the larger trader, with FIFO being the default for small size. The upshot is that I don’t know the answer. I’m sure that many of my readers are more knowledgeable on this score than I am; if so, please share.
Tuesday, May 25, 2010
Brown, Chasing the Same Signals
If you believe that books should be written by people who know how to write, you’ll have a tough time with Brian R. Brown’s Chasing the Same Signals: How Black-Box Trading Influences Stock Markets from Wall Street to Shanghai (Wiley, 2010). The book suffers from a lack of structure, it is repetitive, and it has numerous factual and typographical errors.
Nonetheless, it is a useful book for those who are trying to peer into quant black boxes and, even more, for those who are interested in the interrelationships among market structure, algorithmic order execution, and liquidity. Brown introduces the reader to the world of high frequency trading and to some principles that inform hedge fund strategies. He does this from the vantage point of an insider who worked for Morgan Stanley as director of pan-Asia systematic trading and for Trout Trading Management, researching and managing statistical arbitrage strategies.
Brown claims that the market data metrics most commonly monitored in quantitative strategies are volatility, spread, and volume. In searching for price anomalies quants look for deviations from normal metric readings. An increase in volatility in an individual stock, usually viewed as the result of shifting supply and demand and/or price uncertainty, is taken to be a signal of increased risk. But on the level of market structure, Brown writes, there is another cause of greater volatility—higher transaction costs, which discourage short-term speculation and hence suck liquidity out of the markets.
The bid-ask spread also provides important information to quantitative traders. Traders are accustomed to shifts in the spread during the course of the day depending on the level of trading activity, but “an unusual movement in the spread can denote the beginning of a price rally or a reversal.” (p. 111) Spreads can also dramatically widen out en masse during market crises as market participants worry about underlying risks and the cost of providing liquidity. A review of the tape during the flash crash speaks volumes on this score. Brown writes (well before this particular event): “Algorithms are designed to minimize market impact but they largely depend on forecasting liquidity. When liquidity is weak, algorithms may respond unpredictably to the adversity. Price impacts can be rapid and severe.” (p. 103)
Consider, for instance, the practice known as pinging the book. High-frequency traders submit orders to an ECN; if they are not filled within 60-80 milliseconds the orders are cancelled. There’s a sleazy side to this practice, but let’s not go down that path. The point is that high-frequency traders are testing the waters, searching for liquidity. If they don’t find it, they don’t provide it. They are not magnanimous.
Yet Brown claims that “the essence of a black-box firm is to be a liquidity provider. . . . Before the financial crisis, the black-box influence on the world’s equity markets was observed with historical lows in volatility, dispersion, and spreads. The frictional conditions for long-term investors had never been better.” (p. 176) For instance, statarb and market-neutral strategies dampened down market volatility and dispersion (and hence over time became less profitable). But we can’t conflate plain vanilla hedge-fund strategies with high frequency strategies. They have very different risk profiles. And they will impact markets in very different ways.
Brown’s book is not a model of tight reasoning. Its strength is that it offers up hypotheses from various vantage points that might improve our perception, perhaps even regulation, of the brave new world of the financial markets.
Nonetheless, it is a useful book for those who are trying to peer into quant black boxes and, even more, for those who are interested in the interrelationships among market structure, algorithmic order execution, and liquidity. Brown introduces the reader to the world of high frequency trading and to some principles that inform hedge fund strategies. He does this from the vantage point of an insider who worked for Morgan Stanley as director of pan-Asia systematic trading and for Trout Trading Management, researching and managing statistical arbitrage strategies.
Brown claims that the market data metrics most commonly monitored in quantitative strategies are volatility, spread, and volume. In searching for price anomalies quants look for deviations from normal metric readings. An increase in volatility in an individual stock, usually viewed as the result of shifting supply and demand and/or price uncertainty, is taken to be a signal of increased risk. But on the level of market structure, Brown writes, there is another cause of greater volatility—higher transaction costs, which discourage short-term speculation and hence suck liquidity out of the markets.
The bid-ask spread also provides important information to quantitative traders. Traders are accustomed to shifts in the spread during the course of the day depending on the level of trading activity, but “an unusual movement in the spread can denote the beginning of a price rally or a reversal.” (p. 111) Spreads can also dramatically widen out en masse during market crises as market participants worry about underlying risks and the cost of providing liquidity. A review of the tape during the flash crash speaks volumes on this score. Brown writes (well before this particular event): “Algorithms are designed to minimize market impact but they largely depend on forecasting liquidity. When liquidity is weak, algorithms may respond unpredictably to the adversity. Price impacts can be rapid and severe.” (p. 103)
Consider, for instance, the practice known as pinging the book. High-frequency traders submit orders to an ECN; if they are not filled within 60-80 milliseconds the orders are cancelled. There’s a sleazy side to this practice, but let’s not go down that path. The point is that high-frequency traders are testing the waters, searching for liquidity. If they don’t find it, they don’t provide it. They are not magnanimous.
Yet Brown claims that “the essence of a black-box firm is to be a liquidity provider. . . . Before the financial crisis, the black-box influence on the world’s equity markets was observed with historical lows in volatility, dispersion, and spreads. The frictional conditions for long-term investors had never been better.” (p. 176) For instance, statarb and market-neutral strategies dampened down market volatility and dispersion (and hence over time became less profitable). But we can’t conflate plain vanilla hedge-fund strategies with high frequency strategies. They have very different risk profiles. And they will impact markets in very different ways.
Brown’s book is not a model of tight reasoning. Its strength is that it offers up hypotheses from various vantage points that might improve our perception, perhaps even regulation, of the brave new world of the financial markets.
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