Wednesday, August 31, 2016
Abner’s handbook is directed primarily at institutional investors. The retail investor who owns, let’s say, a few hundred shares of SPY, TLT, and GLD does not need the kind of detailed information provided here.
Abner divides his book into three parts. The first part introduces the structures of ETFs, the methodologies underlying these products, and the ways of bringing them to the marketplace. The second part addresses trading, with special emphasis on volume and liquidity. In the third part Abner discusses the mechanics of calculating the fair value of the products.
Rather than going into the weeds of trade execution, however important it may be for institutions placing large trades (in fact, Abner writes that “the information in [the chapter on execution] alone should make owning this book mandatory for every trader and execution flow staff member who handles orders in exchange-listed funds”), I’ll focus on a topic that bedevils both retail and institutional investors: leveraged products.
Leveraged ETFs are structured to satisfy traders with short-term positions. At the close of every trading day leveraged ETFs have to be reset to 100% exposure, “which means the leveraged funds are truing up their exposure and trading in the close daily.” This also means that “the leverage performance applies only to day-over-day price movements, not to the basis at which you entered into the trade. … [O]ver time, the compounding of this reset can potentially cause the performance of the fund versus its underlying benchmark to diverge.” Consider, for instance, the extreme case in which the index rises 10% a day for ten days. It will have a ten-day cumulative change of 159%. A 2X ETF, however, will have a cumulative change of 519%. Because of the increasing price, the daily gains “are driving the value higher at a faster pace.” If the index declines 10% a day for ten days, its cumulative change will be -65%; the 2X ETF, -89%. It loses progressively less in notional points every day. In a rangebound, volatile market, up 10% then down 10% for ten days, the cumulative change for the index will be -4.90%; for the ETF, -18.46%. The returns of leveraged ETFs are, as can be seen, highly path dependent.
Abner’s book is both comprehensive and comprehensible, and he writes from experience. Earlier in his career he built and managed ETF sales and trading businesses at BNP Paribas and Bear Stearns. He currently leads the European business for WisdomTree Asset Management, an ETF issuer. No professional should enter the ETF world without taking advantage of his experience, analysis, and sound advice.
Sunday, August 28, 2016
Here I’ve decided to focus on a single short chapter: liquidity investing, written by Roger Ibbotson and Daniel Kim, because some of its findings are surprising. First, risk, as measured by standard deviation, increases with liquidity. The authors analyzed the annualized returns (%) between 1972 and 2015 of liquidity quartiles of stocks traded on the NYSE, NYSE MKT, or NASDAQ. The geometric means of the returns of the quartiles, from least liquid to most liquid, were 14.93, 14.04, 12.20, and 7.32. Their arithmetic means were 16.74, 16.06, 14.56, and 10.94. And their standard deviations were 20.01, 21.29, 22.72, and 27.79. One dollar invested in the least-liquid quartile of stocks at the end of 1971 (an equally weighted portfolio with all dividends reinvested) grew to $456.72 by the end of 2015. One dollar invested in the most-liquid quartile grew to only $22.43 over this period.
Liquidity, the authors found, is a much better predictor of returns than size. Although small stocks tend to outperform large stocks in general, this pattern is reversed for the most-liquid stocks. The best performing category is made up of small, relatively less liquid stocks; the worst performing are the small, highly liquid stocks.
Analyzing the performance of value and growth stocks in terms of liquidity, the authors show that high-value, low-liquidity stocks perform the best and high-growth, high-liquidity stocks the worst. The geometric mean of the compound annual returns of the former was 18.85%; of the latter, 2.46%.
In brief, liquidity is a viable investing style and can be mixed and matched with other styles to add to performance.
The SBBI Yearbook has been published for over 30 years. Even in an era of digital data, it remains a wonderful publication. I wish it another 30 years of prosperity.
Wednesday, August 24, 2016
At the heart of Gonzalez’s framework is the core-periphery paradigm. Although currencies exist in a continuum, the paradigm divides currencies into the world’s reserve currency (currently the U.S. dollar), hard currencies (ones that appreciate during episodes of risk aversion, such as the Japanese yen, the Singaporean dollar, and the Swiss franc), and soft currencies (emerging market currencies or commodity-exporting currencies). The reserve currency economy has many advantages over other economies. Most notably, “worldwide monetary conditions are typically ‘optimal’ for the reserve currency economy and only for the reserve currency economy.” It can “generate wealth out of thin air,” it has “longer uninterrupted business cycles” (witness 1991-2001), and it can “have a currency account deficit apparently indefinitely.” (p. 22)
Gonzalez presents two blueprints of the dynamics of global macro, the episode from 2003 to 2008 and that from 1995 to 2001. Here things necessarily become more complicated. Nonetheless, Gonzalez suggests that “there are some difficult-to-manipulate relationships” in these blueprints, which is “why they just might increase the odds of profiting from global macro.” (p. 32)
The bulk of the book is a history lesson, from the commodity boom of the 1970s through the monetary experiments of the 2010s. The author analyzes global macro events in each decade and follows that analysis with graphs covering such areas as currencies, U.S. economic policy, U.S. equities, commodities, global equities, U.S. real estate, and U.S. economics.
In the shorter second part of the book Gonzalez offers a topical analysis: the war effect, crashes and crises, commodities, fallacies and the chairman cycle, macro and power, dollar stability, and the gray swan.
The “mother of all gray swans,” according to the author, is climate change. He considers four scenarios—rising sea levels, lack of water in a metropolis, pandemic, and drought—and offers suggestions about where to invest and what to avoid. He recommends that the sophisticated investor monitor water levels in major cities around the world just as she monitors the dollar index. “Other variables to check upon are agricultural inventories, livestock levels, and more-accurate-than-official climate projections. Just as observing U.S. dollar trends has been profitable in the past (and might still be in the future), monitoring the above mentioned variables might produce outsized returns in the future. It might become a necessary defensive strategy.” (p. 282)
Sunday, August 21, 2016
In the popular history of neuroscience two patient names stand out. First, Phineas Gage (1823-1860), who, as one writer described him, “had a metal rod blown through his head and lived to get cranky about it.” Gage’s personality changed radically, and not for the better, after the accident. Second, Henry Gustav Molaison (1926-2008), known simply as Patient H.M., who, after a lobotomy to control his epilepsy, could no longer commit new events to his explicit memory. He was a hollowed out human being. But he became the subject of intense scientific study. Psychologists researching the formation of memories had in Patient H.M. a classic case study in how “the broken illuminate the unbroken.”
Luke Dittrich is the grandson of Dr. William Beecher Scoville, the surgeon who performed the lobotomy on H.M. and countless others, including, as it turns out late in the book, his own wife. Scoville proselytized for psychosurgery and especially for lobotomies. In performing lobotomies, he found “a way to unite his passion for tinkering and his interest in experimental surgery.”
Scoville, known to medical residents as “Wild Bill,” pushed the boundaries of medicine, to the point that the line between his work as a doctor and his work as a scientist eventually became “impossibly blurred.” The pretext of healing mentally ill patients gave him cover to carry out surgical experiments. ‘Pretext’ may be too strong a word, but there was scant evidence that lobotomies were beneficial to the thousands of patients who underwent them. Scoville’s surgery was not quite the stuff of the Nuremberg trials, but it was ethically sketchy nonetheless.
Patient H.M.is one of those books you can’t put down, and also one you can’t forget.
Sunday, August 14, 2016
The first task of the authors is to make the case for active management in the face of the industry’s pretty grim performance numbers. Even before fees, a minority of U.S. large-cap core equity managers managed to outperform the S&P 500 over one year (42%), three years (48%), and five years (46%). Only over a ten-year time horizon did a majority outperform (69%).
The authors’ argument is that the real-life insights of behavioral economists have effectively defeated what “started off as an ironclad theoretical case for passive management.” (p. 85) Even so, the strongest conclusion this argument can reach is that successful active management is possible.
Several factors work against active managers. Periods of higher correlation and lower dispersion are challenging for managers, as are times when the stocks of lower-quality companies outperform those of higher-quality companies. Active funds also experience a drag from cash holdings. And, of course, they fall victim to the paradox of skill. As Mauboussin described this paradox, as participants in an endeavor become more skillful as a whole, luck becomes an increasingly important component of any one participant’s results.
Theoretically, active managers can outperform stock market averages because behavioral biases create market inefficiencies. Practically, “most managers have not been following an approach that is likely to work.” The authors contend that “capturing the impact of stock-specific inefficiencies requires a disciplined process that (1) understands the forces that create an inefficiency, (2) captures it by ‘casting a wide net’ across stocks that are likely to be affected, and (3) properly structures the portfolio so as to filter out the impact of any factors (e.g., size or industry effects) for which the manager currently has no forecast, and which might otherwise swamp the excess return generated by the inefficiency that the manager is trying to capture.” (p. 106)
The investment philosophy of the authors’ firm is that “cash flow is the origin of value in stocks, and that forecasts of cash flows should be the basis for security selection.” (p. 133)
The authors also address the role of technology in investing. Will computers eventually take over the world of investment management? The authors not unexpectedly take the position that “investing is too important for robots alone.” Instead, they are, in the words of one of their firm’s recent initiatives, “racing with the machine.”
Three appendices to the book present selected articles and white papers of Epoch Investment Partners, a review of principles of valuation for financial assets, and a case study about disclosure written by Jack Treynor in 1993.
Wednesday, August 10, 2016
Traders who have shied away from options because they seem overly complicated may be relieved to learn that understanding the Greeks is not essential in the world of binary options. Yes, market makers use them to price the binaries and Cofnas even introduces the reader to volatility smiles, but the trader’s major decisions are whether to buy or sell binary options, at what strike price, and for what duration. How much does he think the market will move in a given length of time and in what direction?
Of course, getting the direction, magnitude, and timing of a short-term trade (weekly, daily, and a selection of intraday expiries) right is a daunting task. Cofnas therefore devotes four chapters to tools the binary options trader can use to improve his skills: sentiment analysis, tracking fundamental forces that impact markets, technical analysis, and volatility tools.
He then describes in some detail seven major binary option trading strategies that can be used to respond to global market-related events: in-the-money, deep-in-the-money, at-the-money, out-of-the-money, deep-out-of-the-money, range trades, and breakout trades. He offers, among others, examples of gold and EUR/USD trades during the Greek debt crisis, a crude oil play at the time of revolts in Tunisia and Egypt, a GBP/USD trade just before the referendum on Scottish independence, and a USD/CHF trade the week of U.S. congressional elections. He draws these examples from trading alerts he sent out in Agora Financial’s Strategic Currency Trading newsletter. Cofnas also devotes a full chapter to using binary options to trade the non-farm payroll report.
The book concludes with chapters on risk management, metrics for improving trading performance, performance tools and training for improving trading, and a 51-question quiz.
Traders who want to get a feel for binary options can create a free paper trading account at Nadex. If they have experience trading other instruments they will most likely be struck by the incredibly wide bid/ask spreads here. For instance, whereas the front-month crude oil futures normally have a penny-wide spread and options on CL have spreads of about two to seven cents, the day I checked crude oil binary spreads on Nadex, on a weekly contract with two days left, they ranged from $5.25 to $7.00, with bids from $0.50 to $93.50 and offers from $5.75 to $98.75. And in contrast to Cantor, NYSE, and CBOE, Nadex takes the other side of the trade. The trade-off here, as Cofnas points out, is the potential lack of liquidity on the “true exchanges.”
Cofnas’s book is useful to anyone considering adding binary options to his trading portfolio. As, of course, is trying out some strategies in a paper account to see whether they are solid enough to overcome the wide spreads and, in the case of Nadex, to beat the house.
Sunday, August 7, 2016
Gottesman is a professor of finance at the Lubin School of Business at Pace University in Manhattan. I don’t know how sophisticated or focused his MBA students are, but he expects from his readers only a willingness to learn how derivatives function and an ability to work through formulas that he explains step by step. After every couple of pages or so he inserts a knowledge check, easy to answer if you’ve been paying attention, a wake-up call if you haven’t.
The book is divided into five parts: introduction to forwards, futures, and options; pricing and valuation (including the Black-Scholes and binomial option pricing models); the Greeks; trading strategies; and swaps.
Gottesman often takes a different approach to derivatives from most textbook writers. For instance, he explains theta by saying at the outset that “there are two ways that a decrease in the time to expiration can impact the value of a position:
The present value effect: As time to expiration decreases, the present value of the forward price/strike increases.
The optionality value effect: As time to expiration decreases, optionality value erodes.”
Traders who want instant gratification in the form of specific setup recommendations will find Gottesman's book disappointing. But anyone who wants to understand what options are all about, especially in the context of other derivatives, and how the pieces fit together mathematically should read this book. It’s also a book that deserves a permanent place on a derivative trader's reference shelf.