Big Ideas

In their March 2011 paper entitled “The Shrinking Space for Anomalies”, George Jiang and Andrew Zhang investigate the robustness of ten well-known anomalies by iteratively “shrinking the stock space” in two ways to determine whether and how the anomalies really work. The ten anomaly variables are: size, book-to-market ratio, momentum, two liquidity measures, idiosyncratic volatility, accrual, capital expenditure, sales growth and net share issuance. The first way of “shrinking the stock space” involves: (1) ranking the universe of stocks by each of the ten anomaly variables into deciles; (2) iteratively trimming deciles from side of a variable distribution that a hedge portfolio would sell and the side that a hedge portfolio would buy; and, (3) retesting the strength of the anomaly associated with the variable after each iterative trimming. The second way of “shrinking the stock space” involves: (1) trimming from the sample stocks with the smallest market capitalizations and the most extreme book-to-market ratios until size, book-to-market and momentum no longer have significant four-factor alphas for value-weighting and equal equal-weighting (thereby “perfecting” the sample for the four-factor model); and, (2) retesting the strength of the anomalies associated with the other seven variables using the perfected sample. This approach obviates weaknesses in alpha measurement via the commonly applied but imperfect three-factor (market, size, book-to-market) and four-factor (plus momentum) risk models. Using firm characteristics and trading data for all non-financial NYSE, AMEX, and NASDAQ common stocks over the period July 1962 through December 2007, they find that: Keep Reading

What is a financial market anomaly? How can investors determine whether an apparent anomaly is real (economically material)? In his March 2011 book chapter entitled “Perspectives on Capital Market Anomalies”, Mozaffar Khan provides a framework for interpreting academic research on anomalies and evaluating the exploitability of specific anomalies. His context is market efficiency: “Respect for the efficient markets theory, and an acknowledgment that it sometimes fails (i.e., that mispriced stocks can be identified), can coexist.” Key points are: Keep Reading

Can Treasury Inflation-Protected Securities (TIPS), with principal indexed to the U.S. non-seasonally adjusted Consumer Price Index for all urban consumers (CPI), play a valuable role in asset class diversification? In the January 2011 draft of their paper entitled “Optimal Portfolio Choice in Real Terms: Measuring the Benefits of TIPS”, Alvaro Cartea, Jonatan Saul and Juan Toro apply mean-variance optimization to measure the empirical diversification benefits of TIPS for long-term and short-term investors with portfolios including various combinations of equities, nominal Treasuries, commodities and real estate. Using nominal monthly returns for all TIPS issued before August 2009, grouped by maturity, for the period March 1997 through March 2010 (157 monthly observations) and contemporaneous returns for nominal U.S. Treasury instruments, U.S. stocks, commodities and U.S. home prices, they find that: Keep Reading

In his 2010 book Wave Theory for Alternative Investments: Riding the Wave with Hedge Funds, Commodities, and Venture Capital, author Stephen Todd Walker asserts that “dynamic asset allocation (as opposed to static allocation) is imperative… In my view, now is the time that one should be adding alternatives to a well-diversified portfolio. It is time to get out the surfboard. I believe alternatives move in waves, and this next wave will be worth riding. …Investors should consider all asset classes, especially those they do not fully understand, because that is where an investor will likely find the best opportunity going forward. …No one possesses a crystal ball, but it is not impossible to identify a certain trend or wave forming with alternatives.” The book first introduces the author’s Wave Theory of asset class performance and then examines some alternative asset classes. Some notable points from the book regarding dynamic asset class allocation are: Keep Reading

Is there a window of exploitation before prices of individual stocks incorporate relevant information shocks? If so, what is its duration? In their January 2011 paper entitled “Speed of Convergence to Market Efficiency: The Role of ECNs”, Dennis Chung and Karel Hrazdil investigate the duration of stock price inefficiency based on the time interval over which order imbalances significantly predict short-term returns. They focus on the effect of electronic networks on this duration. Using high-frequency stock trade and quote data, institutional ownership levels and market capitalizations for 2,041 firms with shares trading contemporaneously on NYSE and an electronic network (Arca) during the first six months of 2008, they find that: Keep Reading

In his 2011 book The Power of Passive Investing: More Wealth with Less Work, author Richard Ferri presents “the detailed studies and undeniable evidence favoring a passive investing approach. …This information clearly shows that trying to beat the market has never been a reliable investment strategy in the past, and there’s no reason to believe it will beat a passive approach in the future. …Attempting to earn above market returns by picking actively managed mutual funds is an inefficient use of time and money. Knowing this fact, and acknowledging it allows you the freedom to go in a different direction–to change religion in a sense. …This book makes the case for passive investing. You’ll have to read other books for details on asset allocation recommendations and fund selection methods.” The book includes 140 citations of formal studies and expert commentaries. Some notable points from the book are: Keep Reading

A reader interested in the gap between time-weighted equity returns and actual dollar-weighted returns experienced by investors flagged critiques of prior studies described in:

“Returns for Investors (Rather Than Markets)”: “…the actual aggregate (timing) experience of equity investors is inferior to passive buy-and-hold stock market returns. An active approach of buying after pronounced capital outflows from the market and selling after pronounced capital inflows to the market is likely to be successful.”

“Actual Return Experience of Hedge Fund Investors”: …actual hedge fund investor return/risk experience, due to the timing of entries and exits, is much worse than that indicated by the continuously measured returns and volatilities of the funds themselves.”

The critiques of these findings are a January 2008 paper entitled “Dollar-Weighted Returns to Stock Investors: A New Look at the Evidence” by Aneel Keswani and David Stolin, and a November 2010 paper entitled “Historical Returns: Hindsight Bias in Dollar-Weighted Returns” by Simon Hayley. Using the same data considered in the first study above, along with some additional data, the authors of these critiques argue that: Keep Reading

Many asset class allocation, asset valuation/selection and asset return anomaly studies ignore or treat lightly the implications of liquidity constraints. What are those implications and how serious are they? In his December 2010 paper entitled “Comatose Markets: What If Liquidity is Not the Norm?”, Aswath Damodaran examines how introducing illiquidity into decision processes affects investors with different time horizons and investment strategies. He focuses on trading friction (brokerage fees, bid-ask spread and price impact) as an illiquidity measurement. Using results from prior research and recent data on liquidity variations within and across asset classes, he finds that: Keep Reading

Information technology has lowered barriers for creating/operating financial asset exchanges (venues for matching supply and demand). Proliferation of low-cost venues elevates competition for investor dollars and tends to depress transaction fees. Automated, broadened supply/demand matching tends to depress bid-ask spreads. This evolving market ecology attracts high-frequency traders (HFT), enabled by new technology to exploit short-term market predictability. Do such traders succeed, and how do they impact the markets in which they trade? In his December 2010 preliminary paper entitled “High Frequency Trading and The New-Market Makers”, Albert Menkveld examines the behavior of one large high-frequency trader (HFT) and the effects of associated trading on the exchanges in which this HFT participates. Using high-frequency (one-second) quote and trade data from two European exchanges during January 1, 2007 through June 17, 2008, he finds that: Keep Reading

Is the aggregate effect of technical trading visible and exploitable at the equity index level? In his March 2007 paper entitled “The Interaction between the Aggregate Behavior of Technical Trading Systems and Stock Price Dynamics”, Stephan Schulmeister investigates how S&P 500 Index futures prices relate to the aggregate trading signals of 2,580 widely used trend-following and contrarian technical trading rules (moving average, momentum and relative strength) implemented with 30-minute data. Using 30-minute data for S&P 500 Index futures over the period 1983-2000, he finds that: Keep Reading