Downside Risk, Cross-Sectional Equity Returns and the Momentum Effect

Link to PDF File: Downside Risk, Cross-Sectional Equity Returns and the Momentum Effect
Joe Chen, University of Southern California
Andrew Ang, Columbia University
Yuhang Xing, Columbia University

Stocks with greater downside risk, which is measured by higher correlations conditional on downside moves of the market, have higher returns. After controlling for the market beta, the size effect and the book-to-market effect, the average rate of return on stocks with the greatest downside risk exceeds the average rate of return on stocks with the least downside risk by 6.55% per annum. Downside risk is important for explaining the cross-section of expected returns. In particular, the authors find that some of the profitability of investing in momentum strategies can be explained as compensation for bearing high exposure to downside risk.

Getting Squeezed: Market Manipulation in US Equity Markets

Owen Lamont, University of Chicago

The author will study intentional “short squeezes” in US equity markets, defined as situations in which short-sellers are forced to cover their short position. He will focus on legal market manipulation, in which firm management attempts to force short sellers to close their position. Management can attack short sellers by publicly coordinating an attempt to deny short sellers the ability to borrow shares, by taking legal action against short sellers, or by publicly denouncing them. Lamont will study the effect of short squeezes on stock prices, whether this effect is temporary or permanent, and the long-term returns to holding squeezed stocks.

Informed Trading in Stock and Option Markets

Stewart Mayhew, University of Georgia
Sugato Chakravarty,Purdue University
Huseyin Gulen. Virginia Tech

The authors propose to investigate how much price discovery occurs in the option market, as compared to the underlying stock market. Using six years of transactions data on sixty stocks from ISSM and the Berkeley Options Database, they will employ the techniques of Hasbrouck (1995) and Harris, McInish and Wood (2001) to estimate the proportion of price discovery occurring in each market for each stock, each month. Then, they will test whether significant price discovery occurs in the option market, and whether factors such as trading volume or volatility can help explain cross-sectional and time-series variation in these measures.

Evidence on the Speed of Convergence to Market Efficiency

Tarun Chordia, Emory University
Richard Roll, UCLA
Avanidhar Subrahmanyam, UCLA

Order imbalances for large and mid-cap stocks listed on the New York Exchange are highly persistent from day to day. In contrast, daily returns on the same stocks have no serial dependence. These two empirical facts can be reconciled if arbitrageurs react to order imbalances within the trading day by engaging in countervailing trades sufficient to remove serial dependence over the daily horizon. How long does this actually take? The authors propose to study the pattern of intra-day serial dependence, over intervals ranging from five minutes to one hour, to uncover traces of arbitrage.

Style Drift

Russ Wermers, University of Maryland

Prior research has used regression techniques to extract style information from the net returns data of professionally managed portfolios. While easy to apply, these methods cannot capture the dynamic nature of style loadings through time. This study proposes new portfolio holdings-based measures that precisely track the style characteristics of a fund through time. Specifically, the author will decompose style drift into drift in each style dimension (e.g., size, book-to-market, momentum, or liquidity), as well as decomposing drift into “active” and “passive” components. Finally, he will measure the impact of both passive and active drift on the performance of funds.