New strategies:
#125 – 12 Month Cycle in Cross-Section of Stocks Returns
Period of rebalancing: Monthly
Markets traded: equities
Instruments used for trading: stocks
Complexity: Complex strategy
Bactest period: 1965-2002
Indicative performance: 8.60%
Estimated volatility: 12.20%
Source paper:
Heston, Sadka: Seasonality in the Cross-Section of Expected Stock Returns
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=687022
Abstract:
This paper introduces seasonality into a model of expected stock returns. We confirm previous findings that there is no evidence for cross-sectional variation in expected stock returns when we restrict the means to be constant throughout the year. Yet, we show there is substantial variation when considering each month of the year separately. Applying a seasonal structure we estimate an annualized standard deviation of 13.8%. There is strong evidence stocks have distinct expected returns in January, February, … December. The estimated seasonal variation in expected returns is positive in every calendar month and especially high during October, December, and January. This structure is independent of industry, size, and earnings announcements. These results support the inclusion of seasonal structure into asset-pricing models.
#126 – Commodity Risk Factor in Equities
Period of rebalancing: Monthly
Markets traded: equities
Instruments used for trading: stocks
Complexity: Complex strategy
Bactest period: 2004-2010
Indicative performance: 12.49%
Estimated volatility: 16.50%
Source paper:
Boons, De Roon, Szymanovska: The Stock Market Price of Commodity Risk
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1785728
Abstract:
Commodity prices are a risk factor that directly influences inflation for consumers as well as input and output prices for firms. We sort stocks according to their beta with respect to a broad index of commodity futures and find that commodity risk is priced. Our cross-sectional regressions imply that a unit exposure to commodity risk is rewarded with a premium of around 5% pre-2004 and -8.5% post-2003. We argue that commodity risk is likely to proxy for inflation risk and attribute the reversal to the surge in commodity index investment by institutions in the early 2000s. In a simple model in which investors are exposed to exogenous inflation risk, a switch from hedging in the stock market to hedging directly in the commodity market easily leads to the observed reversal in the risk premium. Both time-series and cross-sectional tests imply that the commodity factor is a separate additional risk factor, not replacing the traditional Fama-French-Carhart factors.
New research papers related to existing strategies:
#6 – Volatility Effect in Stocks – Long-Short Version
#7 – Volatility Effect in Stocks – Long-Only Version
New related paper:
Sullivan, Li: Why Low-Volatility Stocks Outperform: Market Evidence on Systematic Risk Versus Mispricing
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1739227
Abstract:
We explore whether the well publicized anomalous returns associated low-volatility stocks can be attributed to market mispricing or to compensation for higher systematic risk. Our results, conducted over a 46 year study period (1962-2008), indicate that the high returns related to low-volatility portfolios cannot be viewed as compensation for systematic factor risk. Instead, the excess returns are more likely to be driven by market mispricing as perhaps associated with an imperfection such as some investor irrationality connected with volatility.
#120 – Speculators' Effect in FX
#121 – Hedgers' Effect in FX
New related paper:
Tornell, Yuan: Speculation and Hedging in the Currency Futures Markets: Are They Informative to the Spot Exchange Rates
http://www.umbc.edu/economics/wpapers/wp_09_116.pdf
Abstract:
This paper presents an empirical analysis investigating the relationship between the futures trading activities of speculators and hedgers and the potential movements of major spot exchange rates. A set of trader position measures are employed as regression predictors, including the level and change of net positions, an investor sentiment index, extremely bullish/bearish entiments, and the peak/trough indicators. We find that the peaks and troughs of net positions are generally useful predictors to the evolution of spot exchange rates but other trader position measures are less correlated with future market movements. In addition, speculative position measures usually forecast pricecontinuations in spot rates while hedging position measures forecast pricereversals in these markets.
