#6 – Volatility Effect in Stocks – Long-Short Version
#7 – Volatility Effect in Stocks – Long-Only Version
Huang, Lou, Polk: The Booms and Busts of Beta Arbitrage
http://personal.lse.ac.uk/polk/research/BoomsAndBustsOfBetaArbitrage20140203.pdf
Abstract:
Historically, low-beta stocks deliver high average returns and low risk relative to high-beta stocks, offering a potentially profitable investment opportunity for professional money managers to “arbitrage” away. We argue that beta-arbitrage activity instead generates booms and busts in the strategy’s abnormal trading profits. In times of relatively little activity, the beta-arbitrage strategy exhibits delayed correction, taking up to three years for abnormal returns to be realized. In stark contrast, in times of relatively-high activity, short-run abnormal re turns are much larger and then revert in the long run. Importantly, we document a novel positive-feedback channel operating through firm-level leverage that facilitates these boom and bust cycles. Namely, when arbitrage activity is relatively high and beta-arbitrage stocks are relatively more levered, the cross-sectional spread in betas widens, resulting in stocks remaining in beta-arbitrage positions significantly longer. Our findings are exclusively in stocks with relatively low limits to arbitrage (large, liquid stocks with low idiosyncratic risk), consistent with excessive arbitrage activity destabilizing prices.
#12 – Pairs Trading with Stocks
Clegg: On the Persistence of Cointegration in Pairs Trading
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2491201
Abstract:
An exploratory study is conducted to assess the persistence of cointegration among U.S. equities. In other words, if a pair of equities is found to be cointegrated in one period, is it likely that it will be found to be cointegrated in the subsequent period? An examination is performed of pairs formed from constituents of the S&P 500 during each of the calendar years 2002-2012, comprising over 860,000 pairs in total. The evidence does not support the hypothesis that cointegration is a persistent property.
#41 – Turn of the Month in Equity Indexes
Giovanis: The Turn-of-The-Month-Effect: Evidence from Periodic Generalized Autoregressive Conditional Heteroskedasticity (PGARCH) Model
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2479295
Abstract:
The current study examines the turn of the month effect on stock returns in 20 countries. This will allow us to explore whether the seasonal patterns usually found in global data; America, Australia, Europe and Asia. Ordinary Least Squares (OLS) is problematic as it leads to unreliable estimations; because of the autocorrelation and Autoregressive Conditional Heteroskedasticity (ARCH) effect existence. For this reason Generalized GARCH models are estimated. Two approaches are followed. The first is the symmetric Generalized ARCH (1,1) model. However, previous studies found that volatility tends to increase more when the stock market index decreases than when the stock market index increases by the same amount. In addition there is higher seasonality in volatility rather on average returns. For this reason the Periodic-GARCH (1,1) is estimated. The findings support the persistence of the specific calendar effect in 19 out of 20 countries examined.
#54 – Momentum and State of Market (Sentiment) Filters
Daniel, Moskowitz: Momentum Crashes
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2486272
Despite their strong positive average returns across numerous asset classes, momentum strategies can experience infrequent and persistent strings of negative returns. These momentum crashes are partly forecastable. They occur in "panic'' states — following market declines and when market volatility is high — and are contemporaneous with market rebounds. We show that the low ex-ante expected returns in panic states are consistent with a conditionally high premium attached to the option-like payoffs of past losers. An implementable dynamic momentum strategy based on forecasts of momentum's mean and variance approximately doubles the alpha and Sharpe Ratio of a static momentum strategy, and is not explained by other factors. These results are robust across multiple time periods, international equity markets, and other asset classes.
#69 – Post-Earnings Announcement Drift Combined with Strong Momentum
Ma, Whidbee, Zhang: Recency Bias and Post-Earnings Announcement Drift
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2469308
Abstract:
In this paper we examine the role of the timing of 52-week high, or recency, in the post earnings announcement drift (PEAD) puzzle. We argue that, because investors are less likely to bid up (down) a stock price if a stock’s 52-week high occurred in the recent (distant) past, these stocks are underpriced (overpriced) and earn higher (lower) future returns. We report these findings. First, PEAD profits are mainly driven by recency bias. An enhanced strategy based on both PEAD and recency accounts for 74% of total PEAD profits. Second, the recency bias accounts for the entire PEAD profits of large stocks and of the recent 24 years. The effect of recency bias on PEAD exists even after controlling for price proximity to 52-week high. Our evidence suggests that recency bias plays an important role in PEAD.
#198 – Exploiting Term Structure of VIX Futures
Cheng: The Expected Return of Fear
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2495414
Abstract:
Long investors in futures contracts on the CBOE Volatility Index (VIX), otherwise known as the “investor fear gauge,” lose 4% per month on average, paying this premium to hedge against periods of high market volatility. Even though there is substantial risk that the VIX rises further during these turbulent market periods, however, subsequent average futures returns are close to zero or even positive, rather than more negative. This phenomenon is predictable using real-time data on the slope of the VIX futures curve. Movements in price risk exposures and positions suggest that low demand for insurance from long investors drives this effect. A short futures investor who earns substantial returns during calm periods but otherwise pays out during VIX spikes can significantly reduce risk by moving into cash when the futures curve slopes downward with little detectable cost to expected returns, earning a 3.4% four-factor alpha per month with a Sharpe ratio of 0.36.
