New strategies:
#193 – Trendfollowing Effect within REITs
Period of rebalancing: Monthly
Markets traded: REITs
Instruments used for trading: stocks, ETFs
Complexity: Simple strategy
Bactest period: 1980 – 2010
Indicative performance: 14.83%
Estimated volatility: 10.67%
Source paper:
Glabadanidis: The Market Timing Power of Moving Averages: Evidence from US REIT Indexes
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2055017
Abstract:
I present evidence that a moving average trading strategy dominates buying and holding the underlying asset in a mean-variance sense using monthly returns of value-weighted and equal-weighted US REIT Indexes over the period January 1980 until December 2010. The abnormal returns are largely insensitive to the four Carhart (1997) factors and produce economically and statistically significant alphas of between 10% and 15% per year after transaction costs. This performance is robust to different lags of the moving average and in sub-periods while investor sentiment, liquidity risks, business cycles, up and down markets, and the default spread cannot fully account for its performance. The substantial market timing ability of the moving average strategy appears to be the main driver of the abnormal returns.
#194 – Advertising Effect within Stocks
Period of rebalancing: 6 Months
Markets traded: equities
Instruments used for trading: stocks
Complexity: Complex strategy
Bactest period: 1996 – 2005
Indicative performance: 9.40%
Estimated volatility: 3.20%
Source paper:
Chemmanur, Yan: Advertising, Attention, and Stock Returns
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1340605
Abstract:
This paper studies the effect of advertising on stock returns both in the short run and in the long run. We find that a greater amount of advertising is associated with a larger stock return in the advertising year but a smaller stock return in the year subsequent to the advertising year, even after we control for other price predictors, such as size, book-to-market, and momentum. We conjecture that this advertising effect on stock returns is due to the effect of advertising on investor attention. Advertising could help a firm attract investors' attention. Stock price increases in the adverting year due to the attracted attention, but decreases in the subsequent year as the attracted attention wears out over time in the long run. We test this "investor attention hypothesis" using trading volume and the number of financial analysts covering to proxy for investors' attention on the firm's stock. We document five consistent findings. First, advertising increases a firm's visibility among investors in the advertising year. Second, an increased level of investor attention is associated with a larger contemporary stock return and a smaller future stock return. Third, the effect of advertising on stock returns is stronger in firms with more visibility in the advertising year. In particular, when a high advertising firm attracts more investor attention in the stock market, the stock return of the high advertising firm increases to a larger degree in the contemporary adverting year and decreases to a larger degree in the subsequent years. However, the stock return of such a high advertising firm decreases to a smaller degree if the attention attracted in the advertising year persists subsequent to the advertising year. Fourth, the effect of advertising on future stock returns is stronger if investors face a larger cost of arbitrage. Finally, we also find that the advertising effect is stronger for small firms, value firms, and firms with poor ex-ante stock performance or poor ex-ante operating performance.
New research papers related to existing strategies:
#33 – Post-Earnings Announcement Effect
Barbosa: Differential Interpretation of Information and the Post-Announcement Drift: A Story of Consensus Learning
http://www.efmaefm.org/0EFMAMEETINGS/EFMA%20ANNUAL%20MEETINGS/2012-Barcelona/papers/EFMA2012_0068_fullpaper.pdf
Abstract:
I show how a post-announcement drift can be generated in a model with fully rational investors who interpret public information differently. Differential interpretation of information transforms public raw information into private interpreted information. If investors recognize their limited ability to interpret information, they will look for other investors’ opinions in prices. Noise trading prevents investors from learning the market consensus interpretation of the announcement from the observation of a single price. But if noise trading follows a mean-reverting process, investors can gradually learn the market consensus from the observation of a series of prices. As investors become more confident about their interpretation of the announcement, they put more weight on it, and the announcement is gradually incorporated into prices, which generates a post-announcement drift. The model accounts for all salient empirical facts related to the post-announcement drift and delivers two new testable implications. If, in addition, investors make mistakes in extracting information from prices, the model also generates momentum.
#36 – Net Payout Yield Effect
Gray, Vogel: Dissecting Shareholder Yield
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2051101
Abstract:
We study a variety of previously examined payout yields over time: dividends, share repurchases cash flow, and equity issuance. We confirm on a newer dataset what other research has found; dividend yield no longer works, but more complete measures of shareholder yield hold promise. We contribute to the literature by examining an additional variable to payout yield, net debt pay down. The addition of net debt pay down helps performance, but is not a panacea. We find that regardless of the yield metric chosen, the predictive power of separating stocks into high and low yield portfolios has lost considerable power in the last twenty years. We also explore the concept of separating yield metrics by payout percentage as a way to salvage the predictability of yield metrics. We find no evidence that using payout percentage within a yield category can systematically improve portfolio performance.
