Asset allocation paper makes SSRN top ten downloads

Thanks for all the downloads, emails and comments!

Your paper, “EXPLOITING FACTOR AUTOCORRELATION TO IMPROVE RISK ADJUSTED RETURNS”, was recently listed on SSRN’s Top Ten download list for: Capital Markets: Asset Pricing & Valuation eJournal, Capital Markets: Asset Pricing & Valuation eJournals, ERN: Asset Pricing Models (Topic), Econometric Modeling: Capital Markets – Asset Pricing eJournal, Econometric Modeling: Financial Markets – Capital Markets eJournals and Mutual Funds, Hedge Funds, & Investment Industry eJournal.

As of 15 July 2014, your paper has been downloaded 165 times. You may view the abstract and download statistics at: http://ssrn.com/abstract=2456543.

Top Ten Lists are updated on a daily basis. Click the following link(s) to view the Top Ten list for:

Capital Markets: Asset Pricing & Valuation eJournal Top Ten, Capital Markets: Asset Pricing & Valuation eJournals Top Ten, ERN: Asset Pricing Models (Topic) Top Ten, Econometric Modeling: Capital Markets – Asset Pricing eJournal Top Ten, Econometric Modeling: Financial Markets – Capital Markets eJournals Top Ten and Mutual Funds, Hedge Funds, & Investment Industry eJournal Top Ten.

Asset allocation whitepaper released.

My paper on using Fama-French factors for efficient asset allocation is up on SSRN:

http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2456543

Downloads, comments and questions gratefully received!

Abstract:

The Fama-French three factor model is ubiquitous in modern finance. Returns are modeled as a linear combination of a market factor, a size factor and a book-to-market equity ratio (or “value”) factor. The success of this approach, since its introduction in 1992, has resulted in widespread adoption and a large body of related academic literature.The risk factors exhibit serial correlation at a monthly timeframe. This property is strongest in the value factor, perhaps due to its association with global funding liquidity risk.

Using thirty years of Fama-French portfolio data, I show that autocorrelation of the value factor may be exploited to efficiently allocate capital into segments of the US stock market. The strategy outperforms the underlying portfolios on an absolute and risk adjusted basis. Annual returns are 5% greater than the components and Sharpe Ratio is increased by 86%.

The results are robust to different time periods and varying composition of underlying portfolios. Finally, I show that implementation costs are much smaller than the excess return and that the strategy is accessible to the individual investor.