New strategies:
#130 – Return on Assets Combined with Value Effect
Period of rebalancing: Yearly
Markets traded: equities
Instruments used for trading: stocks
Complexity: Moderately complex strategy
Bactest period: 1963-2009
Indicative performance: 8.00%
Estimated volatility: 10.00%
Source paper:
Novy-Marx: THE OTHER SIDE OF VALUE: GOOD GROWTH AND THE GROSS PROFITABILITY PREMIUM
http://www.nber.org/papers/w15940.pdf
Abstract:
Profitability, as measured by gross profits-to-assets, has roughly the same power as book-to-market predicting the cross-section of average returns. Profitable firms generate significantly higher average returns than unprofitable firms, despite having, on average, lower book-to-markets and higher market capitalizations. Controlling for profitability also dramatically increases the performance of value strategies, especially among the largest, most liquid stocks. These results are difficult to reconcile with popular explanations of the value premium, as profitable firms are less prone to distress, have longer cashflow durations, and have lower levels of operating leverage, than unprofitable firms. Controlling for gross profitability explains most earnings related anomalies, as well as a wide range of seemingly unrelated profitable trading strategies.
#131 – Paired Switching
Period of rebalancing: Quarterly
Markets traded: equities, bonds
Instruments used for trading: stocks, ETFs, funds
Complexity: Simple strategy
Bactest period: 1991-2011
Indicative performance: 11.30%
Estimated volatility: 9.30%
Source paper:
Maewal, Bock: Paired-Switching for Tactical Portfolio Allocation
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1917044
Abstract:
Paired-switching refers to investing in one of a pair of negatively correlated equities/ETFs/Funds and periodic switching of the position on the basis of either the relative performance of the two equities/ETFs/Funds over a period immediately prior to the switching or some other criterion. It is based upon the idea that if the returns of two equities are negatively correlated, the overlapping of the periods during which the equities individually yield returns greater than their mean values will be infrequent. Consequently, if the criterion for switching is even minimally accurate in its ability to identify the boundaries of such periods, there is a possibility of improving the performance of the portfolio consisting of the two equities over the portfolio wherein the two equities are statically weighted on the basis of traditional methods such as, for example, variance minimization. In this paper we present some results that indicate that some very simple criteria for paired-switching can lead to lower volatility without any significant penalty in terms of lower returns.
New research papers related to existing strategies:
#1 – Asset Class Trend Following
Colucci, Brandolini: A Risk Based Approach to Tactical Asset Allocation
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1965423
Abstract:
Faber’s 'A Quantitative Approach to Tactical Asset Allocation' (2009) proposes the use of a very simple trading rule to improve the risk-adjusted returns across various asset classes. The purpose of this paper is to present an alternative and simple quantitative risk based portfolio management that improves the risk-adjusted portfolio returns across various asset classes. This approach, based on the conclusions of Brandolini D. – Colucci S. 'Backtesting Value-at-Risk: A comparison between Filtered Bootstrap and Historical Simulation', has been tested since 1974 for calibration and since 2000 in a real backtest. The asset allocation framework is using a combination of indices, including the Standard&Poors 500, Topix, Dax, MSCI United Kingdom, MSCI France, Italy Comit Globale, MSCI Canada, MSCI Emerging Markets , RJ/CRB, Merril Lynch U.S. Treasuries, 7-10 Yrs , and all indices are expressed in US Dollar. Since 2000 the empirical results present equity-like returns with lower volatility and drawdown and only one negative year both in gross and net of costs returns.
#119 – Google Search Effect
New related paper:
Chen: Google Search Volume: Influence and Indication for the Dutch Stock Market
http://oaithesis.eur.nl/ir/repub/asset/9487/9487-Chen.pdf
Abstract:
This paper studies the relationship between stock speci c and market level internet search volume on stocks and the Dutch stock market, using the listed stocks in the AEX index. Internet search volume is obtained weekly from the Google Insights database for the period between January 2004 and April 2011. As introduced by earlier studies, internet searching activity is an adequate proxy for investor recognition and should therefore be relevant for modeling trading activity and stock activity. The results obtained show that Google search volume is significantly influential not only for the traded volume, but also the historical stock volatility. This significance is proven to be stable by means of a Quandt-Andrews breakpoint test.
