New strategies:
#133 – Timing the Small Cap Effect
Period of rebalancing: Monthly
Markets traded: equities
Instruments used for trading: stocks, ETFs, futures, CFDs
Complexity: Simple strategy
Bactest period: 1927-2010
Indicative performance: 9.60%
Estimated volatility: 14.62%
Source paper:
Zakamouline: Predicting the Small Stock Premium Over Different Horizons: What Do We Learn About its Source?
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1951931
Abstract:
In this paper we present the evidence that the small stock premium is predictable both in-sample and out-of-sample using a set of lagged macroeconomic variables. It is possible to forecast the size premium over horizons from one month to one year. We demonstrate that the predictability of the size premium allows a portfolio manager to generate an economically and statistically significant active alpha. The results obtained in this paper support the view that the small stock premium tends to appear in economic bad times. Yet the size premium seems to be not a risk premium, but a behavioral phenomenon. Our findings suggest that the small stock premium appears mainly as the result of a delayed and strong reaction of small stocks to good news after a period of prolonged bad times.
#134 – Equity Sector Timing with IPO Factor
Period of rebalancing: Monthly
Markets traded: equities
Instruments used for trading: ETFs, funds
Complexity: Complex strategy
Bactest period: 1979-2008
Indicative performance: 18.05%
Estimated volatility: not stated
Source paper:
Lapham: Using IPOs to Identify Sector Opportunities
http://www.mta.org/eweb/docs/pdfs/dow-award-2009.pdf
Abstract:
The number of initial public offerings (IPOs) is a well-known, longterm stock market indicator. With the popularity of sector investing and the increased use of exchange traded funds, it would be advantageous to employ a new IPO-based indicator to assess sector health, improving upon available technical market measures. This study will examine how the number of IPOs within the ten market sectors can be used to help identify overbought or oversold conditions in each respective sector.
New research paper related to existing strategies:
#99 – FX Carry Trade Combined with PPP (Value) Strategy
Dunis, Miao: Trading Foreign Exchange Portfolios with Volatility Filters: The Carry Model Revisited
http://liveweb.livjm.ac.uk/AFE/AFE_docs/artcdjm_0605.PDF
Abstract:
The rejection of the simple risk-neutral efficient market hypothesis in the foreign exchange (FX) market opens the possibility of the profitable use of a carry model taking full advantage of interest rate differentials to trade currencies. A first motivation for this paper is to study whether a simple passive carry model can outperform a typical currency fund manager replicated by dynamic technical Moving Average Convergence and Divergence (MACD) models as in Lequeux and Acar (1998). Secondly, we study whether the addition of volatility filters can further improve the carry model performance. We consider the period starting from the introduction of the Euro (EUR) on 04/01/1999 through 31/03/2005 (1620 datapoints). To assess the consistency of the carry model performance on a portfolio of the nine most heavily traded exchange rates, the whole review period is further split into two sub-periods. Our results show that in the three periods considered and after inclusion of transaction costs, the simple carry model performs much better than the benchmark MACD model in terms of annualised return, risk-adjusted return and maximum potential loss, while a combined carry/MACD model has the lowest trading volatility. Moreover, the addition of two volatility filters adds significant value to the performance of the three models studied.
