Journal of Investment Strategies

Ali Hirsa
Professor, Columbia University & Managing Partner, Sauma Capital LLC

Welcome to the fourth issue of the eleventh volume of The Journal of Investment Strategies, which contains three research papers.

In the first paper in the issue, titled “Pricing options using expected profit and loss measures”, J. H. Venter and P. J. de Jongh discuss the pricing of options using an approach based on expected profit (EP) and expected loss (EL) as measures of the reward and risk of trades, respectively. They show that the EL/EP ratio is an important indicator of the quality of trades. Under the assumption that the price movement of the underlying security follows a traditional geometric Brownian motion, the authors derive European call and put options expressions for these measures. The Black–Merton–Scholes notion of implied volatility is generalized to consensus implied volatility for options chains. Venter and de Jongh introduce and illustrate optimal portfolios for trading in option chains with real data. Their findings show that the ELEP approach yields much useful information to options traders.

In our second paper, “Dynamic signal selection strategies”, Dilip B. Madan, Yazid M. Sharaiha and P˚al Sundsøy discuss the selection of a small number of predictors from a much larger set of potential stock signals based on the high levels of dependency in stock returns. The authors employ eight different models of pairwise dependency, including the Gaussian, t , Clayton, Frank and Gumbel copulas. In addition, they map predictive factors and returns to gamma, beta and standard bilateral gamma marginals with dependency constructed by using the magnitude of fractional common components from the same distributions. Each dependency model is used to select predictors. The predictions are used both directly and as required returns to build a measure for the value of an invested dollar. Stocks are ranked by these two metrics daily. For the mean-reversion strategy, Madan et al take short positions in a quarter of the top-ranked stocks and long positions in a quarter of the bottom-ranked stocks. The positioning is reversed under momentum. Trading performance results are presented for a variety of dependencies and sectors over the period from June 2006 to January 2021. The selection procedures are observed to deliver a reasonable set of trading strategies.

In “Dynamic rebalancing of a risk parity investment portfolio”, the third and final paper in this issue, Yixi Ning, Sean Yang and Wangzhi Zheng examine a popular risk parity investment portfolio, the so-called All Weather portfolio, in the period from January 2005 to May 2020. Based on the risk-adjusted Sharpe ratio, the Calmar ratio and maximum drawdown, they find that the All Weather portfolio outperforms several other portfolios in the long term. They further examine the impact of various static and dynamic portfolio-rebalancing strategies (eg, periodic rebalancing, dynamic range rebalancing and moving-average-distance-based trend-following rebalancing) on the All Weather portfolio, and they find that the risk-adjusted performance of the portfolio can be improved by implementing the optimal range-rebalancing strategy. Further, Ning et al find that the moving-average-distance-based trend-following rebalancing strategy can improve the All Weather portfolio’s performance in some circumstances. It appears that the two dynamic rebalancing strategies can be used interchangeably.


On behalf of the editorial board, we hope you have continued to do well throughout another year of the Covid-19 pandemic.We would like to thank you, our readers, for your continued support and keen interest in the journal. In 2023 we look forward to sharing with you more papers on a wide variety of topics on modern investment strategies by both academics and practitioners.

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