Affiliation:
1. Department of Mathematics and Statistics, York University, Toronto, ON M3J 1P3, Canada
Abstract
We improve the traditional simple moving average strategy by incorporating an investor-specific risk tolerance into the method. We then propose a multiasset generalized moving average crossover (MGMA) strategy. The MGMA strategies allocate wealth between risky assets and risk-free assets in an adaptive manner, with the risk tolerance specified by an investor. We derive the expected log-utility of wealth, which allows us to estimate the optimal allocation parameters. The algorithm using our MGMA strategy is also presented. As the multiple risky assets can have different variability levels and could have various degrees of correlations, this trading strategy is evaluated on both simulated data and global high-frequency exchange-traded fund (ETF) data. It is shown that the MGMA strategies could significantly increase both the investor’s expected utility of wealth and the investor’s expected wealth.
Funder
Natural Science and Engineering Research Council of Canada
Subject
General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)
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