Abstract
A central issue for managers or investors in portfolio management of assets is to select the assets to be included and to predict the value of the portfolio, given a variety of historical and concurrent information regarding each asset in the portfolio. There exist several criteria or “models” to predict asset returns whose success depends on unknown form (parameters) of underlying probability distributions of assets, and whether one encounters a bull, bear or at market. Different models focus on different aspects of historical market data. We use the recently developed Combinatorial Fusion Analysis (CFA) in computer science to enhance portfolio performance and demonstrate with an example using U.S. stock market data that fusion methods can indeed improve the portfolio performance. The R software is found to offer powerful tools for application of CFA in Finance.
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Vinod, H.D., Hsu, D.F., Tian, Y. (2010). Combinatorial Fusion for Improving Portfolio Performance. In: Vinod, H. (eds) Advances in Social Science Research Using R. Lecture Notes in Statistics(), vol 196. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-1764-5_6
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DOI: https://doi.org/10.1007/978-1-4419-1764-5_6
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