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A0565
Title: A dynamic semiparametric characteristics-based model for optimal portfolio selection Authors:  Shaoran Li - Peking University (China) [presenting]
Oliver Linton - University of Cambridge (United Kingdom)
Chaohua Dong - Zhongnan University of Economics and Law (China)
Gregory Connor - Maynooth University (Ireland)
Abstract: A two-step semiparametric methodology is developed for portfolio weight selection for characteristics-based factor-tilt and factor-timing investment strategies. It is built upon the expected utility maximization framework. Asset returns are assumed to obey a characteristics-based factor model with time-varying factor risk premia. It is proved under our return-generating assumptions that an approximately optimal portfolio can be established using a two-step procedure in a market with a large number of assets. The first step finds optimal factor-mimicking sub-portfolios using a quadratic objective function over linear combinations of characteristics-based factor loadings. The second step dynamically combines these factor-mimicking sub-portfolios based on a time-varying signal, using the investors' expected utility as the objective function. A two-stage semiparametric estimator is developed and implemented. It is applied to CRSP (Center for Research in Security Prices) and FRED (Federal Reserve Economic Data) data, and excellent in-sample and out-sample performance consistent with investors' risk aversion levels is found.