Investors' behavior and rotated asset pricing models: Empirical evidence.

摘要

This research examines the risk-retum relationship of the simple asset pricing model and introduces optimized axis rotation to accommodate investors' expectation of the return. Axis rotation defined in several specifications and applied to different models such as simple asset pricing models; CAPM and market model, conditional partitioned asset pricing models; CAPM and market model under a four-way partition of daily returns derived from expected values of individual asset and market returns based on their current movements. Proposed asset pricing model is referred as rotated asset pricing models, RAPM.; The analysis of the RAPM is carried out for 100 companies from January 2, 1986 through December 29, 2000 using daily returns from the CRSP ® data set. The S&P 500 Index serves as the indicator of general market performance for the CAPM, market models, and for their 4-State variants. Risk free rate used in CAPM, is daily observation of 3-month T-Bill Rate obtained from Federal Reserve Economic Data, FRED®, database.; Our results show that RAPM, with axis rotation to accommodate investors' expectations of the asset and the market returns, outperforms simple asset pricing models, in terms of explaining variation in daily returns. Proposed models also allow empirical testing of most important element of Daniel Kahneman and Amos Tversky's (1979) prospect theory; dependence of expected returns on the current reference frame in 1986–2000 data for 100 companies. Another implication of the RAPM is the explanation of the part of the equity premium by adopting the buyers' expectation on the return on equity is higher than the relative market return. Rotation of the axes in the asset pricing model provides a partial explanation of the equity premium phenomenon.; These findings are important because they help us understand investor behavior better: the investor's valuation process definitely depends on current high frequency information in the reference frame, that information strongly influences expected asset returns, and its inclusion in the asset pricing model enables that model to explain two to five times as much of the historical variation in the asset returns compared to the conventional asset pricing models such as, CAPM and the market model.