The Anomalies Of Stock Return With Behavioral Finance And Empirical Research On Dynamic Simulation

Since Jegadeesh and Titman (1993)and DeBondt and Thaler (1985) respectively documented the short-run cross-sectional momentum and the long-run cross-sectional reversal in stock returns, more and more anomalies had been found gradually. These anomalies made people suspect the academic authority of Efficient Market Hypothesis, stimulated the development of Behavioral Finance, and produced a lot of technical strategies such as momentum trade strategy and reversal trade strategy in practice.According to the existing related literature, this research relies on the scientific results on Behavioral Finance, exercises heterogeneous beliefs method, follows the analytic framework in traditional Financial Economics, sets up normative theoretical model, explains uniformly that the anomalies of stock returns. Compared with related literature, i.e. BSV, HS, DSSW, this research absorbs their merit, relaxes some assumptions, leaves the classical routine of regime-shifting, appends the updating ability for investors, gets over the intrinsic bug about cognitive biases keeping invariable under dynamic condition, extents living space of the model.In the aspect of empirical approach, for the sake of getting rid of Financial Econometrics' restriction on cognitive biases and static simulation's under-reaction on investors dynamic updating ability, introduces the Computational Finance method, uses the logical structure and algorithm on artificial stock market (ASM) in Santa Fe Institute, amends the program based on model assumptions, makes computers simulate the trader's behave, receives stock return data, validates the model result. This research emphasizes much more Agent's irrationality rooted cognitive biases and the difference of forecast normal formulas than the classical method on Computational Finance.