Evidence of the heterogeneous market hypothesis using wavelet multi -resolution analysis

In finance literature many economic theories and models have been proposed to explain and estimate the relationship between risk and return. Assuming risk averseness and rational behavior on part of the investor, the models are developed which are supposed to help in forming efficient portfolios that either maximize (minimize) the expected rate of return (risk) for a given level of risk (rates of return). One of the most used models to form these efficient portfolios is the Sharpe\u27s Capital Asset Pricing Model (CAPM). In the development of this model it is assumed that the investors have homogeneous expectations about the future probability distribution of the rates of return. That is, every investor assumes the same values of the parameters of the probability distribution. Likewise financial volatility homogeneity is commonly assumed, where volatility is taken as investment risk which is usually measured by the variance of the rates of return. Typically the square root of the variance is used to define financial volatility, furthermore it is also often assumed that the data generating process is made of independent and identically distributed random variables. This again implies that financial volatility is measured from homogeneous time series with stationary parameters. In this dissertation, we investigate the assumptions of homogeneity of market agents and provide evidence for the case of heterogeneity in market participants\u27 information, objectives, and expectations about the parameters of the probability distribution of prices as given by the differences in the empirical distributions corresponding to different time scales, which in this study are associated with different classes of investors, as well as demonstrate that statistical properties of the underlying data generating processes including the volatility in the rates of return are quite heterogeneous. In other words, we provide empirical evidence against the traditional views about homogeneity using non-parametric wavelet analysis on trading data, The results show heterogeneity of financial volatility at different time scales, and time-scale is one of the most important aspects in which trading behavior differs. In fact we conclude that heterogeneity as posited by the Heterogeneous Markets Hypothesis is the norm and not the exception