A Variance Ratio Related Prediction Tool with Application to the NYSE Index 1825-2002
Cochrane’s variance ratio is a leading tool for detection of deviations from random walks in financial asset prices. This Paper develops a variance ratio related regression model that can be used for prediction. We suggest a comprehensive framework for our model, including model identification, model estimation and selection, bias correction, model diagnostic check, and an inference procedure. We use our model to study and model mean reversion in the NYSE index in the period 1825-2002. We demonstrate that in addition to mean reversion, our model can generate other characteristic properties of financial asset prices, such as short-term persistence and volatility clustering of unconditional returns.
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