On modeling the volatility in speculative prices
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Following the Probabilistic Reduction(PR) Approach, this paper proposes the Student's Autoregressive (St-AR) Model, Student's t Vector Autoregressive (St-VAR) Model and their heterogeneous versions, as an alternative to the various ARCH type models, to capture univariate and multivariate volatility. The St-AR and St-VAR models di[BULLET]er from the latter volatility models because they give rise to internally consistent statistical models that do not rely on ad-hoc specifi[BULLET]cation and parameter restrictions, but model the conditional mean and conditional variance jointly. The univariate modeling is illustrated using the Real E[BULLET]ect Exchange Rate(REER) indices of three mainstream currencies in Asia (RMB, Hong Kong Dollar and Taiwan Dollar), while the multivariate volatility modeling is applied to investigate the relationship between the REER indices and stock price indices in mainland China, as well as the relationship between the stock prices in mainland China and Hong Kong. Following the PR methodology, the information gained in Mis-Speci[BULLET]cation(M-S) testing leads to respeci[BULLET]cation strategies from the original Normal-(V)AR models to the St-(V)AR models. The results from formal Mis-Speci[BULLET]cation (M-S) tests and forecasting performance indicate that the St-(V)AR models provide a more appropriate way to model volatility for certain types of speculative price data.
- Doctoral Dissertations