On special partial types and weak canonical bases in simple theories

We define a notion of a weak canonical base for a partial type. This notion is weaker than the usual canonical base for an amalgamation base. We prove that certain family of partial types have a weak canonical base. This family clearly contains the class of amalgamation bases

A structural Time Series Model with Markov Switching.

We propose an innovations form of the structural model underlying exponential smoothing that is further augmented by a latent Markov switching process. A particular case of the new model is the local level model with a switching drift, where the switching component describes the change between high and low growth rate periods. This new model is used to analyse the US business cycle using US Quarterly real GNP data. Model parameters are estimated using a Gibbs sampling algorithm and subsequently used for forecasting purposes. In addition, the stability of the new model is tested against Hamilton's model over a range of observation periods.Structural models, Markov switching regime, Gibbs sampling Business cycle.

Association between Markov regime-switching market volatility and beta risk: Evidence from Dow Jones industrial securities

In this paper, the volatility of the return generating process of the market portfolio and the slope coefficient of the market model is assumed to follow a Markov switching process of order one. The results indicate very strong evidence of volatility switching behaviour in a sample of returns in the S&P500 index. In three of the thirty securities in the Dow Jones index, the estimated slope in the market model show strong switching behaviour. In these three securities the low risk state is more persistent than the high-risk state. For each security we estimate the conditional probabilities that the security is in the high (low) risk state given the market is in the high (low) volatility regime and show that this information can be used to classify securities into three distinct groups. There is no association between these groups and the securities' constant beta estimated in the market model and the Sharpe index. Some directions for further research are discussed.Asset pricing, Markov regime-switching, market volatility, beta risk

Association between Markov regime-switching market volatility and beta risk: Evidence from Dow Jones industrial securities.

In this paper, the volatility of the return generating process of the market portfolio and the slope coefficient of the market model is assumed to follow a Markov switching process of order one. The results indicate very strong evidence of volatility switching behaviour in a sample of returns in the S&P500 index. In three of the thirty securities in the Dow Jones index, the estimated slope in the market model show strong switching behaviour. In these three securities the low risk state is more persistent than the high-risk state. For each security we estimate the conditional probabilities that the security is in the high (low) risk state given the market is in the high (low) volatility regime and show that this information can be used to classify securities into three distinct groups. There is no association between these groups and the securities' constant beta estimated in the market model and the Sharpe index. Some directions for further research are discussed.Asset pricing, Markov regime-switching, market volatility, beta risk

Beta Risk and Regime Shift in Market Volatility

In this paper, we relate the returns in the thirty securities in the Dow Jones index to regime shifts in stock market volatility. We apply a Markov switching process of order one to market volatility and examine the variation in the securities' returns in different volatility regimes. We test the significance of the risk premium in different market regimes and we find evidence of relationship between market volatility and securities beta risk.Markov regime-switching, market volatility, beta risk