MCMC techniques, we estimate the model by fitting it to US data on the level of the aggregate US stock market, the short …

inference that feature varying level of trade-off between estimation precision and computational speed. Using monthly data for …

properties for detecting bubbles. Empirical analysis using price-dividend ratios of S&P500 highlights the advantages of our …

properties for detecting bubbles. Empirical analysis using price-dividend ratios of S&P500 highlights the advantages of our …

improving the statistical fit of the model. Suitable algorithms of Markov Chain Monte Carlo (MCMC) are developed to t the … estimation methods commonly used to estimate the SCD model in the literature, we work with the original specification of the … that our proposed model and corresponding estimation methodology perform quite well. We also apply an auxiliary particle …

In this paper, we propose a Markov Chain Quasi-Monte Carlo (MCQMC) approach for Bayesian estimation of a discrete … the conventional Bayesian estimation method for SV models, pseudo-random numbers are usually used. Here we develop an …

. Analysis using simulated data reveals that our method has better power for detecting bubbles compared to existing altnerative …