The paper considers a linear factor model (LFM) to study the behaviour of the correlation coefficient between various stock returns during a downturn. Changing correlation is related to the tail distribution of the driving factors, which is the market for Sharpe's one-factor model. General...

We introduce SV models with Markov regime changing state equation (SVMRS) to investigate the important properties of volatility, high persistence and smoothness. With the quasi-ML approach proposed in our study, we showed that volatility is far less persistent and smooth than the GARCH or SV...

We propose generalised stochastic volatility models with Markov regime changing state equations (SVMRS) to investigate the important properties of volatility in stock returns, specifically high persistence and smoothness. The model suggests that volatility is far less persistent and smooth than...

We investigate loss aversion in financial markets using a typical asset allocation problem. Our theoretical and empirical results show that investors in financial markets are more loss averse than assumed in the literature. Moreover, loss aversion changes depending on market conditions;...

A new framework is provided for identifying market timing. The analysis focuses on the local joint history of the hedge fund with the benchmark. The approach is fully nonparametric. Therefore, it has the advantage of avoiding the misspecification problems so common in this literature. The test...

Nonparametric density estimators on RK may fail to be consistent when the sample size n does not grow fast enough relative to reduction in smoothing. For example a Gaussian kernel estimator with bandwidths proportional to some sequence hn is not consistent if nhnK fails to diverge to infinity....