Bayesian investor. We develop a constrained parameter learning approach for sequential estimation allowing for belief revisions …

This paper employs weighted least squares to examine the risk-return relation by applying high-frequency data from four … returns and expected risk. However, by using quantile regressions, we find that the risk-return relation moves from negative … to positive as the returns’ quantile increases. A positive risk-return relation is valid only in the upper quantiles. The …

applied in order to examine calendar effects in stock returns and to formulate appropriate financial and risk portfolios. We … propose an alternative approach in the estimation of the day of the week effect. More specifically we apply fuzzy regressions …

. Bootstrap methods generally perform better than t-tests, but they can also yield very misleading inferences in some cases. …