The valuation of options and many other derivative instruments requires an estimation of exante or forward looking volatility. This paper adopts a Bayesian approach to estimate stock price volatility. We find evidence that overall Bayesian volatility estimates more closely approximate the...

The price disparity between the A- and H-share markets for dual-listed firms in China is one of the most intriguing puzzles in the mainland and Hong Kong financial markets. In this paper, we revisit this price disparity puzzle using the channel of parameter uncertainty. In the presence of...

Among the 5,000 equity mutual funds in the world, more than 80 percent belong to some fund family. A fund family is a group of mutual funds supervised by the same investment group. Despite the prevalence of the family organization, previous literature, when evaluating mutual fund performance,...

In dynamic asset pricing models, when the model structure becomes complex and derivatives data are introduced in estimation, traditional Bayesian MCMC methods converge slowly, are difficult to design efficient proposals for parameters, and have large computational cost. We propose a two-stage...

We propose new Unconditional, Independence and Conditional Coverage VaR-forecast backtests for the case of annuity pricing under a Bayesian framework that significantly minimise the direct and indirect effects of $p$-hacking or other biased outcomes in decision-making, in general. As a...

We build on Fackler and King (1990) and propose a general calibration model for implied risk neutral densities. Our model allows for the joint calibration of a set of densities at different maturities and dates. The model is a Bayesian dynamic beta Markov random field which allows for possible...

We quantify crash risk in currency returns. To accomplish this task, we develop and estimate an empirical model of exchange rate dynamics using daily data for four currencies relative to the US dollar: the Australian dollar, the British pound, the Swiss franc, and the Japanese yen. The model...

This paper investigates time-changed infinite activity derivatives pricing models from the sequential Bayesian perspective. It proposes a sequential Monte Carlo method with the proposal density generated by the unscented Kalman filter. This approach overcomes to a large extent the particle...

Catastrophe (CAT) bond markets are incomplete and hence carry uncertainty in instrument pricing. As such various pricing approaches have been proposed, but none treat the uncertainty in catastrophe occurrences and interest rates in a sufficiently flexible and statistically reliable way within a...

We propose a nonparametric Bayesian approach for conducting inference on probabilistic surveys. We use this approach to study whether U.S. Survey of Professional Forecasters density projections for output growth and inflation are consistent with the noisy rational expectations hypothesis. We...