Showing 1 - 10 of 21
Optimal probabilistic forecasts of integer-valued random variables are derived. The optimality is achieved by estimating the forecast distribution nonparametrically over a given broad model class and proving asymptotic efficiency in that setting. The ideas are demonstrated within the context of...
Persistent link: https://www.econbiz.de/10005003387
A Bayesian approach to option pricing is presented, in which posterior inference about the underlying returns process is conducted implicitly via observed option prices. A range of models allowing for conditional leptokurtosis, skewness and time-varying volatility in returns are considered, with...
Persistent link: https://www.econbiz.de/10005427614
This paper presents a comprehensive empirical evaluation of option-implied and returns-based forecasts of volatility, in which recent developments related to the impact on measured volatility of market microstructure noise are taken into account. The paper also assesses the robustness of the...
Persistent link: https://www.econbiz.de/10005125282
This paper presents a comprehensive empirical evaluation of option-implied and returns-based forecasts of volatility, in which new developments related to the impact on measured volatility of market microstructure noise and random jumps are explicitly taken into account. The option-based...
Persistent link: https://www.econbiz.de/10005125283
This paper compares two alternative models for autocorrelated count time series. The first model can be viewed as a 'single source of error' discrete state space model, in which a time-varying parameter is specified as a function of lagged counts, with no additional source of error introduced....
Persistent link: https://www.econbiz.de/10005125287
A new class of option price models is developed and applied to options on the Australian S&P200 Index. The class of models generalizes the traditional Black-Scholes framework by accommodating time-varying conditional volatility, skewness and excess kurtosis in the underlying returns process. An...
Persistent link: https://www.econbiz.de/10005149038
A Bayesian Markov Chain Monte Carlo methodology is developed for estimating the stochastic conditional duration model. The conditional mean of durations between trades is modelled as a latent stochastic process, with the conditional distribution of durations having positive support. The sampling...
Persistent link: https://www.econbiz.de/10005149083
In this paper Bayesian methods are applied to a stochastic volatility model using both the prices of the asset and the prices of options written on the asset. Posterior densities for all model parameters, latent volatilities and the market price of volatility risk are produced via a hybrid...
Persistent link: https://www.econbiz.de/10005149095
This paper demonstrates the application of Bayesian simulation-based estimation to a class of interest rate models known as Affine Term Structure (ATS) models. The technique used is based on a Markov Chain Monte Carlo algorithm, with the discrete observations on yields augmented by additional...
Persistent link: https://www.econbiz.de/10005149102
This paper investigates the dynamic behaviour of jumps in financial prices and volatility. The proposed model is based on a standard jump diffusion process for price and volatility augmented by a bivariate Hawkes process for the two jump components. The latter process speci.es a joint dynamic...
Persistent link: https://www.econbiz.de/10010860403