While stochastic volatility models improve on the option pricing error when compared to theBlack-Scholes-Merton model, mispricings remain. This paper uses mixed normalheteroskedasticity models to price options. Our model allows for significant negative skewnessand time varying higher order...

Daily returns of financial assets are frequently found to exhibit positive autocorrelation at lag 1. When specifying a linear AR(l) conditional mean, one may ask how this predictability affects option prices. We investigate the dependence of option prices on autoregressive dynamics under...

This paper uses asymmetric heteroskedastic normal mixture models to fit return data and to price options. The models can be estimated straightforwardly by maximum likelihood, have high statistical fit when used on S&P 500 index return data, and allow for substantial negative skewness and time...

This paper examines the theoretically obtained prices with values based on temperature data in the Isle of Man and the UK. We have also seen that the simulated temperature trajectories do not appear to include entire seasons where the temperature remains cooler than normal. Anecdotally we have...

Can-do options are bespoke option structures listed on Safex and Yield-X. The JSE is the first exchange in the world to list, trade and clear exotic options. The first exotic was listed on 8 January 2007 with the onset of the financial crisis that played out during 2008. The option was on the...

We propose optimal mean-variance dynamic hedging strategies in discrete time under a multivariate Gaussian regime-switching model. The methodology, which also performs pricing, is robust to time-varying and clustering risk observed in financial time series. As such, it overcomes the main...

In this paper we examine the empirical performance of affine jump diffusion models with stochastic volatility in a time series study of crude oil prices. We compare four different models and estimate them using the Markov Chain Monte Carlo method. The support for a stochastic volatility model...

Pushing models to extremes can expose output biases that stem from underlying assumptions. In the case of industry standard option valuation models, long term, high volatility securities provide a stress test vehicle. For instance, in evaluating a stock with 60% volatility, industry standard...

An exploratory estimation of ARFIMA(p,d,q) models on agricultural spot and futures markets showed us that the estimated d is quite sensitive to the number of lags included in the short-term dynamics. AIC and SIC agreed there were many lags but, familiarly, disagreed on how many. To address this...

As a sign of ambivalence in the regulatory definition of capital adequacy for credit risk and the quest for more efficient refinancing sources collateral loan obligations (CLOs) have become a prominent securitisation mechanism. This paper presents a loss-based asset pricing model for the...