This study combines the empirical estimation of a Double-Exponential Jump-Diffusion (DEJD) process for a CDS index and the use of estimated parameters to price options on the index. In the first step we find Maximum Likelihood estimates for the diffusion volatility, the Poisson jump frequencies,...

This article provides a mathematical and empirical investigation of the reasons for the presence of skewness and kurtosis in financial data. The results indicate that this phenomenon is triggered by higher-order moment dependencies in the data, such as asymmetric and conditional volatility....

This paper presents a new approach to deriving default intensities from CDS or bond spreads that yields smooth intensity curves required e.g. for pricing or risk management purposes. Assuming continuous premium or coupon payments, the default intensity can be obtained by solving an integral...

This paper presents a new approach to deriving default intensities from CDS or bond spreads that yields smooth intensity curves required e.g. for pricing or risk management purposes. Assuming continuous premium or coupon payments, the default intensity can be obtained by solving an integral...

This study compares the efficacy of Black–Scholes implied volatility (BSIV) with model-free implied volatility (MFIV) in providing volatility forecasts for 13 North American, European, and Asian stock market indexes: S&P 500 (United States), S&P/ASX 200 (Australia), S&P/TSX 60 (Canada), AEX...

We consider several time series and for each of them, we fit an appropriate dynamic parametric model. This produces serially independent error terms for each time series. The dependence between these error terms is then modeled by a regime-switching copula. The EM algorithm is used for...

A method to price American-style option contracts in a limited information framework is introduced. The pricing methodology is based on sequential Monte Carlo techniques, as presented in Doucet, de Freitas, and Gordon's text "Sequential Monte Carlo Methods in Practice", and the least-squares...

We introduce a new method to price American-style options on underlying investments governed by stochastic volatility (SV) models. The method does not require the volatility process to be observed. Instead, it exploits the fact that the optimal decision functions in the corresponding dynamic...

This paper proposes a novel positive nonparametric estimator of the conditional variance function without reliance on logarithmic or other transformations. The estimator is based on an empirical likelihood modification of conventional local level nonparametric regression applied to squared mean...

This chapter deals with nonparametric estimation of the risk neutral density. We present three different approaches which do not require parametric functional assumptions on the underlying asset price dynamics nor on the distributional form of the risk neutral density. The first estimator is a...