The objective of this study is to investigate the predictability of model based forecasts and the VIX index on forecasting future volatility of S&P 500 index daily returns. The study period is from January 1990 to December 2010, including 5291 observations. A variety of time series models were estimated, including random walk model, GARCH (1,1), GJR(1,1) and EGARCH (1,1) models. The study resul...

This paper presents a joint analysis of the term structure of credit default swap (CDS) spreads and the implied volatility surface. The rapid development of the CDS market has provided convenient products to extract credit risk, and its interaction with equity volatility has been analyzed in many studies. However, in most of them the 5-year credit default swap spread is used to measure credit r...

Several studies find that the return volatility of stocks tends to exhibit long-range dependence, heavy tails, and clustering. Because stochastic processes with self-similarity possess long-range dependence and heavy tails, Rachev and Mittnik (2000) suggest employing self-similar processes to capture these characteristics in return volatility modeling. In this paper, we find using high-frequenc...

 Commodity markets: overview, description and structure  Commodity spot price models, their performance and calibration  Forward curve modeling for commodities  Modeling commodity price volatility  Correlations/dependencies in commodity portfolios  Modeling risk of a commodity portfolio  Typical commodity derivatives (quanto, Asian, spread and basket options, volumetric and swing options...

Default probability is a fundamental variable determining the credit worthiness of a firm and equity volatility estimation plays a key role in its evaluation. Assuming a structural credit risk modeling approach, we study the impact of choosing different non parametric equity volatility estimators on default probability evaluation, when market microstructure noise is considered. A general stocha...

We discuss methods for time-discretization and simulation of squareroot SDEs, both in isolation (CIR process) and as part of vector-SDEs modeling stochastic volatility (Heston model). Both exact and biased discretization methods are covered.

This chapter considers the modeling of electricity forward curve dynamics with parameterized volatility and correlation structures. We estimate the model parameters by using the Nordic market’s price data and show how the model can be implemented into everyday industry practice.

This paper considers the pricing of options when there are jumps in the pricing kernel and correlated jumps in asset prices and volatilities. We extend theory developed by Nelson (1990) and Duan (1997) by considering limiting models for our resulting approximating GARCH-Jump process. Limiting cases of our processes consist of models where both asset price and local volatility follow jump diffus...