Many securities are, to a certain extent, subject to credit risk in one way or another. Both the financial institutions and regulators are keen to have their credit risk exposures well managed. In order to fulfill their needs, the market for credit derivatives has become one of the fast growing...

This article analyzes the specifications of option pricing models based on time-changed Levy processes. We classify option pricing models based on (i) the structure of the jump component in the underlying return process, (ii) the source of stochastic volatility, and (iii) the specification of...

We introduce SV models with Markov regime changing state equation (SVMRS) to investigate the important properties of volatility, high persistence and smoothness. With the quasi-ML approach proposed in our study, we showed that volatility is far less persistent and smooth than the GARCH or SV...

The stochastic volatility (SV) models had not been popular as the ARCH (autoregressive conditional heteroskedasticity) models in practical applications until recent years even though the SV models have close relationship to financial economic theories. The main reason is that the likelihood of...

Financial institutions (FIs) suffered from non-performing loans when debt-ridden firms failed. Nonetheless, FIs in Korea increased loans to distressed firms in the 1990s. Possible explanations for these loans include FIs having better inside information on borrowing firms, firms' sharing...

We analyze the properties of a bias-corrected realized variance (RV) in the presence of iid market microstructure noise. The bias correction is based on the first-order autocorrelation of intraday returns and we derive the optimal sampling frequency as defined by the mean squared error (MSE)...

Techniques for simulated maximum likelihood (SML) estimation, filtering, and assessing the fit of stochastic volatility models are examined. Both one- and two-factor models (with leverage effects) are considered. The techniques are computationally efficient, robust, straightforward to implement,...

We present a general framework for testing the accuracy of Value-at-Risk (VaR) forecasts. The approach is based on the observation that violations – the days on which portfolio losses exceed the VaR – should be unpredictable. Specifically, these violations form a martingale difference...

The properties and applications of the normal log-normal (NLN) mixture are considered. The moment of the NLN mixture is shown to be finite for any positive order. The expectations of exponential functions of a NLN mixture variable are also investigated. The kurtosis and skewness of the NLN...