A complete theory for evaluating interval forecasts has not been worked out to date. Most of
the literature implicitly assumes homoskedastic errors even when this is clearly violated, and …

State-of-the-art stochastic volatility models generate a “volatility smirk” that explains why out-of-the-money
index puts have high prices relative to the Black-Scholes benchmark. These …

International equity markets are characterized by nonlinear dependence and asymmetries.
We propose a new dynamic asymmetric copula model to capture long-run and short-run …

Index option prices differ systematically from Black–Scholes prices. Out-of-the-money put
prices (and in-the-money call prices) are relatively high compared to the Black–Scholes price. …

The Second Edition of this best-selling book expands its advanced approach to financial risk
models by covering market, credit, and integrated risk. With new data that cover the recent …

The cross section of stock returns has substantial exposure to risk captured by higher moments
of market returns. We estimate these moments from daily Standard & Poor's 500 index …

Financial risk model evaluation or backtesting is a key part of the internal model's approach
to market risk management as laid out by the Basle Committee on Banking Supervision. …

Volatility has been one of the most active and successful areas of research in time series
econometrics and economic forecasting in recent decades. This chapter provides a selective …

We use intraday data to compute weekly realized moments for equity returns and study their
time-series and cross-sectional properties. Buying stocks in the lowest realized skewness …

Which loss function should be used when estimating and evaluating option valuation
models? Many different functions have been suggested, but no standard has emerged. We …