settings, one with a stochastic and one with a constant volatility. We find that individual investors' well-being will not be … stochastic volatility market than in the constant volatility market. …

including stochastic volatility models. A robust hedging strategy avoids any losses as long as the realised volatility stays …

Tests for the existence and the sign of the volatility risk premium are often based on expected option hedging errors … the premium is the same as the sign of the mean hedging error for a large class of stochastic volatility option pricing …

kind of the non-traded risk factors. Our main findings for a stochastic volatility model with unbounded volatility show …

autoregressive processes revealing time-varying stochastic volatility. The factor volatilities capture risk inherent to the term … additional determinants of future excess returns. Finally, we illustrate that the yield and volatility factors are closely con …

In this paper, we review the most common specifications of discrete-time stochastic volatility (SV) models and …

capturing interest rate risk. The so-called Stochastic Volatility Nelson-Siegel (SVNS) model allows for stochastic volatility in … evidence for time-varying volatility in the yield factors. This is mostly true for the level and slope volatility revealing … also the highest persistence. It turns out that the inclusion of stochastic volatility improves the model's goodness …

In this paper we propose a Libor model with a high-dimensional specially structured system of driving CIR volatility …

to model a credit quality process as an Itô integral with respect to a Brownian motion with a stochastic volatility … conditional default probabilities and credit spreads. An example for a volatility process is the square root of a Lévy …