This paper proposes a range-based dynamic conditional correlation (DCC) model combined by the return-based DCC model and the conditional autoregressive range (CARR) model. The substantial gain in efficiency of volatility estimation can boost the accuracy for estimating time-varying covariances....

We develop a discrete-time affine stochastic volatility model with time-varying conditional skewness (SVS). Importantly, we disentangle the dynamics of conditional volatility and conditional skewness in a coherent way. Our approach allows current asset returns to be asymmetric conditional on...

The advent of close to zero or even negative rates in major currencies has made the traditional lognormal Black-Scholes-Merton volatility as a representation of option prices in the interest rate market obsolete. Recently more and more cap/floor and even swaption prices in major currencies are...

Range-based volatility estimators are analyzed in both daily and intraday sampling frequency and are also compared to the realized volatility estimator. The family of realized range-based estimators is extended as three range-based estimators are introduced. These three realized Parkinson...

Using high-frequency intraday data, we construct, test and model seven new realized volatility estimators for six international equity indices. We detect jumps in these estimators, construct the jump components of volatility and perform various tests on their properties. Then we use the class of...

We propose a new methodology for obtaining arbitrage free European option prices from a SABR-like parameterisation. The method consists of specifying the joint distribution of the volatility and underlying at a given expiry and requires the calculation of a simple one-dimensional numerical...

Managed volatility strategies adjust market exposure in inverse relation to a risk estimate, to stabilize realized portfolio volatility through time. Our paper examines strategy performance from an investment practitioner perspective. Using long-term data from the Standard & Poor's 500, we show...

We develop an empirically highly accurate discrete-time daily stochastic volatility model that explicitly distinguishes between the jump and continuous time components of price movements using nonparametric realized variation and Bipower variation measures constructed from high-frequency...

We develop a discrete-time affine stochastic volatility model with time-varying conditional skewness (SVS). Importantly, we disentangle the dynamics of conditional volatility and conditional skewness in a coherent way. Our approach allows current asset returns to be asymmetric conditional on...

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 survey of the most important theoretical developments and empirical insights to emerge from this burgeoning...