This paper introduces a new class of multivariate volatility models which is easy to estimate using covariance targeting, even with rich dynamics. We call them rotated ARCH (RARCH) models. The basic structure is to rotate the returns and then to fit them using a BEKK-type parameterization of the...

High frequency financial data allows us to learn more about volatility, volatility of volatility and jumps. One of the key techniques developed in the literature in recent years has been bipower variation and its multipower extension, which estimates time-varying volatility robustly to jumps. We...

This paper introduces a new class of multivariate volatility models that utilizes high-frequency data.  We discuss the models' dynamics and highlight their differences from multivariate GARCH models.  We also discuss their covariance targeting specification and provide closed-form formulas...

This paper studies in some detail a class of high-frequency-based volatility (HEAVY) models. These models are direct models of daily asset return volatility based on realised measures constructed from high-frequency data. Our analysis identifies that the models have momentum and mean reversion...

This paper assesses the quantitative impact of ambiguity on the historically observed financial asset returns and prices. The single agent, in a dynamic exchange economy, treats the conditional uncertainty about the consumption and dividends next period as ambiguous. We calibrate the agent's...

This paper assesses the quantitative impact of ambiguity on the historically observed financial asset returns and prices. The single agent, in a dynamic exchange economy, treats uncertainty about the conditional mean of the probability distribution on consumption and dividends in the next period...

This paper assesses the quantitative impact of ambiguity on the historically observed financial asset returns and prices. The single agent, in a dynamic exchange economy, treats uncertainty about the conditional mean of the probability distribution on consumption and dividends in the next period...

We investigate the properties of the composite likelihood (CL) method for (T ×N_T ) GARCH panels. The defining feature of a GARCH panel with time series length T is that, while nuisance parameters are allowed to vary across N_T series, other parameters of interest are assumed to be common. CL...

This paper studies in some detail a class of high frequency based volatility (HEAVY) models. These models are direct models of daily asset return volatility based on realized measures constructed from high frequency data. Our analysis identifies that the models have momentum and mean reversion...