We propose a novel multivariate GARCH model that incorporates realized measures for the variance matrix of returns. The key novelty is the joint formulation of a multivariate dynamic model for outer-products of returns, realized variances and realized covariances. The updating of the variance...

We introduce a new fractionally integrated model for covariance matrix dynamics based on the long-memory behavior of daily realized covariance matrix kernels and daily return observations. We account for fat tails in both types of data by appropriate distributional assumptions. The covariance...

This paper investigates the merits of high-frequency intraday data when forming minimum variance portfolios and minimum tracking error portfolios with daily rebalancing from the individual constituents of the S&P 100 index. We focus on the issue of determining the optimal sampling frequency,...

We propose a new approach for estimating mutual fund performance that simultaneously controls for both factor exposure and firm characteristics. This double-adjusted alpha is motivated by the recent findings that traditional Fama-French style factor models do not fully adjust returns for the...

Low probability events are overweighted in the pricing of out-of-the-money index puts and single stock calls. This behavioral bias is strongly time-varying, and is linked to equity market sentiment and higher moments of the risk-neutral density. We find that our implied volatility (IV) sentiment...

A novel dynamic asset-allocation approach is proposed where portfolios as well as portfolio strategies are updated at every decision period based on their past performance. For modeling, a general class of models is specified that combines a dynamic factor and a vector autoregressive model and...