We propose a new framework for modeling and forecasting common financial risks based on (un)reliable realized covariance measures constructed from high-frequency intraday data. Our new approach explicitly incorporates the effect of measurement errors and time-varying attenuation biases into the...

This paper provides evidence of the impact of hedge funds on asset markets. We construct a simple measure of the aggregate illiquidity of hedge fund portfolios, based on the cross-sectional average first order autocorrelation coefficient of hedge fund returns, and show that it has strong and...

Abstract Using recently proposed estimators of the variation of positive and negative returns (“realized semivariances”), and high frequency data for the S&P 500 index and 105 individual stocks, this paper sheds new light on the predictability of equity price volatility. We show that future...

We rely on newly-developed realized semicorrelations constructed from high-frequency returns together with hierarchical clustering and cross-validation techniques to identify groups of individual stocks that share common features. Implementing the new procedures based on intraday data for the...

We propose new asymmetric multivariate volatility models. The models exploit estimates of variances and covariances based on the signs of high-frequency returns, measures known as realized semivariances, semicovariances, and semicorrelations, to allow for more nuanced responses to positive and...

Rational respondents to economic surveys may report as a point forecast any measure of the central tendency of their (possibly latent) predictive distribution, for example the mean, median, mode, or any convex combination thereof. We propose tests of forecast rationality when the measure of...

One can consider the concept of market neutrality as having quot;breadthquot; and quot;depthquot;: quot;Breadthquot; reflects the number of market risks to which the hedge fund is neutral, while quot;depthquot; reflects the quot;completenessquot; of the neutrality of the fund to market risks. We...

Clustering methods such as k-means have found widespread use in a variety of applications. This paper proposes a formal testing procedure to determine whether a null hypothesis of a single cluster, indicating homogeneity of the data, can be rejected in favor of multiple clusters. The test is...

The use of a conditionally unbiased, but imperfect, volatility proxy can lead to undesirable outcomes in standard methods for comparing conditional variance forecasts. We derive necessary and sufficient conditions on functional form of the loss function for the ranking of competing volatility...

In this paper we analyze and interpret the quote price dynamics of 100 NYSE stocks stratified by trade frequency. We specify an error-correction model for the log difference of the bid and the ask price with the spread acting as the error-correction term, and include as regressors the...