Momentum returns have time-varying exposures to the three Fama and French equity risk factors. In particular factor loadings are higher when the factor returns during the ranking period are higher. In this study we look at momentum returns after hedging these time-varying exposures to the Fama...

Purpose – This paper aims to incorporate a market wide buying and selling pressure cost component into a spread decomposition model as spread cost component. Design/methodology/approach – The paper extends a commonly used trade indicator spread decomposition model to include a component...

The sum of squared intraday returns provides an unbiased and almost error-free measure of ex-post volatility. In this paper we develop a nonlinear Autoregressive Fractionally Integrated Moving Average (ARFIMA) model for realized volatility, which accommodates level shifts, day-of-the-week...

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,...

Quadratic optimization for asset portfolios often leads to error maximization, with optimizers zooming in on large errors in the predicted inputs, that is, expected returns and risks. The consequence in most cases is a poor real-time performance. In this paper we show how to improve real-time...

We study the effects of FOMC announcements of federal funds target rate decisions on individual stock returns, volatilities and correlations at the intraday level. For all three characteristics we find that the stock market responds differently to positive and negative target rate surprises....

We introduce the realized co-range, a novel estimator of the daily covariance between asset returns based on intraday high--low price ranges. In an ideal world, the co-range is five times more efficient than the realized covariance, which uses cross-products of intraday returns, when sampling at...

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,...

The sum of squared intraday returns provides an unbiased and almost error-free measure of ex-post volatility. In this paper we develop a nonlinear Autoregressive Fractionally Integrated Moving Average (ARFIMA) model for realized volatility, which accommodates level shifts, day-of-the-week...