Motivated by studies of the impact of frictions on asset prices, we examine the effect of key components of time-series momentum strategies on turnover and performance. We show that more efficient volatility estimation and price trend detection can significantly reduce portfolio turnover by more...

This paper first examines the efficiency of the UK covered warrants market by adopting a stochastic dominance (SD) approach to examine market efficiency. Our empirical analyses reveal that neither covered warrants nor the underlying shares stochastically dominate each other, which implies that...

We estimate the latent factors in high-dimensional panel non-Gaussian data using Higher-order multi-cumulant Factor Analysis (HFA). HFA consists of an eigenvalue ratio test to select the number of non-Gaussian factors and uses alternating regressions to estimate both Gaussian and non-Gaussian...

Risk management is an important aspect of financial research because correlations among financial data are essential in evaluating portfolio risk. Among various correlations, spatiotemporal correlations involve economic entity attributes and are interrelated in space and time. Such correlations...

We introduce a Mixed-Frequency Factor Model (MFFM) to estimate vast dimensional covari- ance matrices of asset returns. The MFFM uses high-frequency (intraday) data to estimate factor (co)variances and idiosyncratic risk and low-frequency (daily) data to estimate the factor loadings. We propose...

This paper proposes a data-based measure of model performance to discriminate among competing asset pricing models of return predictability. I form a set of variance bounds on pricing kernels based on different systems for predicting asset returns. For a given asset pricing model, I define the...

We propose a jump robust positive semidefinite rank-based estimator for the daily covariance matrix based on high-frequency intraday returns. It disentangles covariance estimation into variance and correlation components. This allows to estimate correlations over lower sampling frequencies, to...

In this paper, we build estimation error in mean returns into the mean-variance (MV) portfolio theory under the assumption that returns on individual assets follow a joint normal distribution. We derive the conditional sampling distribution of the MV portfolio along with its mean and risk return...

We evaluate the impact of extreme market shifts on equity portfolios and study the difference in negative and positive reactions to market jumps with implications for portfolio risk management. Employing high-frequency data for the constituents of the S&P500 index over the period 2 January 2003...