We propose and test a methodological framework to examine the relation between mutual fund fees and return predictability. Gil-Bazo and Ruiz-Verdu (2009) drew attention to the puzzling fact that funds with worse before-fee performance charge higher fees. We make another contribution to the...

Final working paper version. "" Published version: The Review of Financial Studies, Volume 31, Issue 7, July 2018, pp. 2499–2552. Past fund performance does a poor job of predicting future outcomes. The reason is noise. Using a random effects framework, we reduce the noise by pooling...

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,...

Realized covariance models specify the conditional expectation of a realized covariance matrix as a function of past realized covariance matrices through a GARCH-type structure. We compare the forecasting performance of several such models in terms of economic value, measured through economic...

The purpose of this research is to determine the main forecasting factors of stock analysts, to analyze whether stock analysts have a rational base for their advice to the individual investors. According to the Modigliani-Miller theorem, the factors which affected to dividend and capital gain...

This paper investigates whether realized and implied volatilities of individual stocks can predict the cross-sectional variation in expected returns. Although the levels of volatilities from the physical and risk-neutral distributions cannot predict future returns, there is a significant...

This paper provides a comprehensive analysis on the stock return predictability in Turkey, January 1997 to July 2011, by employing both portfolio method and cross-sectional regressions. In the risk-related predictors, we found predictive power of beta, total volatility, and idiosyncratic...

We introduce a new, hybrid measure of stock return tail covariance risk, motivated by the under-diversified portfolio holdings of individual investors, and investigate its cross-sectional predictive power. Our key innovation is that this covariance is measured across the left tail states of the...

We introduce a new, hybrid measure of stock return tail covariance risk, motivated by the under-diversified portfolio holdings of individual investors, and investigate its cross-sectional predictive power. Our key innovation is that this covariance is measured across the left tail states of the...

We introduce a new, hybrid measure of stock return tail covariance risk, motivated by the under-diversified portfolio holdings of individual investors, and investigate its cross-sectional predictive power. Our key innovation is that this covariance is measured across the left tail states of the...