Most asset prices are subject to significant volatility. Arrival of new information is viewed as the main source of volatility. As new information is continually released, financial asset prices exhibit volatility persistence, which affects financial risk analysis and risk management strategies....

In this paper, we examine the validity of hedonic models for estimating heterogeneous assets returns. We look into the art markets, and show that the returns on hedonic indices strictly depend on the specifications of the model. Different sets of variables lead to different returns. This means...

We develop an estimator for publication bias and apply it to 156 hedge portfolios based on published cross-sectional return predictors. Publication bias adjusted returns are only 12% smaller than in-sample returns. The small bias comes from the dispersion of returns across predictors, which is...

This paper considers spot variance path estimation from datasets of intraday high frequency asset prices in the presence of diurnal variance patterns, jumps, leverage effects and microstructure noise. We rely on parametric and nonparametric methods. The estimated spot variance path can be used...

This paper deals with the estimation of the risk-return trade-off. We use a MIDAS model for the conditional variance and allow for possible switches in the risk-return relation through a Markov-switching specification. We find strong evidence for regime changes in the risk-return relation. This...

This paper examines the relationship between volatility and the probability of occurrence of expected extreme returns in the Canadian market. Four measures of volatility are examined: implied volatility from firm option prices, conditional volatility calculated using an EGARCH model,...

We put forward two jump-robust estimators of integrated volatility, namely realized information variation (RIV) and realized information power variation (RIPV). The "information" here refers to the difference between two-grid of ranges in high-frequency intervals, which preserves continuous...

A new method for computing the standard errors of returns-based risk and performance estimators for serially correlated returns is developed. The method uses the fact that any such estimator can be represented as the sum of returns that are transformed using the estimator's influence function,...

In this article, the authors measure the impact of estimation error on latent factor model forecasts of portfolio risk and factor exposures. In markets simulated with a Gaussian return generating process, the authors measure errors in forecasts for equally weighted and long-only minimum variance...

Daily asset returns are modeled using self decomposable limit laws and the structure is used to estimate the density of the uncentered data. Estimates of mean returns are a byproduct of the density estimate. Estimates of mean returns via density estimation have significantly lower standard...