In this paper we propose a downside risk measure, the expectile-based Value at Risk (EVaR), which is more sensitive to the magnitude of extreme losses than the conventional quantile-based VaR (QVaR). The index $\theta$ of an EVaR is the relative cost of the expected margin shortfall and hence...

This paper proposes a new class of estimators based on the inter-quantile-range of intraday returns, referred to as Inter-Quantile-Range-based volatility (IQRBV), to estimate the integrated daily volatility. As the range-based volatility measure, the IQRBV estimate is insensitive to market...

In the finance literature, statistical inferences for large-scale testing problems usually suffer from data snooping bias. In this paper we extend the quot;superior predictive abilityquot; (SPA) test of Hansen (2005, JBES) to a stepwise SPA test that can identify predictive models without...

In this paper we consider properties of random aggregation in time series analysis. For application, we focus on the problem of estimating high-frequency beta of an asset return when the returns are subject to the effects of market microstructure. Specifically, we study the correlation between...

Finding a precise variance-covariance matrix is the building block of empirical finance. While microstructure-noise-robust methods for realized volatility are in the mainstream of financial econometrics, little if any attention has been devoted to estimating a noise-free realized covariance for...