In this paper the authors set out to date-stamp periods of US housing price explosivity for the period 1830–2013. They make use of several robust techniques that allow them to identify such periods by determining when prices start to exhibit explosivity with respect to its past behaviour and...

In this paper, the authors set out to date-stamp periods of US housing price explosivity for the period 1830-2013. They make use of several robust techniques that allow them to identify such periods by determining when prices start to exhibit explosivity with respect to its past behaviour and...

The effect of COVID‑19 on stock market performance has important implications for both financial theory and practice. This paper examines the relationship between COVID‑19 and the instability of both stock return predictability and price volatility in the U.S over the period January 1st,...

In recent years, numerous volatility-based derivative products have been engineered. This has led to interest in constructing conditional predictive densities and confidence intervals for integrated volatility. In this paper, we propose nonparametric kernel estimators of the aforementioned...

Forecasting-volatility models typically rely on either daily or high frequency (HF) data and the choice between these two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer of many limitations. HF data feature microstructure problem,...

We investigate the impact of China's economic policy uncertainty (EPU) on the time series variation of Chinese stock market expected returns. Using the news based measure in Baker, Bloom, and Davis (2016), we find that EPU predicts negatively future stock market return at various horizons. This...

This paper presents the first comparison of the accuracy of density forecasts for stock prices. Six sets of forecasts are evaluated for DJIA stocks, across four forecast horizons. Two forecasts are risk-neutral densities implied by the Black-Scholes and Heston models. The third set are...

This paper proposes an ex post volatility estimator, called mixed interval realized variance (MIRV), that uses high-frequency data to provide measurements robust to the idiosyncratic noise of stock markets caused by market microstructures. The theoretical properties of the new volatility...

In this paper, we use factor-augmented HAR-type models to predict the daily integrated volatility of asset returns. Our approach is based on a proposed two-step dimension reduction procedure designed to extract latent common volatility factors from a large dimensional and high-frequency returns...

This Appendix contains details on several technical points and additional empirical results. Sections in this Appendix are indexed by letters and formulas/tables/figures by a letter followed by a number (e.g. A.1). Sections and formulas/tables/figures of the paper are referenced by numbers. In...