We study whether prices of traded options contain information about future extreme market events. Our option-implied conditional expectation of market loss due to tail events, or tail loss measure, predicts future market returns, magnitude, and probability of the market crashes, beyond and above...

In this paper we propose a simple one-factor quantile regression model based on realized volatility to forecast Value-at-Risk (VaR). The model only uses daily realized volatility as input and thus simplifies estimation substantially compared with most other methodologies currently used to...

The subprime crisis was quite damaging for hedge funds. Using the local projection method (Jordà 2004, 2005, 2009), we forecast the dynamic responses of the betas of hedge fund strategies to macroeconomic and financial shocks-especially volatility and illiquidity shocks-over the subprime crisis...

We derive risk-neutral option price formulas for plain-vanilla temperature futures derivatives on the basis of several multi-factor Ornstein-Uhlenbeck temperature models which allow for seasonality in the mean level and volatility. Our main innovation consists in an incorporation of omnipresent...

This paper documents a significant time-series momentum effect that is consistent and robust across all examined conventional asset classes from 1969 to 2015. We find that the duration and magnitude of time-series momentum is different in developed and emerging markets, but this is no longer the...

We investigate the use of machine learning techniques into building statistically stable systematic allocation strategies. Traditionally, allocation processes usually rely on variations of Markowitz framework such as Mean Variance allocation, Maximum Diversity, Risk Allocation , Value at Risk,...

The modeling of wind speed is a traditional topic in meteorological researches where the main interest is on the short term forecast of wind speed intensity and direction. More recently this theme has received some interest in the quantitative finance literature for its relations with the...

PurposeThe purpose of this paper is to propose an improved reinsurance pricing framework, which includes a crop yield forecasting model that integrates weather variables and crop production information from different geographically correlated regions using a new credibility estimator, and closed...

In this study we propose a stochastic mortality forecast model that may be viewed as a Lévy process. First, age, period and cohort effects are objectively identified in a given matrix of historic mortality data. Next, these patterns are removed from the matrix of mortality improvement rates. We...

We explain stock mispricing linked to long-term expectations of earnings growth in terms of managerial manipulation in high-growth conglomerates. Manipulation does not affect analysts’ forecasts of conglomerate earnings, which are more accurate relative to pseudo-conglomerates. The combined...