Many finance questions require a full characterization of the distribution of returns. We propose a bivariate model of returns and realized volatility (RV), and explore which features of that time-series model contribute to superior density forecasts over horizons of 1 to 60 days out of sample....

The paper undertakes a non-parametric analysis of the very high frequency movements in stock market volatility using very finely sampled data on the Samp;P VIX index compiled by the CBOE. The data suggest that stock market volatility is best described as a pure jump process without a continuous...

Stock markets employ specialized traders, market-makers, designed to provide liquidity and volume to the market by constantly supplying both supply and demand. In this paper, we demonstrate a novel method for modeling the market as a dynamic system and a reinforcement learning algorithm that...

We develop a portfolio risk model that uses high-frequency data to forecast the loss surface, which is the set of loss distributions at future time horizons. Our model uses a fully automated, semi-parametric fitting procedure that has its basis in extreme value statistics. We take account of...

Previous risk management in the venture capital industry has focused mainly on qualitative risk management, such as team selection and due diligence. As investment volume has increased during the past decade, and as venture capital becomes more important as an asset class for institutional...

Time reversal invariance can be sumarised as follows: no difference can be measured if a sequence of events is run forward or backward in time. Because price time series are dominated by a randomness that hides possible structures and orders, the existence of time reversal invariance requires...

Motivated by the implications from a stylized self-contained general equilibrium model incorporating the effects of time-varying economic uncertainty, we show that the difference between implied and realized variation, or the variance risk premium, is able to explain a non-trivial fraction of...

The connections between stock market volatility and returns are studied within the context of a general equilibrium framework. The framework rules out it a priori any purely statistical relationship between volatility and returns by imposing uncorrelated innovations. The main model generates a...

We examine tests for jumps based on recent asymptotic results; we interpret the tests as Hausman-type tests. Monte Carlo evidence suggests that the daily ratio z-statistic has appropriate size, good power, and good jump detection capabilities revealed by the confusion matrix comprised of jump...