In recent years, authors have focused on modeling and forecasting volatility in financial series it is crucial for the characterization of markets, portfolio optimization and asset valuation. One of the most used methods to forecast market volatility is the linear regression. Nonetheless, the errors in prediction using this approach are often quite high. Hence, continued research is conducted t...

We comprehensively examine the effects of stock return volatility on firms’ financial and investment decisions. Consistent with theories of investment with financing frictions, firms with high volatility actively reduce their leverage, cut investment, increase cash holding, cut non-cash current assets such as inventories and account receivables, and cut dividend. The effects of volatility are s...

We study the dynamic relation between daily stock returns and innovations in option-derived implied volatilities. By simultaneously analyzing innovations in index-level and firm-level implied volatilities, we distinguish between innovations in systematic and idiosyncratic volatility in an effort to better understand the asymmetric volatility phenomenon. Our results indicate that the relation be...

Volatility derivatives are becoming increasingly popular as means for hedging unexpected changes in volatility. Although pricing volatility derivatives demands extreme care in modeling the underlying volatility process, not much attention has been devoted to the complete specification of the autonomous process that volatility follows in continuous time. Despite the fact that jumps are widely co...

We implement an estimator of the model-free implied volatility derived by Britten-Jones and Neuberger (2000) and investigate its information content in the S&P 500 index options. In contrast to the commonly used Black-Scholes implied volatility, the model-free implied volatility is not based on any specific option pricing model and thus provides a direct test of the informational efficiency of ...

This paper introduces a new class of stochastic volatility models which allows for stochastic volatility of volatility. Such models are given by volatility modulated non–Gaussian Ornstein Uhlenbeck processes. We study the probabilistic properties of such models both under the physical and under the risk neutral probability measure, where we focus in particular on the role of the volatility of v...

This study examines the performance of the S&P 100 implied volatility as a forecast of future stock market volatility. The results indicate that the implied volatility is an upward biased forecast, but also that it contains relevant information regarding future volatility. The implied volatility dominates the historical volatility rate in terms of ex ante forecasting power, and its forecast err...

In their 2014 article in the British Journal of Political Science, Eleanor Neff Powell and Joshua A. Tucker examine the determinants of party system volatility in post-communist Europe. Their central conclusion is that replacement volatility – volatility caused by new party entry and old party exit – is driven by long-term economic performance. This article shows that this conclusion is based e...

Volatility in equity markets is asymmetric: contemporaneous return and conditional return volatility are negatively correlated. In this article I develop an asymmetric volatility model where dividend growth and dividend volatility are the two state variables of the economy. The model allows both the leverage effect and the volatility feedback effect, the two popular explanations of asymmetry. T...