It is difficult to predict stock market returns but relatively easy to predict market volatility. But volatility … produces a formula in which returns become a function of volatility and therefore become somewhat more predictable. We show … strategy also smooths out volatility variation over time, reduces the kurtosis of daily returns, reduces maximum drawdown, and …

than 30% of SP500 securities can have percentage change in volatility of more than 10% as a result of noise filtering …, variances (diagonal elements of the covariance matrix - squares of volatility) contain noise as well. Our noise …

This study explores the stylized facts, volatility clustering, other highly irregular behaviour, and risk measures of … there was confirmed existence of volatility clusters when high volatility periods are followed by low volatility periods … expect in the worst case scenario. Our results confirm the existence of predictability, volatility clustering, and …

macro fundamentals, utilising methods that account for parameter uncertainty and stochastic volatility. We show that …

. Accordingly, investors often want to minimize downside volatility as a part of their portfolio planning. Investors already have … several tools to measure downside volatility, including the lower partial moment and the maximum drawdown. The performance … Index is a volatility measure that only captures continuous downside movements in share price, and ignores upside volatility …