Using volatility estimation as the underlying commonality, this thesis traverses the statistical problem of robust … robust scale estimators to benchmark a non-parametric volatility estimation procedure, which not only uses techniques which … are particularly suited to observed financial returns, but also addresses the problem of bias in any robust volatility …

This paper explores the volatility forecasting implications of a model in which the friction in high-frequency prices … is related to the true underlying volatility. The contribution of this paper is to propose a framework under which the … realized variance may improve volatility forecasting if the noise variance is related to the true return volatility. The …

of volatility in finance for portfolio allocation, derivative pricing and risk management. The method has a two … average realized volatility processes can achieve a convergence rate close to OP(n−4/9) , which is better than the convergence … based on average realized volatility processes indeed performs better than that based on the price processes. Empirically …

return and its volatility. Although this characteristic of stock returns is well acknowledged, most studies about it are … stochastic volatility context and for high frequency data. The consistency and limit distribution of the estimators are derived …, e.g. volatility of volatility …

value robust volatility estimator with respect to the standard robust volatility estimator as proposed in the paper by … Muneer & Maheswaran (2018b). We show that the robust volatility ratio is unbiased both in the population as well as in finite … samples. We empirically test the robust volatility ratio on 9 global stock indices from America, Asia Pacific and EMEA markets …

We compare more than 1000 different volatility models in terms of their fit to the historical ISE-100 Index data and … for modeling the ISE-100 return volatility. The t-distribution seems to characterize the distribution of the heavy tailed … model to the historical ISE-100 return data indicates that the return volatility reacts to bad news 24% more than they react …