We develop and implement a new method for maximum likelihood estimation in closed-form of stochastic volatility models … unobservable volatility state, to an approximate likelihood procedure where the volatility state is replaced by the implied … volatility of a short dated at-the-money option. We find that the approximation results in a negligible loss of accuracy. We …

Volatility tests are an alternative to regression tests for evaluating the joint null hypothesis of market efficiency … taken to be. By considering tests based on conditional volatility bounds, we show that if the alternative is that one could … conditional volatility tests.If the application is to spot and forward markets, then the most powerful conditional volatility test …

We develop new procedures for maximum likelihood estimation of affine term structure models with spanned or unspanned … stochastic volatility. Our approach uses linear regression to reduce the dimension of the numerical optimization problem yet it … produces the same estimator as maximizing the likelihood. It improves the numerical behavior of estimation by eliminating …

stock price reaction to news, and hence lowering the stock return volatility. Thus, in addition to uncertainty about … fundamentals, uncertainty about CEO quality is also a source of stock return volatility, which decreases over a CEO's tenure as the …'s prospects. Overall, uncertainty about management quality appears to be an important source of stock return volatility …

volatility over the next month, but with decreasing realized volatility. These predictability patterns are consistent with …