predicting monthly US excess stock returns and volatility over the period 1980-2005. Factor-augmented predictive regression … superior market timing ability and volatility timing ability, while a mean-variance investor would be willing to pay an annual …

periods. Returns in this framework display time varying volatility, skewness and kurtosis. We provide a detailed account of … of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which forecasting … errors in realized volatility are substantive. Even though returns standardized by ex post quadratic variation measures are …

Most multivariate variance or volatility models suffer from a common problem, the “curse of dimensionality”. For this … stochastic volatility models. The empirical analysis on stock returns on the US market shows that 1% and 5 % Value …

the daily returns. To give a new view of the question whether time series volatility models or implied volatility have … on some high frequency basis has spurred the research in the field of volatility modeling and forecasting into new … directions. First, the realized variance is a much better estimate of the latent volatility than the sum of the weighted daily …

We investigate the predictability of both volatility and volume for a large sample of Japanese stocks. The particular … emphasis of this paper is on assessing the performance of long memory time series models in comparison to their short … practically always improves upon the na?ve forecast provided by historical volatility. As a somewhat surprising result, we also …

Multi-fractal processes have recently been proposed as a new formalism for modelling the time series of returns in … Bayesian forecasting of volatility. However, applicability of MLE is restricted to cases with a discrete distribution of … volatility components. From a practical point of view, ML also becomes computationally unfeasible for large numbers of components …

We investigate the predictability of both volatility and volume for a large sample of Japanese stocks. The particular … emphasis of this paper is on assessing the performance of long memory time series models in comparison to their short … practically always improves upon the na?ve forecast provided by historical volatility. As a somewhat surprising result, we also …

Multifractal processes have recently been proposed as a new formalism for modelling the time series of returns in … forecasting of volatility. However, applicability of MLE is restricted to cases with a discrete distribution of volatility … which in principle is applicable for any continuous distribution with any number of volatility components. Monte Carlo …

mothers and fathers make investments in their children. We find that time investments, educational investments, and … education subsidies can reduce inequality, due to an estimated dynamic complementarity between time investments and education …