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 … of returns. Explicitly modeling this volatility risk is fundamental. We propose a dually asymmetric realized volatility …

Any measure of unobserved inflation uncertainty relies on specific assumptions which are most likely not fulfilled … forecast models, and volatility models. We show that all measures are driven by a common component which constitutes an … indicator for inflation uncertainty. Moreover, the idiosyncratic component of survey disagreement contains systematic …

heteroskedastic. After presenting the model, we propose a multi-step estimation technique which combines asymptotic principal … results in order to assess the finite sample properties of the estimation technique. Finally, we carry out two empirical … applications respectively on macroeconomic series, with a particular focus on different measures of inflation, and on financial …

and Karanasos (2008) to examine the intertemporal relationship between the uncertainties of inflation and output growth in … the US. We find that inflation uncertainty effects output variability positively, while output variability has a negative … effect on inflation uncertainty. …

We examine the performance of volatility models that incorporate features such as long (short) memory, regime …-t). Second, we perform a comprehensive panel forecasting analysis of the MSM models as well as other competing volatility models … (GMM) estimation are both suitable for MSM-t models, (ii) empirical panel forecasts of MSM-t models show an improvement …

financial forecasting. This paper deals with the application of SVR in volatility forecasting. Based on a recurrent SVR, a GARCH … to forecast financial markets volatility. The real data in this study uses British Pound-US Dollar (GBP) daily exchange … examined to the free parameters. Keywords: recurrent support vector regression ; GARCH model ; volatility forecasting …

Market expectations of future return volatility play a crucial role in finance; so too does our understanding of the … informativeness of volatility forecasts produced by ARCH models versus the volatility forecasts derived from option prices and in … improving volatility forecasts produced by ARCH and option models and combinations of models. Daily and monthly data are …

describe the most typical features of capital markets like volatility clustering, excess kurtosis and fat tails. As empirical … evidence shows asymmetry is also a prominent feature of stock market returns volatility. The reaction of risk if stock returns …