Showing 1 - 10 of 51,328
forecasting financial volatility. We use the auto-covariances of log increments of the multi-fractal process in order to estimate … ?scaling? approach. Our empirical estimates are used in out-of-sample forecasting of volatility for a number of important …
Persistent link: https://www.econbiz.de/10010295056
forecasting financial volatility. We use the auto-covariances of log increments of the multi-fractal process in order to estimate … ?scaling? approach. Our empirical estimates are used in out-of-sample forecasting of volatility for a number of important …
Persistent link: https://www.econbiz.de/10005082872
Multi-fractal processes have been proposed as a new formalism for modelling the time series of returns in finance. The major attraction of these processes is their capability of generating various degrees of long-memory in different powers of returns - a feature that has been found to...
Persistent link: https://www.econbiz.de/10005706741
Multi-fractal processes have been proposed as a new formalism for modeling the time series of returns in finance. The major attraction of these processes is their capability of generating various degrees of long-memory in different powers of returns - a feature that has been found to...
Persistent link: https://www.econbiz.de/10004968280
Multi-fractal processes have been proposed as a new formalism for modeling the time series of returns in finance. The major attraction of these processes is their capability of generating various degrees of long-memory in different powers of returns - a feature that has been found to...
Persistent link: https://www.econbiz.de/10004968323
Bayesian forecasting of volatility. However, applicability of MLE is restricted to cases with a discrete distribution of … leads to gains in forecasting accuracy for some time series. …
Persistent link: https://www.econbiz.de/10010295106
forecasting of volatility. However, applicability of MLE is restricted to cases with a discrete distribution of volatility … leads to gains in forecasting accuracy for some time series. …
Persistent link: https://www.econbiz.de/10010295151
Bayesian forecasting of volatility. However, applicability of MLE is restricted to cases with a discrete distribution of … leads to gains in forecasting accuracy for some time series. …
Persistent link: https://www.econbiz.de/10005082869
forecasting of volatility. However, applicability of MLE is restricted to cases with a discrete distribution of volatility … leads to gains in forecasting accuracy for some time series. …
Persistent link: https://www.econbiz.de/10005082887
A practice that has become widespread and widely endorsed is that of evaluating forecasts of financial variability obtained from discrete time models by comparing them with high-frequency ex post estimates (e.g. realised volatility) based on continuous time theory. In explanatory financial...
Persistent link: https://www.econbiz.de/10010332964