market uncertainty and volatility of the investment instruments. Thus, the prediction of the uncertainty and volatilities of … to identify the best fit model that can predict the volatility of return of Bitcoin, which is in high demand as an … the residuals of the average equation model selected have ARCH effect. Volatility of Bitcoin return series after detection …

improved ex-post volatility measurements but has also inspired research into their potential value as an informa-tion source … for longer horizon volatility forecasts. In this paper we explore the forecasting value of these high fre-quency series in … conjunction with a variety of volatility models for returns on the Standard & Poor's 100 stock index. We consider two so …

provided between frequentist and Bayesian estimation. No significant difference is found between the qualities of the forecasts …

forecasting the volatility of equity prices, using high-frequency data from 2000 to 2016. We consider the SPY and 20 stocks that …, 60 and 300 seconds), forecast horizons (1, 5, 22 and 66 days) and the use of standard and robust-to-noise volatility and …-time forecasts than the HAR-RV model, although no single extended model dominates. In general, standard volatility measures at the …

Forecasting-volatility models typically rely on either daily or high frequency (HF) data and the choice between these … two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer of many … forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the assumptions of jumping …

Forecasting volatility models typically rely on either daily or high frequency (HF) data and the choice between these … two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer from … these two family forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the …

The contributions of error distributions have been ignored while modeling stock market volatility in Nigeria and … studies have shown that the application of appropriate error distribution in volatility model enhances efficiency of the model … asymmetric volatility models each in Normal, Student's-t and generalized error distributions with the view to selecting the best …

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 …

foreign exchange markets. -- Random Lognormal cascades ; GMM estimation ; best linear forecasting ; volatility of financial … Generalized Method of Moments (GMM) estimation procedure to cope with the documented difficulties of previous methodologies. We … by estimating the intermittency parameter and forecasting of volatility for a sample of financial data from stock and …