Results 281 to 290 of about 1,459,377 (344)

Stock market volatility forecasting: Do we need high-frequency data?

International Journal of Forecasting, 2021
The general consensus in the volatility forecasting literature is that high-frequency volatility models outperform low-frequency volatility models.
Štefan Lyócsa, Péter Molnár, T. Výrost   +2 more
semanticscholar   +1 more source

Forecasting cryptocurrency volatility

International Journal of Forecasting, 2022
Abstract This paper studies the behavior of cryptocurrencies’ financial time series, of which Bitcoin is the most prominent example. The dynamics of these series are quite complex, displaying extreme observations, asymmetries, and several nonlinear characteristics that are difficult to model and forecast.
Catania L., Grassi S.
openaire   +2 more sources

Forecasting stock market volatility with regime-switching GARCH-MIDAS: The role of geopolitical risks

International Journal of Forecasting, 2023
We investigate the role of geopolitical risks (GPR) in forecasting stock market volatility in a robust autoregressive Markov-switching GARCH mixed data sampling (ARMSGARCH-MIDAS) framework that accounts for structural breaks through regime switching and ...
Mawuli Segnon, Rangan Gupta, Bernd Wilfling   +2 more
semanticscholar   +1 more source

Forecasting volatility

Statistics & Probability Letters, 2005
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Thavaneswaran, A., Appadoo, S. S., Peiris, S.   +2 more
openaire   +2 more sources

Novel volatility forecasting using deep learning-Long Short Term Memory Recurrent Neural Networks

Expert systems with applications, 2019
s The volatility is related to financial risk and its prediction accuracy is very important in portfolio optimisation. A large body of literature to-date suggests Support Vector Machines (SVM) as the “best of regression” algorithms for financial data ...
Yang Liu
semanticscholar   +1 more source

Forecasting Volatility

Financial Markets, Institutions & Instruments, 1997
This monograph puts together results from several lines of research that I have pursued over a period of years, on the general topic of volatility forecasting for option pricing applications. It is not meant to be a complete survey of the extensive literature on the subject, nor is it a definitive set of prescriptions on how to get the best volatility ...
openaire   +1 more source

COMMENTARY: Volatility Forecasting

The Journal of Trading, 2018
This paper provides a perspective on volatility forecasting. The basic idea is that a number of factors are leading to volatility having a lower baseline expected value than in prior years. These factors include lower earnings uncertainty, greater market efficiency, better market-marking, and the fact that volatility trading itself tends to reduce ...
Haim A. Mozes, John Launny Steffens
openaire   +1 more source

Harnessing jump component for crude oil volatility forecasting in the presence of extreme shocks

Journal of Empirical Finance, 2019
Oil markets are subject to extreme shocks (e.g. Iraq’s invasion of Kuwait), causing the oil market price exhibits extreme movements, called jumps (or spikes). These jumps pose challenges on oil market volatility forecasting using conventional volatility
Feng Ma, Yin Liao, Yaojie Zhang, Yang Cao   +3 more
semanticscholar   +1 more source

Machine Learning for Realised Volatility Forecasting

Social Science Research Network, 2020
This paper examines, for the first time, the performance of machine learning models in realised volatility forecasting using big data sets such as LOBSTER limit order books and news stories from ‘Dow Jones News Wires’ for 28 NASDAQ stocks over a sample ...
Eghbal Rahimikia, S. Poon
semanticscholar   +1 more source

Forecasting exchange rate volatility

Economics Letters, 2002
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +1 more source