Results 271 to 280 of about 1,459,377 (344)
Some of the next articles are maybe not open access.

Related searches:

Functional Volatility Forecasting

Journal of Forecasting, 2023
Widely used volatility forecasting methods are usually based on low‐frequency time series models. Although some of them employ high‐frequency observations, these intraday data are often summarized into low‐frequency point statistics, for example, daily ...
Ying Tan   +3 more
semanticscholar   +2 more sources

The role of news sentiment in oil futures returns and volatility forecasting: Data-decomposition based deep learning approach

Energy Economics, 2021
In this paper, we extract the qualitative information from crude oil news headlines, and develop a novel VMD-BiLSTM model with investor sentiment indicator for crude oil forecasting.
Yuze Li   +3 more
semanticscholar   +3 more sources

Automated Volatility Forecasting

Management Science
We develop an automated system to forecast volatility by leveraging more than 100 features and five machine learning algorithms. Considering the universe of S&P 100 stocks, our system results in superior out-of-sample volatility forecasts compared with ...
Sophia Zhengzi Li, Yushan Tang
semanticscholar   +2 more sources

Oil price volatility forecasting: Threshold effect from stock market volatility

Technological Forecasting and Social Change, 2022
Yan Chen, Gaoxiu Qiao, Feipeng Zhang
semanticscholar   +3 more sources

Capturing the dynamics of the China crude oil futures: Markov switching, co-movement, and volatility forecasting

Energy Economics, 2021
The launch of the China's Shanghai International Energy Exchange (INE) oil futures market in 2018 has shed new light on the role of China in international crude oil market. Understanding the dynamics of the newly arrived RMB denominated crude oil futures
Min Liu, Chien‐Chiang Lee
semanticscholar   +1 more source

Home - About - Disclaimer - Privacy