Results 21 to 30 of about 2,269 (199)
International Review of Finance, Volume 22, Issue 3, Page 540-550, September 2022., 2022 Abstract We examine the forecasting power of a daily newspaper‐based index of uncertainty associated with infectious diseases (EMVID) for real estate investment trusts (REITs) realized market variance of the United States (US) via the heterogeneous autoregressive realized volatility (HAR‐RV) model.
Matteo Bonato +3 more
wiley +1 more source
Nonlinear Volatility Risk Prediction Algorithm of Financial Data Based on Improved Deep Learning
Discrete Dynamics in Nature and Society, Volume 2022, Issue 1, 2022., 2022 With the gradual integration of global economy and finance, the financial market presents many complex financial phenomena. To increase the prediction accuracy of financial data, a new nonlinear volatility risk prediction algorithm is proposed based on the improved deep learning algorithm.
Wangsong Xie, Stefan Cristian Gherghina
wiley +1 more source
[Retracted] Prediction of High‐Frequency Economic Data Based on Stochastic Fluctuation Model
Security and Communication Networks, Volume 2022, Issue 1, 2022., 2022 In order to improve the effect of economic high‐frequency data analysis, this paper combines the stochastic fluctuation model to carry out the forecast analysis of economic high‐frequency data. Moreover, this paper uses the spider web model for data processing and makes a preliminary judgment on the extent to which futures/stock prices lead the spot ...
Xiaoyang Zhang +3 more
wiley +1 more source
Does Indian Commodity Futures Markets Exhibit Price Discovery? An Empirical Analysis
Discrete Dynamics in Nature and Society, Volume 2022, Issue 1, 2022., 2022 Price discovery function analyses the dynamics of futures and spot price behavior in an asset’s intertemporal dimensions. The present study examines the price discovery function of the bullion, metal, and energy commodity futures and spot prices through the Granger causality and Johansen–Juselius cointegration tests.
Upananda Pani +5 more
wiley +1 more source
DEVELOPING THE HYBRID ARIMA- FIGARCH MODEL FOR TIME SERIES ANALYSIS
FUDMA JOURNAL OF SCIENCES, 2023 This study takes into account the newly developed hybrid ARIMA-FIGARCH. We use the daily price index of the S&P 500. The data employed for this study was secondary in nature for all the variables and was obtained from the publications of the Central Bank of Nigeria Bulletin, the National Bureau of Statistics, and the World Bank Statistics Database,
Musa Usman Bawa +4 more
openaire +1 more source
International Journal of Finance &Economics, Volume 26, Issue 3, Page 4441-4461, July 2021., 2021 Abstract This study examines the impact of investors’ buy and sell trades on Korean stock market volatility across two crisis events, the Asian crisis of 1997 and the 2008 global financial crash. We investigate the trading behaviour of domestic vs. foreign and institutional vs. individual investors. Our results suggest that the buy and sell trades have
Guglielmo Maria Caporale +3 more
wiley +1 more source
Estimating the volatility of asset pricing factors
Journal of Forecasting, Volume 40, Issue 2, Page 269-278, March 2021., 2021 Abstract Models based on factors such as size or value are ubiquitous in asset pricing. Therefore, portfolio allocation and risk management require estimates of the volatility of these factors. While realized volatility has become a standard tool for liquid assets, this measure is difficult to obtain for asset pricing factors such as size and value ...
Janis Becker, Christian Leschinski
wiley +1 more source
Long Memory and Volatility Clustering: is the empirical evidence consistent across stock markets? [PDF]
, 1994 Long memory and volatility clustering are two stylized facts frequently related to financial markets. Traditionally, these phenomena have been studied based on conditionally heteroscedastic models like ARCH, GARCH, IGARCH and FIGARCH, inter alia.
Bentes, Sonia R. +2 more
core +5 more sources
Complexity, Volume 2021, Issue 1, 2021., 2021 Carbon price fluctuation is affected by both internal market mechanisms and the heterogeneous environment. Moreover, it is a complex dynamic evolution process. This paper focuses on carbon price fluctuation trend prediction. In order to promote the accuracy of the forecasting model, this paper proposes the idea of integrating network topology ...
Hua Xu +2 more
wiley +1 more source
Block Trading Based Volatility Forecasting: An Application of VACD-FIGARCH Model [PDF]
The Journal of Asian Finance, Economics and Business, 2020 The purpose of this study is to construct the ACD model for the block trading volume duration. The ACD model based on the block trading volume duration is referred to as Volume ACD (VACD) in this study. By integrating with GARCH-type models, the VACD based GARCH type models, which include VACD-GARCH, VACD-IGARCH and VACD-FIGARCH models, are set up ...
Teng-Tsai TU, Chih-Wei LIAO
openaire +1 more source