Results 81 to 90 of about 36,906 (198)

Forecasting the time-varying beta of UK firms: GARCH models vs Kalman filter method

, 2007
This paper forecast the weekly time-varying beta of 20 UK firms by means of four different GARCH models and the Kalman filter method. The four GARCH models applied are the bivariate GARCH, BEKK GARCH, GARCH-GJR and the GARCH-X model.
Wu, Hao, Choudhry, Taufiq
core   +1 more source

Estimation and Inference for Higher‐Order Stochastic Volatility Models With Leverage

Journal of Time Series Analysis, Volume 46, Issue 6, Page 1064-1084, November 2025.
ABSTRACT Statistical inference—estimation and testing—for stochastic volatility models is challenging and computationally expensive. This problem is compounded when leverage effects are allowed. We propose efficient, simple estimators for higher‐order stochastic volatility models with leverage [SVL(p)$$ (p) $$], based on a small number of moment ...
Md. Nazmul Ahsan, Jean‐Marie Dufour, Gabriel Rodriguez‐Rondon   +2 more
wiley   +1 more source

Spillovers Into the German Electricity Market From the Gas, Coal, and CO2 Emissions Markets

Journal of Futures Markets, Volume 45, Issue 9, Page 1253-1277, September 2025.
ABSTRACT This paper investigates the mean, volatility, skewness, and kurtosis of price spillovers from the natural gas, coal, and CO2 emissions markets into the German electricity market from 2010 to July 2023, segmented into three periods: pre‐Russo‐Ukrainian war, war‐triggered price rise, and postwar adjustment. Utilizing a flexible probability model
Filippos Ioannidis, Kyriaki Kosmidou, Panayiotis Theodossiou   +2 more
wiley   +1 more source

Extended Multivariate EGARCH Model: A Model for Zero‐Return and Negative Spillovers

Journal of Forecasting, Volume 44, Issue 4, Page 1266-1279, July 2025.
ABSTRACT This paper introduces an extended multivariate EGARCH model that overcomes the zero‐return problem and allows for negative news and volatility spillover effects, making it an attractive tool for multivariate volatility modeling. Despite limitations, such as noninvertibility and unclear asymptotic properties of the QML estimator, our Monte ...
Yongdeng Xu
wiley   +1 more source

Seize the Moments: Approximating American Option Prices in the GARCH Framework [PDF]

This paper proposes an efficient approach to compute the prices of American style options in the GARCH framework. Rubinstein's (1998) Edgeworth tree idea is combined with the analytical formulas for moments of the cumulative return under GARCH developed ...
Caroline Sasseville, Genevieve Gauthier, Jin-Chuan Duan, Jean-Guy Simonato   +3 more
core  

Risk measurement of global stock markets: a factor copula-based GJR-GARCH approach

Journal of Physics: Conference Series, 2019
AbstractFinancial crisis in 2008 caused huge loss and one of the accusations is the misprediction of risk measurement. Considering the important role the stock markets play, and the trend of globalization in economy, we propose forecasting Value at Risk of G20’s (except European Union) stock indexes in three periods, pre-crisis, during crisis and post ...
Quanrui Song, Jianxu Liu, Songsak Sriboonchitta   +2 more
openaire   +1 more source

The Volatility Forecasting of Tehran& International Stock Exchanges [PDF]

مطالعات تجربی حسابداری مالی, 2008
Stock prices are one of the most volatile economic variables and forecasting stock prices and their returns has proved very challenging, if not impossible.
H. Khaleghi Moghadam, S. Moshiri, K. Pakizeh   +2 more
doaj  

Green Hydrogen Market and Green Cryptocurrencies: A Dynamic Correlation Analysis

Commodities
The urgent need to mitigate climate change has elevated green hydrogen as a sustainable alternative to fossil fuels, while green cryptocurrencies have emerged to address the environmental concerns of traditional cryptocurrency mining.
Eder J. A. L. Pereira, Thanmillys Nadhynne de Lima da Conceição, Emanuel Cruz da Lima   +2 more
doaj   +1 more source

COMPARATIVE ANALYSIS AND RANKING OF HYBRID MACHINE LEARNING AND GARCH MODELS FOR STOCK MARKET VOLATILITY IN SADC FINANCIAL MARKETS

Prizren Social Science Journal
This study investigates the forecasting performance of machine learning models and traditional econometric volatility models in predicting daily stock price volatility across selected Southern African Development Community (SADC) markets from 02 January
Oloruntoba OYEDELE
doaj   +1 more source

Estimated Value-at-Risk Using the ARIMA-GJR-GARCH Model on BBNI Stock

Operations Research: International Conference Series
Stocks are investment instruments that are much in demand by investors as a basis in financial storage. Return and risk are the most important things in investing. Return is a complete summary of investment and the return series is easier to handle than the price series. The movement of risk of loss is obtained from stock investments with profits.
Rizki Apriva Hidayana, Herlina Napitupulu, Sukono Sukono   +2 more
openaire   +1 more source