Results 41 to 50 of about 3,916 (205)

Quantile Correlations: Uncovering temporal dependencies in financial time series [PDF]

, 2015
We conduct an empirical study using the quantile-based correlation function to uncover the temporal dependencies in financial time series. The study uses intraday data for the S\&P 500 stocks from the New York Stock Exchange.
Dette, Holger, Guhr, Thomas, Schmitt, Thilo A., Schäfer, Rudi   +3 more
core   +2 more sources

Shock‐Triggered Asymmetric Response Stochastic Volatility

Journal of Forecasting, Volume 45, Issue 1, Page 217-240, January 2026.
ABSTRACT We propose a novel asymmetric stochastic volatility model (STAR‐SV) in which the leverage parameter adjusts to the magnitude of past shocks. This flexible specification captures both the leverage effects and their propagation more effectively than standard asymmetric volatility models.
J. Miguel Marin, Helena Veiga
wiley   +1 more source

An Empirical Evaluation of GARCH Models in Value-at-Risk Estimation: Evidence from the Macedonian Stock Exchange

Business Systems Research, 2013
Background: In light of the latest global financial crisis and the ongoing sovereign debt crisis, accurate measuring of market losses has become a very current issue. One of the most popular risk measures is Value-at-Risk (VaR). Objectives: Our paper has
Bucevska Vesna
doaj   +1 more source

Study on Financial Market Risk Measurement Based on GJR-GARCH and FHS [PDF]

Science Journal of Applied Mathematics and Statistics, 2015
In this paper, we establish GJR-GARCH models to extract the residuals of logarithmic returns of one kind of Chinese stock index--- Shanghai Composite Index and the series of independent and identically distribution standardized residuals is formed from the filtered model residuals and conditional volatilities from the return series with an GJR-GARCH ...
openaire   +1 more source

Unveiling Complex Seasonality in Stock Price Forecasting Using a Seasonal‐Adjusted Hybrid Machine Learning Approach

Applied Computational Intelligence and Soft Computing, Volume 2026, Issue 1, 2026.
In emerging financial markets, stock price forecasting is challenged by nonstationarity, irregular trading calendars, and evolving structural dynamics that limit the effectiveness of conventional linear models. This study develops and evaluates a seasonal‐adjusted hybrid machine learning framework to forecast the daily closing stock prices of Square ...
K. M. Zahidul Islam, Amrin Binte Ahmed, Adisha Dulmini, Dulsaba Azmain, Md. Mahin Uddin Qureshi, Meherun Ahmed, Mst. Nilufar Yasmin, Muhammad Khairul Alam, Rumana Rois, Zhaocai Wang   +9 more
wiley   +1 more source

Examining Oil Prices for Chaos, Entropy, Fractionality and Complexity, and Modeling the Impacts of Economic Policy Uncertainty and Geopolitical Risks: GARCH–MIDAS–LSTM Approach

International Journal of Energy Research, Volume 2026, Issue 1, 2026.
As the leading energy source, oil price volatility has crucial effects in energy markets, and geopolitical risks (GPRs) and economic policy uncertainties contribute to its volatility. Further, chaos, long‐range dependence, fractionality, and complexity significantly reduce modeling and forecast performances.
Özgür Ömer Ersin, Melike Bildirici, Rajashik Paul   +2 more
wiley   +1 more source

Comparing GARCH Models by Introducing Fuzzy Asymmetric Realized GARCH [PDF]

مدلسازی اقتصادسنجی, 2018
Estimation of conditional variance has lots of application reflecting economic, especially financial economics, social economics and political economics’ risk and volatility research.
Esmaiel Abounoori, Mohammad Amin Zabol
doaj   +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

Forecasting Malaysian gold using a hybrid of ARIMA and GJR-GARCH models

Applied Mathematical Sciences, 2015
An effective way to improve forecast accuracy is to use a hybrid model. This paper proposes a hybrid model of linear autoregressive moving average (ARIMA) and non-linear GJR-GARCH model also known as TARCH in modeling and forecasting Malaysian gold.
Ahmad, Maizah Hura, Pung, Yean Ping, Yaziz, Siti Roslindar, Miswan, Nor Hamizah   +3 more
openaire   +2 more sources

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