Results 41 to 50 of about 4,202 (205)

Robust CDF‐Filtering of a Location Parameter

Journal of Time Series Analysis, EarlyView.
ABSTRACT This paper introduces a novel framework for designing robust filters associated with signal plus noise models having symmetric observation density. The filters are obtained by a recursion where the innovation term is a transform of the cumulative distribution function of the residuals.
Leopoldo Catania, Andrew C. Harvey, Alessandra Luati   +2 more
wiley   +1 more source

Financial Time Series Uncertainty: A Review of Probabilistic AI Applications

Journal of Economic Surveys, Volume 40, Issue 2, Page 915-953, April 2026.
ABSTRACT Probabilistic machine learning models offer a distinct advantage over traditional deterministic approaches by quantifying both epistemic uncertainty (stemming from limited data or model knowledge) and aleatoric uncertainty (due to inherent randomness in the data), along with full distributional forecasts.
Sivert Eggen, Tord Johan Espe, Kristoffer Grude, Morten Risstad, Rickard Sandberg   +4 more
wiley   +1 more source

A new method for estimating liquidity and stock returns in Indian stock market

China Accounting and Finance Review
This study aims to explore the impact of systematic liquidity risk on the averaged cross-sectional equity return of the Indian equity market. It also examines the effects of illiquidity and decomposed illiquidity on the conditional volatility of the ...
Tapas Kumar Sethy, Naliniprava Tripathy
doaj   +1 more source

The Monetary Policy–Commodities Nexus: A Survey

Journal of Economic Surveys, Volume 40, Issue 2, Page 1050-1082, April 2026.
ABSTRACT This survey synthesizes evidence on the bidirectional links between commodity markets and monetary policy. On the commodities‐to‐policy side, we review how shocks to energy, food, and metals pass through to inflation, inflation expectations, economic activity, and financial stability in state‐dependent ways that vary by shock type, exposure ...
Martin T. Bohl, Niklas Humann, Pierre L. Siklos   +2 more
wiley   +1 more source

Information‐Driven Modeling of Energy Markets: An Unbalanced Wasserstein Barycenter Approach

Applied Stochastic Models in Business and Industry, Volume 42, Issue 2, March/April 2026.
ABSTRACT A novel methodology is proposed for jointly modeling the price dynamics of natural gas and electricity by integrating graph‐based Machine Learning and optimal transport theory. The framework combines visibility graph embeddings with the Wasserstein barycenter to uncover latent structures and asymmetric dependencies between the two ...
Carlo Mari, Emiliano Mari, Cristiano Baldassari   +2 more
wiley   +1 more source

Volatility spillover between stock market and currency market of Pakistan in the presence of structural breaks

Business Review, 2022
This study examines the volatility transmission between the currency market and the stock market of Pakistan in the presence of structural breaks. For this purpose, daily data from the stock market and currency market is analyzed.
Muhammad Jamil , Hifsa Mobeen
doaj   +1 more source

EGARCH-RR: realized ranges explaining EGARCH volatilities [PDF]

, 2015
The purpose of this paper is to investigate whether the inclusion of a realized measure of volatility as external regressor on the GARCH and EGARCH variance equation would result in more accurate ts.
Mendes, Beatriz Vaz de Melo, Accioly, Victor Bello   +1 more
core  

Markov regime-switching Beta-t-EGARCH

, 2017
We suggest a Markov regime-switching (MS) Beta-t-EGARCH (exponential generalized autoregressive conditional heteroscedasticity) model for U.S. stock returns.
Ho, Han Chiang, Han-Chiang Ho, Blazsek, Szabolcs, Szabolcs Blazsek   +3 more
core   +1 more source

Estimating Volatility and Investment Risk: An Empirical Case Study for NIFTY MIDCAP 50 Index of National Stock Exchange (NSE) in India [PDF]

Ovidius University Annals: Economic Sciences Series, 2021
This study evaluates performance of Indian index considering NIFTY MIDCAP 50 index daily series returns. Autoregressive model EGARCH forecasts the volatility predictability and empirically analyze volatility pattern considering daily returns from NIFTY ...
Ramona Birau, Jatin Trivedi, Cristi Spulbar   +2 more
doaj  

المقارنة بين نماذج EGARCH والشبكات العصبية الاصطناعية في قياس أثر المخاطر المنتظمة على المؤشر العام لسوق الأوراق المالية في مصر [PDF]

The Egyptian Statistical Journal, 2014
The main objective of this paper is to make a comparison between an EGARCH models and artificial neural networks approach in measuring the impact of systematic risk on the stock market index in Egypt.
ماهر احمد علي
doaj   +1 more source