Results 91 to 100 of about 291,653 (252)

Modelling time-varying volatility using GARCH models: evidence from the Indian stock market [version 2; peer review: 2 approved]

F1000Research, 2022
Background: In this study, we examined the volatility of the Indian stock market from 2008 to 2021. Owing to the financial crisis, volatility forecasting of the Indian stock market has become crucial for economic and financial analysts.
Tarunpreet Kaur, Deepa Bisht, Farman Ali, Pradeep Suri   +3 more
doaj  

On the Optimal Prediction of Extreme Events in Heavy‐Tailed Time Series With Applications to Solar Flare Forecasting

Journal of Time Series Analysis, EarlyView.
ABSTRACT The prediction of extreme events in time series is a fundamental problem arising in many financial, scientific, engineering, and other applications. We begin by establishing a general Neyman–Pearson‐type characterization of optimal extreme event predictors in terms of density ratios.
Victor Verma, Stilian Stoev, Yang Chen
wiley   +1 more source

Theoretical Results on FIEGARCH Processes [PDF]

arXiv, 2012
Here we present a theoretical study on the main properties of Fractionally Integrated Exponential Generalized Autoregressive Conditional Heteroskedastic (FIEGARCH) processes. We analyze the conditions for the existence, the invertibility, the stationarity and the ergodicity of these processes.
arxiv  

Testing for Threshold Effects in the Presence of Heteroskedasticity and Measurement Error With an Application to Italian Strikes

Oxford Bulletin of Economics and Statistics, EarlyView.
Abstract We address the issue of testing for threshold nonlinearity in the conditional mean in the presence of conditional heteroskedasticity. We propose a supremum Lagrange multiplier approach to test a linear ARMA‐GARCH model versus a TARMA‐GARCH model.
Francesco Angelini, Massimiliano Castellani, Simone Giannerini, Greta Goracci   +3 more
wiley   +1 more source

Artificial Neural Network and Time Series Modeling Based Approach to Forecasting the Exchange Rate in a Multivariate Framework [PDF]

Journal of Insurance and Financial Management, Vol. 1, Issue 5, PP. 92-123, 2016, 2016
Any discussion on exchange rate movements and forecasting should include explanatory variables from both the current account and the capital account of the balance of payments. In this paper, we include such factors to forecast the value of the Indian rupee vis a vis the US Dollar. Further, factors reflecting political instability and lack of mechanism
arxiv  

Gravity in Transition

Review of International Economics, EarlyView.
ABSTRACT We propose a reduced‐form transitional gravity model and an accompanying flexible reduced‐form estimation approach. The Lucas–Prescott adjustment model is extended to allow for lag‐interval‐varying depreciation‐cum‐adjustment‐cost of bilateral trade capacities.
James E. Anderson, Yoto V. Yotov
wiley   +1 more source

Czech Stock Market Analysis

Austrian Journal of Statistics, 2016
The analysis of relative returns of selected stocks at Prague Stock Exchange has been performed. As a rule, the kurtosis of the return distribution was greater than that of the standard normal distribution.
Jiří Trešl, Dagmar Blatná
doaj   +1 more source

Modelling Economic Policy Uncertainty—Examining the Effects of Oil Prices, Global and Domestic Economic Policy Uncertainty on Firm Stability in Nigeria

African Development Review, Volume 37, Issue 2, June 2025.
ABSTRACT The article explored the effects of economic policy uncertainty (EPU) on firm stability in Nigeria. The article makes three contributions to the literature. First, the article examined the impact of global EPU on firm stability. Second, it examined the effects of domestic EPU on firm stability, given the vulnerable nature of the Nigerian ...
Olajide O. Oyadeyi
wiley   +1 more source

Study About the Minimum Value at Risk of Stock Index Futures Hedging Applying Exponentially Weighted Moving Average - Generalized Autoregressive Conditional Heteroskedasticity Model

International Journal of Economics and Financial Issues, 2017
What investors often wish to insure is that the maximum possible loss of their portfolios falling below a certain value. Namely, the maximum possible loss that a portfolio will lose under normal market fluctuations, with a given confidence level, over a ...
Rong Xu, Xingye Li
doaj   +4 more sources

Forecasting gains by using extreme value theory with realised GARCH filter

IIMB Management Review, 2021
Early empirical evidence suggests that the realised generalised autoregressive conditional heteroskedasticity (GARCH) model provides significant forecasting gains over the standard GARCH models in volatility forecasting.
Samit Paul, Prateek Sharma
doaj