Journal ArticleDOI
Threshold heteroskedastic models
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TLDR
In this paper, the conditional standard deviation is a piecewise linear function of past values of the white noise, which allows different reactions of the volatility to different signs of the lagged errors.About:
This article is published in Journal of Economic Dynamics and Control.The article was published on 1994-09-01. It has received 2125 citations till now. The article focuses on the topics: Autoregressive conditional heteroskedasticity & Heteroscedasticity.read more
Citations
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Semiparametric GARCH via Bayesian Model Averaging
Wilson Ye Chen,Richard Gerlach +1 more
TL;DR: In this paper, a model capable of providing consistently accurate volatility estimates should not make rigid assumptions on how prices will change over time, as the dynamic structure of financial markets is subject to dramatic change.
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Information bias and its spillover effect on return volatility: A study on stock markets in the Asia-Pacific region
TL;DR: In this article, the authors investigated the evidence of information bias and its spillover effects on the stock market returns of the Asia Pacific region and found that negative innovations had a greater impact on the conditional volatility of the market returns than positive innovations.
The Use of ARCH and GARCH Models for Estimating and Forecasting Volatility
Bahadtin Rüzgar,İsmet Kale +1 more
TL;DR: In this paper, the authors present a model of an ARCH model for volatilite degerlemesi yapabilmektedir carpik-t ve Student-t dagilimlarinin kullanilmasi modelin======¯¯¯¯veriye daha uyumlu olmasini saglamaktadir Sonuc olarak, belirli bir model veya dagilIMin kllanilmalmasinin volatileite tahmininde acik bir iyilesme
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The dynamic contagion of the global financial crisis into Japanese markets
TL;DR: This paper investigated the risk contagion channel of the global financial crisis into Japan using daily data on bond risk premiums for the financial and manufacturing industries from July 18, 2006 to May 25, 2010.
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A GARCH-VaR Investigation on the Brazilian Sectoral Stock Indices
TL;DR: In this article, the authors explored operational risk in Brazil by considering different sectoral indices of the Brazilian economy and the GACH Value-at-Risk (GARCH-VaR) estimation approach.
References
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Journal ArticleDOI
Handbook of Mathematical Functions
Journal ArticleDOI
Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation
TL;DR: In this article, a new class of stochastic processes called autoregressive conditional heteroscedastic (ARCH) processes are introduced, which are mean zero, serially uncorrelated processes with nonconstant variances conditional on the past, but constant unconditional variances.
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Generalized autoregressive conditional heteroskedasticity
Tim Bollerslev,Tim Bollerslev +1 more
TL;DR: In this paper, a natural generalization of the ARCH (Autoregressive Conditional Heteroskedastic) process introduced in 1982 to allow for past conditional variances in the current conditional variance equation is proposed.
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Conditional heteroskedasticity in asset returns: a new approach
TL;DR: In this article, an exponential ARCH model is proposed to study volatility changes and the risk premium on the CRSP Value-Weighted Market Index from 1962 to 1987, which is an improvement over the widely-used GARCH model.
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On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks
TL;DR: In this article, a modified GARCH-M model was used to find a negative relation between conditional expected monthly return and conditional variance of monthly return, using seasonal patterns in volatility and nominal interest rates to predict conditional variance.