Journal ArticleDOI
Threshold heteroskedastic models
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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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Interest Rate Transmission and Volatility Transmission along the Yield Curve
TL;DR: In this paper, the authors estimate multivariate VECM-GARCH models, which take into account moste of the usual features of financial data (non-stationarity, cointegration, heteroskedasticity, asymmetric effects) allowing them to study interest rate transmission as well as volatility transmission along the yield curve.
Book
Democratic Processes and Financial Markets: Pricing Politics
William Bernhard,David Leblang +1 more
TL;DR: Bernhard and Leblang as mentioned in this paper examined the conditions under which democratic events, including elections, cabinet formations, and government dissolutions, affect asset markets and found that when these events have less predictable outcomes, market returns are depressed and volatility increases.
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Are Dow Jones Islamic equity indices exposed to interest rate risk
TL;DR: In this article, the Dow Jones Islamic Market indices (DJIMI) are constructed by screening out stocks that are incompatible with Islam's prohibition of interest and certain lines of business.
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Detecting Instability in the Volatility of Carbon Prices
TL;DR: In this paper, the authors investigated the presence of outliers in the volatility of carbon prices and found evidence of strong shifts mainly for the EGARCH and IV models during the time period.
Testing the Empirical Performance of Stochastic Volatility Models of the Short-Term
TL;DR: In this article, the authors introduce two-factor discrete time stochastic volatility models of the short-term inter? est rate to compare the relative performance of existing and alternative empirical spec? ifications.
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.