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
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Asian Flu or Wall Street virus? Tech and non-tech spillovers in the United States and Asia
TL;DR: Using TGARCH models, this paper found that U.S. stock markets have been the major source of price and volatility spillovers to stock markets in the Asia-Pacific region during three different period of time.
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Geometric Ergodicity of a Class of Markov Chains with Applications to Time Series Models
TL;DR: In this article, the authors give general conditions for a general non-linear Markov model to be geometrically ergodic (which implies beta-mixing of the stationary solution) and existence of certain moments.
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Investigating the sources of Black’s leverage effect in oil and gas stocks
TL;DR: In this article, the authors investigated the authenticity of the Black's leverage effect hypothesis and the relationship between negative stock returns and the financial leverage of the UK oil and gas stocks from 2004 to 2015.
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Time-frequency domain analysis of investor fear and expectations in stock markets of BRIC economies.
Peterson Owusu Junior,Anokye M. Adam,Emmanuel Asafo-Adjei,Ebenezer N. K. Boateng,Zulaiha Hamidu,Eric Awotwe +5 more
TL;DR: In this article, the authors investigated the relationship between the BRIC stock index and its constituents and the US volatility index (VIX) as a measure of investor uncertainty and fear and stock returns of BRIC economies.
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Conditional Value-at-Risk: Semiparametric estimation and inference
Chuan Sheng Wang,Zhibiao Zhao +1 more
TL;DR: A user-friendly bootstrap approach is introduced to facilitate non-expert practitioners to perform confidence interval construction forCVaR and establish a functional central limit theorem for CVaR process indexed by the confidence level to study the conditional expected shortfall.
References
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Journal ArticleDOI
Handbook of Mathematical Functions
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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.