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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.
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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.

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A Copula-Based Autoregressive Conditional Dependence Model of International Stock Markets

TL;DR: In this article, the authors investigated the level and development of cross-country stock market dependence using daily returns on stock indices, and found strong evidence that the conditional dependence between pairs of each of these markets varies over time.
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The impact of COVID-19 shocks on the volatility of stock markets in technologically advanced countries

TL;DR: In this article, the authors examined the volatility of China and the most advanced countries of the world stock markets due to the pandemic of COVID-19 using the TGARCH model.
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Price thresholds, price volatility, and the private costs of investment in a developing country grain market

TL;DR: In this paper, empirical evidence regarding the presence of price thresholds and price volatility in an African maize market was reported. But, the authors did not consider the effect of price volatility on the price of maize.
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Short selling constraints and stock returns volatility: empirical evidence from the German stock market

TL;DR: In this paper, the impact of short selling restrictions on stock returns volatility was investigated and it was found that the financial crisis was accompanied by an increase in volatility persistence and that this effect was particularly pronounced for those stocks that were subject to short selling constraints.
References
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Journal ArticleDOI

Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation

Robert F. Engle
- 01 Jul 1982 - 
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

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

Daniel B. Nelson
- 01 Mar 1991 - 
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.
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