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
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Jumps in the Volatility of Financial Markets
TL;DR: In this article, a non-parametric procedure is proposed to detect discontinuities in otherwise continuous functions of a random variable developed by Delgado and Hidalgo (1996) to higher conditional moments, in particular the conditional variance.
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La performance di modelli non lineari per i tassi di cambio: un'applicazione con dati a diversa frequenza
Gianna Boero,Emanuela Marrocu +1 more
TL;DR: In this article, the authors compare the performance of different models for the returns of some of the most traded exchange rates in terms of the US dollar, namely the French Franc (FF/$), the German Mark (DM/$), and the Japanese Yen (Y/$).
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A high-frequency analysis of the interactions between REIT return and volatility
TL;DR: In this article, the authors make the first attempt in the real estate literature to test the two hypotheses depicting the interactions between return and volatility, the leverage effect and volatility feedback effect.
Modelización de la volatilidad del tipo de interés a corto plazo
TL;DR: In this paper, a trabajo se centra en the modelizacion de la volatilidad de the cambios of the interes of different modalities a corto plazo, and compare distintos modelos of heteroscedasticidad condicional agrupados in tres bloques.
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Risk management of Bitcoin futures with GARCH models
TL;DR: In this article , the authors investigated the quantitative risk management of Bitcoin futures by using the GARCH models and found that it is crucial to introduce a heavy-tailed distribution into the gARCH models to explain return volatilities of the Bitcoin futures.
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.
Journal ArticleDOI
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.