Villa 'Les Terrasses, Garches, Paris [slaid]

Villa 'Les Terrasses' Garches Paris [slaid]

Comparing GARCH Models by Introducing Fuzzy Asymmetric Realized GARCH by Esmaiel Abounoori, Mohammad Amin Zabol

Subjects: “…garch models…”
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GARCH Proof of Concept by Datta, Shoumen

Subjects: “…Forecasting, SCM, demand amplification, risk management, intelligent decision systems, auto-id, GARCH…”
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PERAMALAN VOLATILITAS SAHAM MENGGUNAKAN MODEL EXPONENTIAL GARCH DAN THRESHOLD GARCH by SITI RAHAYU NINGSIH, I WAYAN SUMARJAYA, KARTIKA SARI

“…In financial data there is asymmetric volatility, which denotes the different movements on conditional volatility of increase and decrease financial asset returns. The exponential GARCH and threshold GARCH models can be used to capture asymmetric volatility, called leverage effect. …”
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MODELING ROMANIAN EXCHANGE RATE EVOLUTION WITH GARCH, TGARCH, GARCH- IN MEAN MODELS by Cociuba Mihail Ioan, Trenca Ioan

Subjects: “…exchange rate, GARCH, TGARCH, AIC, BIC.…”
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Calculation of Crude Oil Price Risk Using HM-GARCH and MRS-GARCH Model by Moslem Nilchi, Ali Farhadian

“…Accordingly, the present study compares the Markov Regime Switching (MRS) and Hidden Markov (HM) volatility models with the GJR-GARCH asymmetric model on their forecasting capabilities in the WTI and Brent crude oil markets. …”
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Performance of the Realized-GARCH Model against Other GARCH Types in Predicting Cryptocurrency Volatility by Rhenan G. S. Queiroz, Sergio A. David

“…This study emphasizes an investigation on the performance of the Realized-GARCH against a range of GARCH-based models to predict the volatility of five prominent cryptocurrency assets. …”
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On GARCH(p,q) convergence by J. Carkovs, N. Gutmanis

“…The paper deals with symmetric GARCH(p,q) model. Assuming that there exists defined by this model stationary time series, we have proposed the necessary and sufficient condition for exponential mean square convergence of any stochastic recurrent procedure satisfying this model to the above stationary time series. …”
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A GARCH Tutorial with R by Marcelo Scherer Perlin, Mauro Mastella, Daniel Francisco Vancin, Henrique Pinto Ramos

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Ainda os modelos GARCH by Rodrigo De Losso da Silveira Bueno

Subjects: “…GARCH Models…”
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Multimodality in GARCH Regression Models. by Doornik, J, Ooms, M

“…It is shown empirically that mixed autoregressive moving average regression models with generalized autoregressive conditional heteroskedasticity (Reg-ARMA-GARCH models) can have multimodality in the likelihood that is caused by a dummy variable in the conditional mean. …”

Outlier Detection in GARCH Models. by Doornik, J, Ooms, M

“…We present a new procedure for detecting multiple additive outliers in GARCH(1,1) models at unknown dates. The outlier candidates are the observations with the largest standardized residual. …”

Multimodality in the GARCH Regression Models. by Doornik, J, Ooms, M

“…It is shown empirically that mixed autoregressive moving average regression models with generalized autoregressive conditional heteroskedasticity (Reg-ARMA-GARCH models) can have multimodality in the likelihood that is caused by a dummy variable in the conditional mean. …”

Volatility Co-Movement between Bitcoin and Stablecoins: BEKK–GARCH and Copula–DCC–GARCH Approaches by Kuo-Shing Chen, Shen-Ho Chang

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GRG Non-Linear and ARWM Methods for Estimating the GARCH-M, GJR, and log-GARCH Models by Didit Budi Nugroho, Lam Peter Panjaitan, Dini Kurniawati, Zaini Kholil, Bambang Susanto, Leopoldus Ricky Sasongko

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On The Accuracy of GARCH Estimation in R Packages by B. D. McCullough, Chelsey Hill

“…The R software is commonly used in applied finance and generalized autoregressive conditionally heteroskedastic (GARCH) estimation is a staple of applied finance; many papers use R to compute GARCH estimates. …”
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Kurtosis dan model volatiliti Garch by , IFANSYAH, Nor, , Prof. Drs. Subanar, Ph.D

Stability of nonlinear AR-GARCH models by Meitz, M, Saikkonen, P

“…We consider a nonlinear autoregression of order p (AR(p)) with the conditional variance specified as a nonlinear first order generalized autoregressive conditional heteroskedasticity (GARCH(1,1)) model. Conditions under which the model is stable in the sense that its Markov chain representation is geometrically ergodic are provided. …”

Stability of nonlinear AR-GARCH models. by Meitz, M, Saikkonen, P

“…We consider a nonlinear autoregression of order p (AR(p)) with the conditional variance specified as a nonlinear first order generalized autoregressive conditional heteroskedasticity (GARCH(1,1)) model. Conditions under which the model is stable in the sense that its Markov chain representation is geometrically ergodic are provided. …”