GARCH-in-Mean Model
Research on Dynamic Relationship between Exchange Rate and Stock Price—Based on GARCH in Mean Model
... The GARCH-in-Mean model not only focuses on the impact of changes in the foreign exchange market on the domestic stock market, but also using the equa- tion of variance to explain the uncertainty ...
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The time-varying GARCH-in-mean model
... Conclusion I introduce a kernel-based iterative estimator that combines the estimators in Giraitis, Kapetanios, and Yates 2013 and Linton and Perron 2003 to estimate the stochastic time-[r] ...
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Inflation and Inflation Uncertainty in Iran: An Application of GARCH-in-Mean Model with FIML Method of Estimation
... This paper examines the relationship between inflation and inflation uncertainty with Iranian data for the period of 1990 to 2009 and FIML method of estimation. The paper contributes to the literature in several ...
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A Comparative Study of the Taiwan and Japan Equity and Foreign Exchange Markets: Modeling, Estimation and Application of the Component Garch-in-Mean Model
... the GARCH framework, where it incorporates past conditional variances into current conditional variance, In his study, stationary conditions and autocorrelation structures of the GARCH model for this ...
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Price, Return and Volatility Linkages of Base Metal Futures traded in India
... Mechanism Model (b) Return and Volatility – Modified GARCH model (c) Return and Volatility - ARMA-GARCH in mean model – Innovations ...
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Asymptotic Theory for GARCH-in-mean Models
... the GARCH-in-mean process and its squared ...ARCH-M model and conducted numeric exper- iments on the estimator, but no asymptotic theory was ...in mean model by combining both ...
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Dynamic Relationship between Inflation Uncertainty and Private Investment in Iran: An Application of VAR-GARCH-M Model
... the mean equations are the inflation and the private ...in mean equations and their uncertainty measures in variance ...to model a BGARCH model to simultaneously estimate the conditional ...
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A Comparison of Conditional Volatility Estimators for the ISE National 100 Index Returns
... 1000 GARCH type models in terms of their ability to fit to the historical data and to forecast the conditional variance in an out- of-sample ...used GARCH(1,1) model performs well, it is still ...
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Measuring the Forecast Performance of GARCH and Bilinear-GARCH Models in Time Series Data
... in model evaluation. These include mean absolute error (MAE), root mean square error (RMSE), mean absolute deviation (MAD), mean absolute precision error (MAPE) and THEIL ...
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Revisiting the Effects of Growth Uncertainty on Inflation in Iran:An Application of GARCH-in-Mean Models
... The Breush-Godfrey Serial Correlation LM Test rejects first through 12 order serial correlation at all standard significant levels. However, the LM tests for ARCH reject the null of no first or eight order conditional ...
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A Nonlinear Threshold Model for the Dependence of Extremes of Stationary Sequences
... pure GARCH(1,1) processes or AR(1)-GARCH(1,1) with a very small although statistically significant autoregressive param- eter for modeling the sequence of ...market. Model (5) however can be devised ...
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A Study on Taiwan's Bond Market Integrity and Market Timing Ability - Based on The Armax-Garch Model
... Table 2 reports the descriptive statistics of the bond funds’ net asset value (hereafter, Nav), beta ratio, Jensen index, Treynor index, Sharpe index, and the rate of return. Here, Nav runs between NT$10.671 to ...
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Nonlinear volatility models in economics: smooth transition and neural network augmented GARCH, APGARCH, FIGARCH and FIAPGARCH models
... Threshold GARCH (TGARCH) model that aims to capture asymmetric effects of negative and positive shocks, the intuition to capture different effects below and above a certain threshold is ...STGARCH ...
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Modeling Stock Market Volatility Using Univariate GARCH Models: Evidence from Bangladesh
... The mean and variance equations of the estimated MA(1)- EGARCH(1,1) model for DSE show that all the parameters are highly significant at 1% ...estimated model for DSE satisfies all conditions of the ...
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A new approach to modelling nonlinear time series: introducing the ExpAR ARCH and ExpAR GARCH models and applications
... nonlinear model in the conditional mean and a nonlinear model in the conditional variance and have the potential of explaining observed data in various ...
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A Unified Probabilistic Approach of Tunisian Stock Market Cycle: Nonlinearity, Turning Points and Duration- Dependence
... single-regime model (M1) with AR(2) specification for the mean return equation and a GARCH(1,1) specification for the volatility ...the model M1 as the benchmark ...autoregressive GARCH ...
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The Glosten-Jagannathan-Runkle-Generalized Autoregressive Conditional Heteroscedastic Approach to Investigating the Foreign Exchange Forward Premium Volatility
... linear model with the consideration of the average effect and the conditional variance effect in a univariate framework namely GARCH-in ...the GARCH-M model is not a good specification for the ...
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Unconditional mean, Volatility and the Fourier Garch representation
... basic model can be extended to incorporate the long-run volatility in the mean ...to model inflation and money demand as having smooth changes in the ...to model the unknown shape of the ...
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Evaluating the Forecast Accuracy of Exchange Rate Volatility in Bangladesh Using ARCH Family of Models
... appropriate model, several model selection criterion: Akaike information criteria (AIC) and Schwarz information criteria (SIC) and for measuring accuracy Root mean squared error (RMSE), Mean ...
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Unified quasi maximum likelihood estimation theory for stable and unstable Markov bilinear processes
... conditional mean and volatility (CM V ) models because of their ability to describe both level and variability of a broad array of observed time series such as …nancial stock returns (see ...conditional ...
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