Autoregressive conditional heteroskedasticity
Study About the Minimum Value at Risk of Stock Index Futures Hedging Applying Exponentially Weighted Moving Average - Generalized Autoregressive Conditional Heteroskedasticity Model
... average-generalized autoregressive conditional heteroskedasticity (GARCH) (1,1)-M applicable to the real financial markets based on previous ...
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Testing and modelling autoregressive conditional heteroskedasticity of streamflow processes
... (Periodic AutoRegressive Moving Average) models for sea- sonal streamflow ...of autoregressive conditional het- eroskedasticity ...(AutoRegressive Conditional Heteroskedasticity) ...
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FORECASTING GOLD PRICES IN SRI LANKA USING GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSKEDASTICITY APPROACH
... as Autoregressive Integrated Moving Average (ARIMA) (Pitigalaarachchi et ...Generalized Autoregressive Conditional Heteroskedasticity (GARCH) family models (Mahalingam et ...
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Estimation of Volatility and Correlation with Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models: An Application to Moroccan Stock Markets
... generalized autoregressive conditional heteroskedasticity (GARCH) models were developed for this purpose and have known a great ...dynamic conditional correlation (DCC) and Baba, Engle, Kraft ...
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Autoregressive Conditional Heteroskedasticity Models and the Dynamic Structure of the Athens Stock Exchange
... According to efficient market theory, the stock market returns themselves contain little serial correlation. Moreover, when high frequency data is used, the non-synchronous trading in the stocks making up an index ...
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Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review
... the conditional variance persist indefinitely does not reconcile with the persistence observed after large shocks, such as the crash of October 1987, and with the perceived behavior of agents who do not appear to ...
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Estimating value at risk for sukuk market using generalized autoregressive conditional heteroskedasticity models
... 4.3 In- sample evaluation and parameters estimates of all GARCH models for Malaysian Sukuk return series, using the entire dataset and assuming three different distribut[r] ...
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Functional generalized autoregressive conditional heteroskedasticity
... the autoregressive conditional heteroskedastic, ARCH, model, and Bollerslev (1986), who introduced the generalized ARCH, GARCH, model to deal with non-constant and randomly changing volatilities for ...
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Support Vector Machine and Least Square Support Vector Machine Stock Forecasting Models
... General Autoregressive Conditional Heteroskedasticity (GARCH), Support Vector Regression (SVR) and Least Square Support Vector Machine (LSSVM) are combined with the wavelet kernel to form three novel ...
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A Note on the Oil Price Trend and GARCH Shocks
... This paper investigates the trend in the monthly real price of oil between 1990 and 2008 with a generalized autoregressive conditional heteroskedasticity (GARCH) model. Trend and volatility are ...
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Assessment of data-driven models in downscaling of the daily temperature in Birjand synoptic station
... Contemporaneous Autoregressive-Moving Average (CARMA), CARMA-ARCH (Autoregressive Conditional Heteroskedasticity), Support Vector Regression (SVR), Adaptive Neuro-Fuzzy Inference System ...
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Volatility estimation for Bitcoin: A comparison of GARCH models
... for conditional heteroskedasticity confirms that there exist ARCH effects in the returns of the Bitcoin price index, suggesting that the Autoregressive model for the conditional mean needs to ...
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On the Performance of Garch Family Models in the Presence of Additive Outliers
... generalized autoregressive conditional heteroskedasticity (GARCH) ...with autoregressive moving average (ARMA) formulation, was proposed independently by Bollerslev (1986) and Tylor (1986) in ...
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An Empirical Investigation of Arima and Garch Models in Agricultural Price Forecasting
... export. Autoregressive integrated moving average (ARIMA) models performed better than the structural model in predicting the wheat price (Moghaddasiand et ...generalized autoregressive conditional ...
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Does inflation has an Impact on Stock Returns and Volatility? Evidence from Nigeria and Ghana
... generalized autoregressive conditional heteroskedasticity (GARCH) model to assess the impact of inflation on stock market returns and volatility using monthly time series data from two West African ...
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Conditional heteroskedasticity in crypto asset returns
... Keywords: Autoregressive conditional heteroskedasticity (ARCH), generalized autoregressive conditional heteroskedasticity (GARCH), market volatility, nonlinear time series, ...
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Structural VAR analysis of monetary transmission mechanism and central bank’s response to equity volatility shock in Taiwan
... Generalized Autoregressive Conditional Heteroskedasticity (GARCH) volatility of TWSE on Taiwan’s daily exchange rate, overnight interbank loan rate, and Taiwan Government Bond Index ...
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Compare Value at Risk and Return of Assets Portfolio Stock, Gold, REIT, U.S. & Iran Market Indices
... represent autoregressive conditional heteroskedasticity and generalized autoregressive conditional heteroskedasticity, are designed to deal with just in financial applications ...
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Rolling sampled parameters of ARCH and Levy stable models
... asymmetric autoregressive conditional heteroskedasticity (ARCH) model and a Levy-stable distribution are applied to some well-known financial indices (DAX30, FTSE20, FTSE100 and SP500), using a ...
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Real Time Monitoring of Carbon Monoxide Using Value at Risk Measure and Control Charting
... Keywords: Air Quality Surveillance, Atmospheric Pollution, Autoregressive Conditional Heteroskedasticity modelling, Control Charts, Diag-aVECH, Multivariate Statistical Process Monitorin[r] ...
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