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Autoregressive conditional heteroskedasticity
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151	RESEARCH REPORT Serial No. 507 November 2013 THRESHOLD MODELS IN TIME SERIES ANALYSIS-SOME REFLECTIONS Add to Reading List Source URL: lx2.saas.hku.hk Language: English - Date: 2013-11-05 06:18:22 Non-linear systems Stochastic processes Noise STAR model Autoregressive conditional heteroskedasticity Threshold model Akaike information criterion Moving-average model Maximum likelihood Statistics Time series analysis Estimation theory
152	Dynamic Models for Volatility and Heavy Tails Course Information Date: Tuesday 17th December 2013 Location: Cass Business School, London Lecturer: Andrew Harvey, FBA, Professor of Econometrics, Cambridge University This Add to Reading List Source URL: www.cfenetwork.org Language: English - Date: 2013-08-08 01:50:46 Time series analysis Autoregressive conditional heteroskedasticity Time series Volatility Economic model Economics Mathematical sciences Statistics Mathematical finance Econometrics
153	Proceedings of the 2005 International Conference on Simulation and Modelling V. Kachitvichyanakul, U. Purintrapiban, and P. Uthayopas, eds. A TIME SERIES ANALYSIS OF THE UNCERTAINTY IN INTERNATIONAL TOURIST ARRIVALS TO T Add to Reading List Source URL: www.mssanz.org.au Language: English - Date: 2013-01-15 22:02:57 Time series analysis Tourism Moving-average model Economics Statistics Autoregressive conditional heteroskedasticity Econometrics
154 $Statistics / Volatility / Autoregressive conditional heteroskedasticity / Beta / Futures contract / Stochastic volatility / Markov switching multifractal / Mathematical finance / Financial economics / Finance$	Have Aluminium And Copper Futures Markets Become More Volatile Over Time? Add to Reading List Source URL: www.mssanz.org.au Language: English - Date: 2013-01-15 19:03:42 Statistics Volatility Autoregressive conditional heteroskedasticity Beta Futures contract Stochastic volatility Markov switching multifractal Mathematical finance Financial economics Finance
155	R functions for time series analysis by Vito Ricci () RR FUNCTIONS FOR TIME SERIES ANALYSIS Here are some helpful R functions for time series analysis. They belong from stats, tseries, Add to Reading List Source URL: star-www.st-andrews.ac.uk Language: English - Date: 2004-11-29 04:09:50 Econometrics Covariance and correlation Noise Augmented Dickey–Fuller test Autoregressive integrated moving average Autoregressive conditional heteroskedasticity Partial autocorrelation function Time series Jarque–Bera test Statistics Time series analysis Statistical tests
156	Curriculum Vitae for WAI KEUNG LI Ph. D. Department of Statistics & Actuarial Science Add to Reading List Source URL: lx2.saas.hku.hk Language: English - Date: 2014-10-29 02:24:37 Autoregressive conditional heteroskedasticity Time series Linear regression Unit root test Autoregressive–moving-average model Akaike information criterion Autoregressive conditional duration Threshold model Heteroscedasticity Statistics Time series analysis Econometrics
157	Package Development in R: Implementing GO-GARCH models Dr. Bernhard Pfaff Invesco Asset Management Deutschland GmbH, Frankfurt am Main Add to Reading List Source URL: www.pfaffikus.de Language: English - Date: 2012-07-05 15:38:17 Time series analysis Autoregressive conditional heteroskedasticity Data analysis Covariance matrix Normal distribution Matrix Covariance Statistics Covariance and correlation Econometrics
158	Value at Risk Estimation using Extreme Value Theory Add to Reading List Source URL: www.mssanz.org.au Language: English - Date: 2013-01-15 23:48:05 Mathematical finance Econometrics Autoregressive conditional heteroskedasticity Time series analysis Extreme value theory Generalized extreme value distribution RiskMetrics Financial risk modeling Expected shortfall Statistics Actuarial science Financial risk
159	R functions for time series analysis by Vito Ricci () RR FUNCTIONS FOR TIME SERIES ANALYSIS Here are some helpful R functions for time series analysis. They belong from stats, tseries, Add to Reading List Source URL: cran.repo.bppt.go.id Language: English - Date: 2004-11-29 04:09:50 Econometrics Covariance and correlation Noise Augmented Dickey–Fuller test Autoregressive integrated moving average Autoregressive conditional heteroskedasticity Partial autocorrelation function Time series Jarque–Bera test Statistics Time series analysis Statistical tests
160	R functions for time series analysis by Vito Ricci () RR FUNCTIONS FOR TIME SERIES ANALYSIS Here are some helpful R functions for time series analysis. They belong from stats, tseries, Add to Reading List Source URL: cran-r.c3sl.ufpr.br Language: English - Date: 2004-11-29 04:09:50 Econometrics Covariance and correlation Noise Augmented Dickey–Fuller test Autoregressive integrated moving average Autoregressive conditional heteroskedasticity Partial autocorrelation function Time series Jarque–Bera test Statistics Time series analysis Statistical tests

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