Autoregressive conditional heteroskedasticity (English Wikipedia)

Analysis of information sources in references of the Wikipedia article "Autoregressive conditional heteroskedasticity" in English language version.

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13doi.org

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5semanticscholar.org

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2psu.edu

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1hu-berlin.de

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1duke.edu

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1martinsewell.com

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1ssrn.com

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1worldcat.org

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1handle.net

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1uni-muenchen.de

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1nih.gov

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arxiv.org

Otto, P.; Schmid, W.; Garthoff, R. (2018). "Generalised spatial and spatiotemporal autoregressive conditional heteroscedasticity". Spatial Statistics. 26 (1): 125–145. arXiv:1609.00711. doi:10.1016/j.spasta.2018.07.005. S2CID 88521485.
Platanios, E.; Chatzis, S. (2014). "Gaussian process-mixture conditional heteroscedasticity". IEEE Transactions on Pattern Analysis and Machine Intelligence. 36 (5): 889–900. arXiv:1211.4410. doi:10.1109/TPAMI.2013.183. PMID 26353224. S2CID 10424638.

doi.org

Engle, Robert F. (1982). "Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of United Kingdom Inflation". Econometrica. 50 (4): 987–1007. doi:10.2307/1912773. JSTOR 1912773.
Bollerslev, Tim (1986). "Generalized Autoregressive Conditional Heteroskedasticity". Journal of Econometrics. 31 (3): 307–327. CiteSeerX 10.1.1.468.2892. doi:10.1016/0304-4076(86)90063-1. S2CID 8797625.
Lanne, Markku; Saikkonen, Pentti (July 2005). "Non-linear GARCH models for highly persistent volatility" (PDF). The Econometrics Journal. 8 (2): 251–276. doi:10.1111/j.1368-423X.2005.00163.x. JSTOR 23113641. S2CID 15252964.
Engle, Robert F.; Ng, Victor K. (1993). "Measuring and testing the impact of news on volatility" (PDF). Journal of Finance. 48 (5): 1749–1778. doi:10.1111/j.1540-6261.1993.tb05127.x. SSRN 262096. It is not yet clear in the finance literature that the asymmetric properties of variances are due to changing leverage. The name "leverage effect" is used simply because it is popular among researchers when referring to such a phenomenon.
Higgins, M.L; Bera, A.K (1992). "A Class of Nonlinear Arch Models". International Economic Review. 33 (1): 137–158. doi:10.2307/2526988. JSTOR 2526988.
Caporale, Guglielmo Maria; Pittis, Nikitas; Spagnolo, Nicola (October 2003). "IGARCH models and structural breaks". Applied Economics Letters. 10 (12): 765–768. doi:10.1080/1350485032000138403. ISSN 1350-4851.
St. Pierre, Eilleen F. (1998). "Estimating EGARCH-M Models: Science or Art". The Quarterly Review of Economics and Finance. 38 (2): 167–180. doi:10.1016/S1062-9769(99)80110-0.
Chatterjee, Swarn; Hubble, Amy (2016). "Day-Of-The-Whieek Effect In Us Biotechnology Stocks—Do Policy Changes And Economic Cycles Matter?". Annals of Financial Economics. 11 (2): 1–17. doi:10.1142/S2010495216500081.
Hentschel, Ludger (1995). "All in the family Nesting symmetric and asymmetric GARCH models". Journal of Financial Economics. 39 (1): 71–104. CiteSeerX 10.1.1.557.8941. doi:10.1016/0304-405X(94)00821-H.
Klüppelberg, C.; Lindner, A.; Maller, R. (2004). "A continuous-time GARCH process driven by a Lévy process: stationarity and second-order behaviour". Journal of Applied Probability. 41 (3): 601–622. doi:10.1239/jap/1091543413. hdl:10419/31047. S2CID 17943198.
Li, D.; Zhang, X.; Zhu, K.; Ling, S. (2018). "The ZD-GARCH model: A new way to study heteroscedasticity" (PDF). Journal of Econometrics. 202 (1): 1–17. doi:10.1016/j.jeconom.2017.09.003.
Otto, P.; Schmid, W.; Garthoff, R. (2018). "Generalised spatial and spatiotemporal autoregressive conditional heteroscedasticity". Spatial Statistics. 26 (1): 125–145. arXiv:1609.00711. doi:10.1016/j.spasta.2018.07.005. S2CID 88521485.
Platanios, E.; Chatzis, S. (2014). "Gaussian process-mixture conditional heteroscedasticity". IEEE Transactions on Pattern Analysis and Machine Intelligence. 36 (5): 889–900. arXiv:1211.4410. doi:10.1109/TPAMI.2013.183. PMID 26353224. S2CID 10424638.

duke.edu

public.econ.duke.edu

Bollerslev, Tim; Russell, Jeffrey; Watson, Mark (May 2010). "Chapter 8: Glossary to ARCH (GARCH)" (PDF). Volatility and Time Series Econometrics: Essays in Honor of Robert Engle (1st ed.). Oxford: Oxford University Press. pp. 137–163. ISBN 9780199549498. Retrieved 27 October 2017.

handle.net

hdl.handle.net

Klüppelberg, C.; Lindner, A.; Maller, R. (2004). "A continuous-time GARCH process driven by a Lévy process: stationarity and second-order behaviour". Journal of Applied Probability. 41 (3): 601–622. doi:10.1239/jap/1091543413. hdl:10419/31047. S2CID 17943198.

hu-berlin.de

edoc.hu-berlin.de

Lanne, Markku; Saikkonen, Pentti (July 2005). "Non-linear GARCH models for highly persistent volatility" (PDF). The Econometrics Journal. 8 (2): 251–276. doi:10.1111/j.1368-423X.2005.00163.x. JSTOR 23113641. S2CID 15252964.

ijf.hr

Posedel, Petra (2006). "Analysis Of The Exchange Rate And Pricing Foreign Currency Options On The Croatian Market: The Ngarch Model As An Alternative To The Black Scholes Model" (PDF). Financial Theory and Practice. 30 (4): 347–368. Special attention to the model is given by the parameter of asymmetry [theta (θ)] which describes the correlation between returns and variance.⁶ ...
⁶ In the case of analyzing stock returns, the positive value of [theta] reflects the empirically well known leverage effect indicating that a downward movement in the price of a stock causes more of an increase in variance more than a same value downward movement in the price of a stock, meaning that returns and variance are negatively correlated

jstor.org

Engle, Robert F. (1982). "Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of United Kingdom Inflation". Econometrica. 50 (4): 987–1007. doi:10.2307/1912773. JSTOR 1912773.
Lanne, Markku; Saikkonen, Pentti (July 2005). "Non-linear GARCH models for highly persistent volatility" (PDF). The Econometrics Journal. 8 (2): 251–276. doi:10.1111/j.1368-423X.2005.00163.x. JSTOR 23113641. S2CID 15252964.
Higgins, M.L; Bera, A.K (1992). "A Class of Nonlinear Arch Models". International Economic Review. 33 (1): 137–158. doi:10.2307/2526988. JSTOR 2526988.

martinsewell.com

finance.martinsewell.com

Engle, Robert F.; Ng, Victor K. (1993). "Measuring and testing the impact of news on volatility" (PDF). Journal of Finance. 48 (5): 1749–1778. doi:10.1111/j.1540-6261.1993.tb05127.x. SSRN 262096. It is not yet clear in the finance literature that the asymmetric properties of variances are due to changing leverage. The name "leverage effect" is used simply because it is popular among researchers when referring to such a phenomenon.

nbn-resolving.de

Klüppelberg, C.; Lindner, A.; Maller, R. (2004). "A continuous-time GARCH process driven by a Lévy process: stationarity and second-order behaviour". Journal of Applied Probability. 41 (3): 601–622. doi:10.1239/jap/1091543413. hdl:10419/31047. S2CID 17943198.

nih.gov

pubmed.ncbi.nlm.nih.gov

Platanios, E.; Chatzis, S. (2014). "Gaussian process-mixture conditional heteroscedasticity". IEEE Transactions on Pattern Analysis and Machine Intelligence. 36 (5): 889–900. arXiv:1211.4410. doi:10.1109/TPAMI.2013.183. PMID 26353224. S2CID 10424638.

psu.edu

citeseerx.ist.psu.edu

Bollerslev, Tim (1986). "Generalized Autoregressive Conditional Heteroskedasticity". Journal of Econometrics. 31 (3): 307–327. CiteSeerX 10.1.1.468.2892. doi:10.1016/0304-4076(86)90063-1. S2CID 8797625.
Hentschel, Ludger (1995). "All in the family Nesting symmetric and asymmetric GARCH models". Journal of Financial Economics. 39 (1): 71–104. CiteSeerX 10.1.1.557.8941. doi:10.1016/0304-405X(94)00821-H.

semanticscholar.org

api.semanticscholar.org

Bollerslev, Tim (1986). "Generalized Autoregressive Conditional Heteroskedasticity". Journal of Econometrics. 31 (3): 307–327. CiteSeerX 10.1.1.468.2892. doi:10.1016/0304-4076(86)90063-1. S2CID 8797625.
Lanne, Markku; Saikkonen, Pentti (July 2005). "Non-linear GARCH models for highly persistent volatility" (PDF). The Econometrics Journal. 8 (2): 251–276. doi:10.1111/j.1368-423X.2005.00163.x. JSTOR 23113641. S2CID 15252964.
Klüppelberg, C.; Lindner, A.; Maller, R. (2004). "A continuous-time GARCH process driven by a Lévy process: stationarity and second-order behaviour". Journal of Applied Probability. 41 (3): 601–622. doi:10.1239/jap/1091543413. hdl:10419/31047. S2CID 17943198.
Otto, P.; Schmid, W.; Garthoff, R. (2018). "Generalised spatial and spatiotemporal autoregressive conditional heteroscedasticity". Spatial Statistics. 26 (1): 125–145. arXiv:1609.00711. doi:10.1016/j.spasta.2018.07.005. S2CID 88521485.
Platanios, E.; Chatzis, S. (2014). "Gaussian process-mixture conditional heteroscedasticity". IEEE Transactions on Pattern Analysis and Machine Intelligence. 36 (5): 889–900. arXiv:1211.4410. doi:10.1109/TPAMI.2013.183. PMID 26353224. S2CID 10424638.

ssrn.com

papers.ssrn.com

Engle, Robert F.; Ng, Victor K. (1993). "Measuring and testing the impact of news on volatility" (PDF). Journal of Finance. 48 (5): 1749–1778. doi:10.1111/j.1540-6261.1993.tb05127.x. SSRN 262096. It is not yet clear in the finance literature that the asymmetric properties of variances are due to changing leverage. The name "leverage effect" is used simply because it is popular among researchers when referring to such a phenomenon.

tandfonline.com

Caporale, Guglielmo Maria; Pittis, Nikitas; Spagnolo, Nicola (October 2003). "IGARCH models and structural breaks". Applied Economics Letters. 10 (12): 765–768. doi:10.1080/1350485032000138403. ISSN 1350-4851.

uni-muenchen.de

mpra.ub.uni-muenchen.de

Li, D.; Zhang, X.; Zhu, K.; Ling, S. (2018). "The ZD-GARCH model: A new way to study heteroscedasticity" (PDF). Journal of Econometrics. 202 (1): 1–17. doi:10.1016/j.jeconom.2017.09.003.

worldcat.org

search.worldcat.org

Caporale, Guglielmo Maria; Pittis, Nikitas; Spagnolo, Nicola (October 2003). "IGARCH models and structural breaks". Applied Economics Letters. 10 (12): 765–768. doi:10.1080/1350485032000138403. ISSN 1350-4851.