A Video Interview of Buz Brock
Author
Abstract
Suggested Citation
DOI: 10.2202/1558-3708.1308
Download full text from publisher
As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.
Other versions of this item:
- Bruce Mizrach, 2004. "A Video Interview of Buz Brock," Departmental Working Papers 200417, Rutgers University, Department of Economics.
References listed on IDEAS
- repec:cup:macdyn:v:4:y:2000:i:1:p:108-38 is not listed on IDEAS
- Woodford, Michael, 2000. "An Interview With William A. Brock," Macroeconomic Dynamics, Cambridge University Press, vol. 4(1), pages 108-138, March.
- Mantegna,Rosario N. & Stanley,H. Eugene, 2007.
"Introduction to Econophysics,"
Cambridge Books,
Cambridge University Press, number 9780521039871, October.
- Mantegna,Rosario N. & Stanley,H. Eugene, 1999. "Introduction to Econophysics," Cambridge Books, Cambridge University Press, number 9780521620086, September.
- Brock, W. A., 1986. "Distinguishing random and deterministic systems: Abridged version," Journal of Economic Theory, Elsevier, vol. 40(1), pages 168-195, October.
- Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
- Bollerslev, Tim, 1986.
"Generalized autoregressive conditional heteroskedasticity,"
Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
- Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
- Brock, W.A. & Dechert, W.D. & LeBaron, B. & Scheinkman, J.A., 1995. "A Test for Independence Based on the Correlation Dimension," Working papers 9520, Wisconsin Madison - Social Systems.
- Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Huiming Zhu & Xianfang Su & Wanhai You & Yinghua Ren, 2017. "Asymmetric effects of oil price shocks on stock returns: evidence from a two-stage Markov regime-switching approach," Applied Economics, Taylor & Francis Journals, vol. 49(25), pages 2491-2507, May.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Fernando Fernandez-Rodriguez & Simon Sosvilla-Rivero & Maria Dolores Garcia-Artiles, 1997. "Using nearest neighbour predictors to forecast the Spanish stock market," Investigaciones Economicas, Fundación SEPI, vol. 21(1), pages 75-91, January.
- Ataurima Arellano, Miguel & Rodríguez, Gabriel, 2020. "Empirical modeling of high-income and emerging stock and Forex market return volatility using Markov-switching GARCH models," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
- Theodore Panagiotidis, 2010.
"Market efficiency and the Euro: the case of the Athens stock exchange,"
Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 37(3), pages 237-251, July.
- Theodore Panagiotidis, 2003. "Market Efficiency and the Euro:The case of the Athens Stock Exchange," Public Policy Discussion Papers 03-08, Economics and Finance Section, School of Social Sciences, Brunel University.
- Theodore Panagiotidis, 2008. "Market Efficiency and the Euro: The case of the Athens Stock exchange," Discussion Paper Series 2008_14, Department of Economics, University of Macedonia, revised Dec 2008.
- Theodore Panagiotidis, 2005. "Market Efficiency and the Euro: The case of the Athens Stock Exchange," Finance 0507022, University Library of Munich, Germany.
- Theodore Panagiotidis, 2003. "Market Efficiency and the Euro:The case of the Athens Stock Exchange," Economics and Finance Discussion Papers 03-08, Economics and Finance Section, School of Social Sciences, Brunel University.
- Misiorek Adam & Trueck Stefan & Weron Rafal, 2006. "Point and Interval Forecasting of Spot Electricity Prices: Linear vs. Non-Linear Time Series Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(3), pages 1-36, September.
- Rossen Anja, 2016.
"On the Predictive Content of Nonlinear Transformations of Lagged Autoregression Residuals and Time Series Observations,"
Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 236(3), pages 389-409, May.
- Rossen Anja, 2016. "On the Predictive Content of Nonlinear Transformations of Lagged Autoregression Residuals and Time Series Observations," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 236(3), pages 389-409, May.
- Rossen, Anja, 2011. "On the predictive content of nonlinear transformations of lagged autoregression residuals and time series observations," HWWI Research Papers 113, Hamburg Institute of International Economics (HWWI).
- Rossen, Anja, 2014. "On the predictive content of nonlinear transformations of lagged autoregression residuals and time series observations," HWWI Research Papers 157, Hamburg Institute of International Economics (HWWI).
- Pelletier, Denis, 2006.
"Regime switching for dynamic correlations,"
Journal of Econometrics, Elsevier, vol. 131(1-2), pages 445-473.
- Denis Pelletier, 2004. "Regime Switching for Dynamic Correlations," Econometric Society 2004 North American Summer Meetings 230, Econometric Society.
- Krishnamurthy, Vikram & Leoff, Elisabeth & Sass, Jörn, 2018. "Filterbased stochastic volatility in continuous-time hidden Markov models," Econometrics and Statistics, Elsevier, vol. 6(C), pages 1-21.
- Marisa Faggini, 2011. "Chaotic Time Series Analysis in Economics: Balance and Perspectives," Working papers 25, Former Department of Economics and Public Finance "G. Prato", University of Torino.
- Bernardi, Mauro & Catania, Leopoldo, 2018. "Portfolio optimisation under flexible dynamic dependence modelling," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 1-18.
- Gianna Boero & Emanuela Marrocu, 2005.
"Evaluating non-linear models on point and interval forecasts: an application with exchange rates,"
BNL Quarterly Review, Banca Nazionale del Lavoro, vol. 58(232), pages 91-120.
- Gianna Boero & Emanuela Marrocu, 2005. "Evaluating non-linear models on point and interval forecasts: an application with exchange rates," Banca Nazionale del Lavoro Quarterly Review, Banca Nazionale del Lavoro, vol. 58(232), pages 91-120.
- Mihaela Craioveanu & Eric Hillebrand, 2012. "Level changes in volatility models," Annals of Finance, Springer, vol. 8(2), pages 277-308, May.
- Andrea Gaunersdorfer & Cars Hommes, 2007.
"A Nonlinear Structural Model for Volatility Clustering,"
Springer Books, in: Gilles Teyssière & Alan P. Kirman (ed.), Long Memory in Economics, pages 265-288,
Springer.
- Gaunersdorfer, A. & Hommes, C.H., 2000. "A Nonlinear Structural Model for Volatility Clustering," CeNDEF Working Papers 00-02, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
- Gaunersdorfer, A. & Hommes, C.H., 2005. "A nonlinear structural model for volatility clustering," CeNDEF Working Papers 05-02, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
- Martinez Oscar & Olmo Jose, 2012.
"A Nonlinear Threshold Model for the Dependence of Extremes of Stationary Sequences,"
Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(3), pages 1-39, September.
- Martínez Ibáñez, Oscar & Olmo, José, 2008. "A nonlinear threshold model for the dependence of extremes of stationary sequences," Working Papers 2072/5361, Universitat Rovira i Virgili, Department of Economics.
- Martinez, O. & Olmo, J., 2008. "A Nonlinear Threshold Model for the Dependence of Extremes of Stationary Sequences," Working Papers 08/08, Department of Economics, City University London.
- Kosater, Peter & Mosler, Karl, 2006.
"Can Markov regime-switching models improve power-price forecasts? Evidence from German daily power prices,"
Applied Energy, Elsevier, vol. 83(9), pages 943-958, September.
- Kosater, Peter & Mosler, Karl, 2005. "Can Markov-regime switching models improve power price forecasts? Evidence for German daily power prices," Discussion Papers in Econometrics and Statistics 1/05, University of Cologne, Institute of Econometrics and Statistics.
- Naifar, Nader, 2011. "What explains default risk premium during the financial crisis? Evidence from Japan," Journal of Economics and Business, Elsevier, vol. 63(5), pages 412-430, September.
- Fong, Wai Mun & See, Kim Hock, 2002. "A Markov switching model of the conditional volatility of crude oil futures prices," Energy Economics, Elsevier, vol. 24(1), pages 71-95, January.
- Maurício Yoshinori Une & Marcelo Savino Portugal, 2005. "Fear of disruption: a model of Markov-switching regimes for the Brazilian country risk conditional volatility," Econometrics 0509005, University Library of Munich, Germany.
- Rinke Saskia & Sibbertsen Philipp, 2016.
"Information criteria for nonlinear time series models,"
Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(3), pages 325-341, June.
- Rinke, Saskia & Sibbertsen, Philipp, 2015. "Information Criteria for Nonlinear Time Series Models," Hannover Economic Papers (HEP) dp-548, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
- Pedro Nielsen Rotta & Pedro L. Valls Pereira, 2016. "Analysis of contagion from the dynamic conditional correlation model with Markov Regime switching," Applied Economics, Taylor & Francis Journals, vol. 48(25), pages 2367-2382, May.
- M. Hashem Pesaran & Francisco J. Ruge-Murcia, 1996. "Limited-dependent rational expectations models with jumps," Discussion Paper / Institute for Empirical Macroeconomics 111, Federal Reserve Bank of Minneapolis.
More about this item
JEL classification:
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bpj:sndecm:v:9:y:2005:i:1:n:1. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.