IDEAS home Printed from https://ideas.repec.org/e/c/plu79.html
   My authors  Follow this author

Richard Luger

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. René Garcia & Richard Luger, 2012. "Risk aversion, intertemporal substitution, and the term structure of interest rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(6), pages 1013-1036, September.

    Mentioned in:

    1. Risk aversion, intertemporal substitution, and the term structure of interest rates (Journal of Applied Econometrics 2012) in ReplicationWiki ()

Working papers

  1. Jean-Marie Dufour & Richard Luger, 2016. "Identification-robust moment-based tests for Markov-switching in autoregressive models," CIRANO Working Papers 2016s-63, CIRANO.

    Cited by:

    1. Gabriel Rodriguez-Rondon & Jean-Marie Dufour, 2024. "MSTest: An R-Package for Testing Markov Switching Models," Papers 2411.08188, arXiv.org.
    2. Gabriel Rodriguez-Rondon, 2024. "Underlying Core Inflation with Multiple Regimes," Papers 2411.12845, arXiv.org.
    3. Hiroyuki Kasahara & Katsumi Shimotsu, 2018. "Testing the Number of Regimes in Markov Regime Switching Models," Papers 1801.06862, arXiv.org, revised Jan 2018.

  2. Sermin Gungor & Richard Luger, 2014. "Bootstrap Tests of Mean-Variance Efficiency with Multiple Portfolio Groupings," Staff Working Papers 14-51, Bank of Canada.

    Cited by:

    1. Gungor, Sermin & Luger, Richard, 2020. "Small-sample tests for stock return predictability with possibly non-stationary regressors and GARCH-type effects," Journal of Econometrics, Elsevier, vol. 218(2), pages 750-770.
    2. Fu, Hsuan & Luger, Richard, 2022. "Multiple testing of the forward rate unbiasedness hypothesis across currencies," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 232-245.

  3. Sermin Gungor & Richard Luger, 2013. "Multivariate Tests of Mean-Variance Efficiency and Spanning with a Large Number of Assets and Time-Varying Covariances," Staff Working Papers 13-16, Bank of Canada.

    Cited by:

    1. David Ardia & S'ebastien Laurent & Rosnel Sessinou, 2024. "High-Dimensional Mean-Variance Spanning Tests," Papers 2403.17127, arXiv.org.
    2. Seung C. Ahn & Alex R. Horenstein, 2017. "Asset Pricing and Excess Returns over the Market Return," Working Papers 2017-12, University of Miami, Department of Economics.
    3. M. Hashem Pesaran & Takashi Yamagata, 2017. "Testing for Alpha in Linear Factor Pricing Models with a Large Number of Securities," Discussion Papers 17/04, Department of Economics, University of York.
    4. Feng, Long & Lan, Wei & Liu, Binghui & Ma, Yanyuan, 2022. "High-dimensional test for alpha in linear factor pricing models with sparse alternatives," Journal of Econometrics, Elsevier, vol. 229(1), pages 152-175.
    5. Cheng, Tingting & Yan, Cheng & Yan, Yayi, 2021. "Improved inference for fund alphas using high-dimensional cross-sectional tests," Journal of Empirical Finance, Elsevier, vol. 61(C), pages 57-81.
    6. Yu, Xiufan & Yao, Jiawei & Xue, Lingzhou, 2024. "Power enhancement for testing multi-factor asset pricing models via Fisher’s method," Journal of Econometrics, Elsevier, vol. 239(2).

  4. Luis García-Álvarez & Richard Luger, 2011. "Dynamic Correlations, Estimation Risk, and Porfolio Management During the Financial Crisis," Working Papers wp2011_1103, CEMFI, revised Sep 2011.

    Cited by:

    1. R. REYTIER & A. Blanes & Q. Gaucher & S. Thiam & P. Debled, 2015. "Behavior of Covariance Matrices with Equi-Correlation Approach," Proceedings of International Academic Conferences 2805027, International Institute of Social and Economic Sciences.
    2. Miralles-Quirós, José Luis & Miralles-Quirós, María del Mar, 2017. "The Copula ADCC-GARCH model can help PIIGS to fly," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 50(C), pages 1-12.
    3. Miralles-Marcelo, José Luis & Miralles-Quirós, María del Mar & Miralles-Quirós, José Luis, 2015. "Improving international diversification benefits for US investors," The North American Journal of Economics and Finance, Elsevier, vol. 32(C), pages 64-76.

  5. René Garcia & Richard Luger, 2009. "Risk Aversion, Intertemporal Substitution, and the Term Structure of Interest Rates," CIRANO Working Papers 2009s-20, CIRANO.

    Cited by:

    1. Elminejad, Ali & Havranek, Tomas & Irsova, Zuzana, 2022. "Relative Risk Aversion: A Meta-Analysis," MetaArXiv b8uhe, Center for Open Science.
    2. Jardet, C. & Monfort, A. & Pegoraro, F., 2009. "No-arbitrage Near-Cointegrated VAR(p) Term Structure Models, Term Premia and GDP Growth," Working papers 234, Banque de France.
    3. Gregory Bauer & Antonio Diez de los Rios, 2012. "An International Dynamic Term Structure Model with Economic Restrictions and Unspanned Risks," Staff Working Papers 12-5, Bank of Canada.
    4. Elminejad, Ali & Havranek, Tomas & Irsova, Zuzana, 2022. "Relative Risk Aversion: A Meta-Analysis," MetaArXiv b8uhe_v1, Center for Open Science.

  6. René Garcia & Richard Luger, 2005. "The Canadian Macroeconomy and the Yield Curve: An Equilibrium-Based Approach," Staff Working Papers 05-36, Bank of Canada.

    Cited by:

    1. René Garcia & Richard Luger, 2007. "The Canadian macroeconomy and the yield curve: an equilibrium-based approach," Canadian Journal of Economics, Canadian Economics Association, vol. 40(2), pages 561-583, May.
    2. Matteo Modena, 2008. "An Empirical Analysis of the Curvature Factor of the Term Structure of Interest Rates," Working Papers 2008_35, Business School - Economics, University of Glasgow.
    3. Huynh, Kim P. & Petrunia, Robert J. & Voia, Marcel, 2012. "Duration of new firms: The role of startup financial conditions, industry and aggregate factors," Structural Change and Economic Dynamics, Elsevier, vol. 23(4), pages 354-362.
    4. Lange, Ronald H., 2014. "The small open macroeconomy and the yield curve: A state-space representation," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 1-21.
    5. Mustapha Olalekan Ojo & Luís Aguiar-Conraria & Maria Joana Soares, 2020. "A time–frequency analysis of the Canadian macroeconomy and the yield curve," Empirical Economics, Springer, vol. 58(5), pages 2333-2351, May.
    6. Lange, Ronald H., 2013. "The Canadian macroeconomy and the yield curve: A dynamic latent factor approach," International Review of Economics & Finance, Elsevier, vol. 27(C), pages 261-274.
    7. Lange, Ronald Henry, 2018. "The term structure of liquidity premia and the macroeconomy in Canada: A dynamic latent-factor approach," International Review of Economics & Finance, Elsevier, vol. 57(C), pages 164-182.
    8. Lange, Ronald H., 2015. "International long-term yields and monetary policy in a small open economy: The case of Canada," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 292-310.
    9. Fousseni Chabi-Yo & Jun Yang, 2007. "A No-Arbitrage Analysis of Macroeconomic Determinants of Term Structures and the Exchange Rate," Staff Working Papers 07-21, Bank of Canada.
    10. Bruno Feunou & Jean-Sébastien Fontaine, 2012. "Forecasting Inflation and the Inflation Risk Premiums Using Nominal Yields," Staff Working Papers 12-37, Bank of Canada.

  7. Richard Luger, 2004. "Exact Tests of Equal Forecast Accuracy with an Application to the Term Structure of Interest Rates," Staff Working Papers 04-2, Bank of Canada.

    Cited by:

    1. Pär Österholm, 2008. "Can forecasting performance be improved by considering the steady state? An application to Swedish inflation and interest rate," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(1), pages 41-51.
    2. Heinisch, Katja, 2016. "A real-time analysis on the importance of hard and soft data for nowcasting German GDP," VfS Annual Conference 2016 (Augsburg): Demographic Change 145864, Verein für Socialpolitik / German Economic Association.
    3. Katja Heinisch & Rolf Scheufele, 2019. "Should Forecasters Use Real‐Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, Verein für Socialpolitik, vol. 20(4), pages 170-200, November.
    4. Alessandra Amendola & Vincenzo Candila & Antonio Scognamillo, 2017. "On the influence of US monetary policy on crude oil price volatility," Empirical Economics, Springer, vol. 52(1), pages 155-178, February.
    5. Ryan Ratcliff, 2010. "Predicting nominal exchange rate movements using skewness information from options prices," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 15(1), pages 75-92.

  8. Florian PELGRIN & Alain GUAY & Richard LUGER, 2004. "The New Keynesian Phillips Curve: An empirical assessment," Econometric Society 2004 North American Summer Meetings 418, Econometric Society.

    Cited by:

    1. Choi, Yoonseok, 2021. "Inflation dynamics, the role of inflation at different horizons and inflation uncertainty," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 649-662.
    2. Thorvardur Tjörvi Ólafsson, 2006. "The New Keynesian Phillips Curve: In Search of Improvements and Adaptation to the Open Economy," Economics wp31_tjorvi, Department of Economics, Central bank of Iceland.
    3. Rumler, Fabio, 2005. "Estimates of the open economy New Keynesian Phillips curve for euro area countries," Working Paper Series 496, European Central Bank.
    4. Agénor, Pierre-Richard & Bayraktar, Nihal, 2010. "Contracting models of the Phillips curve empirical estimates for middle-income countries," Journal of Macroeconomics, Elsevier, vol. 32(2), pages 555-570, June.
    5. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Working Papers 22-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    6. FAME,Eric Jondeau, University of Lausanne-HEC & Jean Imbs & Eric Jondeau & Florian Pelgrin, 2006. "Aggregating Phillips Curves," Computing in Economics and Finance 2006 314, Society for Computational Economics.
    7. Gbaguidi, David, 2012. "La courbe de Phillips : temps d’arbitrage et/ou arbitrage de temps," L'Actualité Economique, Société Canadienne de Science Economique, vol. 88(1), pages 87-119, mars.
    8. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Papers 2202.04146, arXiv.org, revised Oct 2024.
    9. Faith Christian Cacnio, 2013. "Analysing inflation dynamics in the Philippines using the new Keynesian Phililips curve," Philippine Review of Economics, University of the Philippines School of Economics and Philippine Economic Society, vol. 50(2), pages 53-82, December.
    10. Frode Brevik & Manfred Gärtner, 2005. "Partisan Theory and the New Keynesian and Sticky-Information Phillips Curves," University of St. Gallen Department of Economics working paper series 2005 2005-25, Department of Economics, University of St. Gallen.
    11. Mohamed Boutahar & David Gbaguidi, 2009. "Which Econometric Specification to Characterize the U.S. Inflation Rate Process?," Computational Economics, Springer;Society for Computational Economics, vol. 34(2), pages 145-172, September.
    12. Fructuoso Borrallo Egea & Pedro del Río López, 2021. "Monetary policy strategy and inflation in Japan," Occasional Papers 2116, Banco de España.

  9. René Garcia & Richard Luger & Eric Renault, 2001. "Asymmetric Smiles, Leverage Effects and Structural Parameters," CIRANO Working Papers 2001s-01, CIRANO.

    Cited by:

    1. Garcia, Rene & Luger, Richard & Renault, Eric, 2003. "Empirical assessment of an intertemporal option pricing model with latent variables," Journal of Econometrics, Elsevier, vol. 116(1-2), pages 49-83.
    2. Ali Alami & Eric Renault, 2001. "Risque de modèle de volatilité," CIRANO Working Papers 2001s-06, CIRANO.
    3. Bertholon, H. & Monfort, A. & Pegoraro, F., 2007. "Pricing and Inference with Mixtures of Conditionally Normal Processes," Working papers 188, Banque de France.
    4. Fousseni Chabi-Yo & René Garcia & Eric Renault, 2005. "State Dependence in Fundamentals and Preferences Explains Risk-Aversion Puzzle," Staff Working Papers 05-9, Bank of Canada.
    5. Nour Meddahi, 2001. "An Eigenfunction Approach for Volatility Modeling," CIRANO Working Papers 2001s-70, CIRANO.
    6. René Garcia & Richard Luger & Éric Renault, 2005. "Viewpoint: Option prices, preferences, and state variables," Canadian Journal of Economics, Canadian Economics Association, vol. 38(1), pages 1-27, February.
    7. Luca Benzoni & Pierre Collin-Dufresne & Robert S. Goldstein, 2010. "Explaining asset pricing puzzles associated with the 1987 market crash," Working Paper Series WP-2010-10, Federal Reserve Bank of Chicago.
    8. GARCIA, René & RENAULT, Éric, 2000. "Latent Variable Models for Stochastic Discount Factors," Cahiers de recherche 2000-01, Universite de Montreal, Departement de sciences economiques.
    9. Daglish, Toby & Maheu, John & McCurdy, Tom, 2008. "A Financial Metric for Comparing Volatility Models: Do Better Models Make Money?," Working Paper Series 19110, Victoria University of Wellington, The New Zealand Institute for the Study of Competition and Regulation.
    10. Almut E. D. Veraart, 2008. "Impact of time–inhomogeneous jumps and leverage type effects on returns and realised variances," CREATES Research Papers 2008-57, Department of Economics and Business Economics, Aarhus University.
    11. Alexander David & Pietro Veronesi, 1998. "Option Prices with Uncertain Fundamentals: Theory and Evidence on the Dynamics of Implied Volatilities," CRSP working papers 485, Center for Research in Security Prices, Graduate School of Business, University of Chicago.
    12. Anindya Biswas & Biswajit Mandal, 2016. "Estimating Preference Parameters From Stock Returns Using Simulated Method Of Moments," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 11(01), pages 1-13, March.
    13. René Garcia & Richard Luger & Eric Renault, 2001. "Empirical Assessment of an Intertemporal Option Pricing Model with Latent Variables (Note : Nouvelle version Février 2002)," CIRANO Working Papers 2001s-02, CIRANO.
    14. Frederik Lundtofte, 2010. "Implied volatility and risk aversion in a simple model with uncertain growth," Economics Bulletin, AccessEcon, vol. 30(1), pages 182-191.

  10. Richard Luger, 2001. "Exact Non-Parametric Tests for a Random Walk with Unknown Drift under Conditional Heteroscedasticity," Staff Working Papers 01-2, Bank of Canada.

    Cited by:

    1. Paulo M. M. Rodrigues & Antonio Rubia, 2004. "On the Small Sample Properties of Dickey Fuller and Maximum Likelihood Unit Root Tests on Discrete-Sampled Short-Term Interest Rates," Econometrics 0405004, University Library of Munich, Germany.
    2. Marc Hallin & Ramon van den Akker & Bas Werker, 2009. "A class of Simple Semiparametrically Efficient Rank-Based Unit Root Tests," Working Papers ECARES 2009_001, ULB -- Universite Libre de Bruxelles.
    3. Jorge Belaire-Franch & Kwaku Opong, 2013. "A Time Series Analysis of U.K. Construction and Real Estate Indices," The Journal of Real Estate Finance and Economics, Springer, vol. 46(3), pages 516-542, April.
    4. Shyh-wei Chen, 2009. "Random walks in asian foreign exchange markets:evidence from new multiple variance ratio tests," Economics Bulletin, AccessEcon, vol. 29(2), pages 1296-1307.
    5. Kaveh Salehzadeh Nobari, 2021. "Pair copula constructions of point-optimal sign-based tests for predictive linear and nonlinear regressions," Papers 2111.04919, arXiv.org.
    6. Seok Young Hong & Oliver Linton & Hui Jun Zhang, 2014. "Multivariate variance ratio statistics," CeMMAP working papers 29/14, Institute for Fiscal Studies.
    7. Mobarek, Asma & Fiorante, Angelo, 2014. "The prospects of BRIC countries: Testing weak-form market efficiency," Research in International Business and Finance, Elsevier, vol. 30(C), pages 217-232.
    8. Jui-Cheng Hung & Yen-Hsien Lee & Tung-Yueh Pai, 2009. "Examining market efficiency for large- and small-capitalization of TOPIX and FTSE stock indices," Applied Financial Economics, Taylor & Francis Journals, vol. 19(9), pages 735-744.
    9. Hallin, M. & van den Akker, R. & Werker, B.J.M., 2011. "A Class of Simple Distribution-free Rank-based Unit Root Tests (Revision of DP 2010-72)," Discussion Paper 2011-002, Tilburg University, Center for Economic Research.
    10. Hung, Jui-Cheng, 2009. "Deregulation and liberalization of the Chinese stock market and the improvement of market efficiency," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(3), pages 843-857, August.
    11. Gungor, Sermin & Luger, Richard, 2009. "Exact distribution-free tests of mean-variance efficiency," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 816-829, December.
    12. Arjoon, Vaalmikki, 2016. "Microstructures, financial reforms and informational efficiency in an emerging market," Research in International Business and Finance, Elsevier, vol. 36(C), pages 112-126.
    13. Amélie Charles & Olivier Darné, 2009. "Variance‐Ratio Tests Of Random Walk: An Overview," Journal of Economic Surveys, Wiley Blackwell, vol. 23(3), pages 503-527, July.
    14. Marc Hallin & Ramon van den Akker & Bas J.M. Werker, 2011. "A class of simple distribution-free rank-based unit root tests," Post-Print hal-00834424, HAL.
    15. Ntim, Collins G. & English, John & Nwachukwu, Jacinta & Wang, Yan, 2015. "On the efficiency of the global gold markets," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 218-236.
    16. Belaire-Franch, Jorge & Opong, Kwaku K., 2005. "Some evidence of random walk behavior of Euro exchange rates using ranks and signs," Journal of Banking & Finance, Elsevier, vol. 29(7), pages 1631-1643, July.
    17. Seok Young Hong & Oliver Linton & Hui Jun Zhang, 2015. "An investigation into Multivariate Variance Ratio Statistics and their application to Stock Market Predictability," Cambridge Working Papers in Economics 1552, Faculty of Economics, University of Cambridge.
    18. Brown, Donald & Ibragimov, Rustam, 2019. "Sign tests for dependent observations," Econometrics and Statistics, Elsevier, vol. 10(C), pages 1-8.

  11. René Garcia & Richard Luger & Eric Renault, 2000. "Empirical Assessment of an Intertemporal Option Pricing Model with Latent Variables," Working Papers 2000-56, Center for Research in Economics and Statistics.

    Cited by:

    1. Fearghal Kearney & Han Lin Shang & Lisa Sheenan, 2019. "Implied volatility surface predictability: the case of commodity markets," Papers 1909.11009, arXiv.org.
    2. Bertholon, H. & Monfort, A. & Pegoraro, F., 2008. "Econometric Asset Pricing Modelling," Working papers 223, Banque de France.
    3. David Backus & Mikhail Chernov & Ian Martin, 2009. "Disasters implied by equity index options," NBER Working Papers 15240, National Bureau of Economic Research, Inc.
    4. René Garcia & Richard Luger, 2007. "The Canadian macroeconomy and the yield curve: an equilibrium-based approach," Canadian Journal of Economics, Canadian Economics Association, vol. 40(2), pages 561-583, May.
    5. Chalamandaris, Georgios & Tsekrekos, Andrianos E., 2010. "Predictable dynamics in implied volatility surfaces from OTC currency options," Journal of Banking & Finance, Elsevier, vol. 34(6), pages 1175-1188, June.
    6. James D. Hamilton, 2016. "Macroeconomic Regimes and Regime Shifts," NBER Working Papers 21863, National Bureau of Economic Research, Inc.
    7. Laurent-Emmanuel Calvet & Adlai J. Fisher, 2008. "Multifrequency jump-diffusions: An equilibrium approach," Post-Print hal-00459681, HAL.
    8. Sergei Koulayev & Marc Rysman & Scott Schuh & Joanna Stavins, 2016. "Explaining adoption and use of payment instruments by US consumers," RAND Journal of Economics, RAND Corporation, vol. 47(2), pages 293-325, May.
    9. Peter Christoffersen & Kris Jacobs, 2003. "The Importance of the Loss Function in Option Valuation," CIRANO Working Papers 2003s-52, CIRANO.
    10. Bertholon, H. & Monfort, A. & Pegoraro, F., 2007. "Pricing and Inference with Mixtures of Conditionally Normal Processes," Working papers 188, Banque de France.
    11. Araújo, Fabio & Issler, João Victor, 2011. "A stochastic discount factor approach to asset pricing using panel data asymptotics," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 717, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    12. Godin, Frédéric & Trottier, Denis-Alexandre, 2021. "Option pricing in regime-switching frameworks with the Extended Girsanov Principle," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 116-129.
    13. Nestor Gandelman & Rubén Hernández-Murillo, 2014. "Risk aversion at the country level," Documentos de Investigación 98, Universidad ORT Uruguay. Facultad de Administración y Ciencias Sociales.
    14. René Garcia & Richard Luger & Eric Renault, 2001. "Asymmetric Smiles, Leverage Effects and Structural Parameters," CIRANO Working Papers 2001s-01, CIRANO.
    15. Le, Van & Zurbruegg, Ralf, 2014. "Forecasting option smile dynamics," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 32-45.
    16. Grith, Maria & Karl Härdle, Wolfgang & Krätschmer, Volker, 2013. "Reference dependent preferences and the EPK puzzle," SFB 649 Discussion Papers 2013-023, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    17. Gandelman, Néstor & Hernández-Murillo, Rubén, 2013. "What do happiness and health satisfaction data tell us about relative risk aversion?," Journal of Economic Psychology, Elsevier, vol. 39(C), pages 301-312.
    18. George M. Constantinides & Jens Carsten Jackwerth & Stylianos Perrakis, 2009. "Mispricing of S&P 500 Index Options," The Review of Financial Studies, Society for Financial Studies, vol. 22(3), pages 1247-1277, March.
    19. Elminejad, Ali & Havranek, Tomas & Irsova, Zuzana, 2022. "Relative Risk Aversion: A Meta-Analysis," MetaArXiv b8uhe, Center for Open Science.
    20. Frédéric Godiny & Van Son Lai & Denis-Alexandre Trottier, 2019. "Option Pricing Under Regime-Switching Models: Novel Approaches Removing Path-Dependence," Working Papers 2019-014, Department of Research, Ipag Business School.
    21. Constantinides, George M. & Jackwerth, Jens Carsten & Perrakis, Stylianos, 2007. "Option Pricing: Real and Risk-Neutral Distributions," MPRA Paper 11637, University Library of Munich, Germany.
    22. Sergio Pastorello & Valentin Patilea & Eric Renault, 2003. "Iterative and Recursive Estimation in Structural Non-Adaptive Models," CIRANO Working Papers 2003s-08, CIRANO.
    23. René Garcia & Richard Luger & Éric Renault, 2005. "Viewpoint: Option prices, preferences, and state variables," Canadian Journal of Economics, Canadian Economics Association, vol. 38(1), pages 1-27, February.
    24. Han, Hyojin & Khrapov, Stanislav & Renault, Eric, 2020. "The leverage effect puzzle revisited: Identification in discrete time," Journal of Econometrics, Elsevier, vol. 217(2), pages 230-258.
    25. Carol Alexandra & Emese Lazar, 2005. "The Continuous Limit of GARCH Processess," ICMA Centre Discussion Papers in Finance icma-dp2004-09, Henley Business School, University of Reading, revised Jul 2004.
    26. Shang, Han Lin & Kearney, Fearghal, 2022. "Dynamic functional time-series forecasts of foreign exchange implied volatility surfaces," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1025-1049.
    27. Sílvia Gonçalves & Massimo Guidolin, 2006. "Predictable Dynamics in the S&P 500 Index Options Implied Volatility Surface," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1591-1636, May.
    28. Tao Li, 2013. "Investors' Heterogeneity and Implied Volatility Smiles," Management Science, INFORMS, vol. 59(10), pages 2392-2412, October.
    29. Luca Benzoni & Pierre Collin-Dufresne & Robert S. Goldstein, 2010. "Explaining asset pricing puzzles associated with the 1987 market crash," Working Paper Series WP-2010-10, Federal Reserve Bank of Chicago.
    30. Fabozzi, Frank J. & Leccadito, Arturo & Tunaru, Radu S., 2014. "Extracting market information from equity options with exponential Lévy processes," Journal of Economic Dynamics and Control, Elsevier, vol. 38(C), pages 125-141.
    31. Banerjee, Ameet Kumar & Pradhan, H.K. & Akhtaruzzaman, Md & Sensoy, Ahmet & Dann, Susan, 2024. "Anatomy of sovereign yield behaviour using textual news," Research in International Business and Finance, Elsevier, vol. 71(C).
    32. Chourdakis, Kyriakos & Dendramis, Yiannis & Tzavalis, Elias, 2014. "Are regime-shift sources of risk priced in the market?," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 151-170.
    33. Marianna Oliskevych & Iryna Lukianenko, 2020. "European unemployment nonlinear dynamics over the business cycles: Markov switching approach," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 22(4), pages 375-401.
    34. Parro, Francisco, 2024. "Unveiling the impact of income taxes on inequality in a HACT model," Journal of Macroeconomics, Elsevier, vol. 79(C).
    35. Johanna Etner, 2006. "A Note on the Relation between Risk Aversion, Intertemporal Substitution and Timing of the Resolution of Uncertainty," Annals of Economics and Finance, Society for AEF, vol. 7(2), pages 251-256, November.
    36. Backus, David & Zin, Stanley E. & Chernov, Mikhail, 2011. "Sources of entropy in representative agent models," CEPR Discussion Papers 8488, C.E.P.R. Discussion Papers.
    37. Aivazian, Sergey & Bereznyatskiy, Alexander & Brodsky, Boris & Darkhovsky, Boris, 2015. "Statistical analysis of variable-structure models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 84-105.
    38. Steven Heston & Kris Jacobs & Hyung Joo Kim, 2023. "The Pricing Kernel in Options," Finance and Economics Discussion Series 2023-053, Board of Governors of the Federal Reserve System (U.S.).
    39. Shaliastovich, Ivan, 2015. "Learning, confidence, and option prices," Journal of Econometrics, Elsevier, vol. 187(1), pages 18-42.
    40. Daglish, Toby & Maheu, John & McCurdy, Tom, 2008. "A Financial Metric for Comparing Volatility Models: Do Better Models Make Money?," Working Paper Series 19110, Victoria University of Wellington, The New Zealand Institute for the Study of Competition and Regulation.
    41. René Garcia & Richard Luger, 2009. "Risk Aversion, Intertemporal Substitution, and the Term Structure of Interest Rates," CIRANO Working Papers 2009s-20, CIRANO.
    42. Liao, Wen Ju & Sung, Hao-Chang, 2020. "Implied risk aversion and pricing kernel in the FTSE 100 index," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    43. Horatio Cuesdeanu & Jens Carsten Jackwerth, 2018. "The pricing kernel puzzle: survey and outlook," Annals of Finance, Springer, vol. 14(3), pages 289-329, August.
    44. Badescu, Alexandru M. & Kulperger, Reg J., 2008. "GARCH option pricing: A semiparametric approach," Insurance: Mathematics and Economics, Elsevier, vol. 43(1), pages 69-84, August.
    45. René Garcia & Eric Ghysels & Eric Renault, 2004. "The Econometrics of Option Pricing," CIRANO Working Papers 2004s-04, CIRANO.
    46. Georgios Chalamandaris & Andrianos Tsekrekos, 2013. "Explanatory Factors and Causality in the Dynamics of Volatility Surfaces Implied from OTC Asian–Pacific Currency Options," Computational Economics, Springer;Society for Computational Economics, vol. 41(3), pages 327-358, March.
    47. Cesteros, Santiago Rodrigo, 2018. "Sobre volatilidad macroeconómica y dolarización de la riqueza: el caso argentino [On macroeconomic volatility and wealth dollarization: the Argentine case]," MPRA Paper 88968, University Library of Munich, Germany.
    48. Bildirici, Melike & Ersin, Özgür, 2012. "Nonlinear volatility models in economics: smooth transition and neural network augmented GARCH, APGARCH, FIGARCH and FIAPGARCH models," MPRA Paper 40330, University Library of Munich, Germany, revised May 2012.
    49. Anindya Biswas & Biswajit Mandal, 2016. "Estimating Preference Parameters From Stock Returns Using Simulated Method Of Moments," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 11(01), pages 1-13, March.
    50. Bjørn Eraker & Ivan Shaliastovich, 2008. "An Equilibrium Guide To Designing Affine Pricing Models," Mathematical Finance, Wiley Blackwell, vol. 18(4), pages 519-543, October.
    51. Peters, R. & van der Weide, R., 2012. "Volatility: Expectations and Realizations," CeNDEF Working Papers 12-04, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    52. Wan-Ni Lai, 2014. "Comparison of methods to estimate option implied risk-neutral densities," Quantitative Finance, Taylor & Francis Journals, vol. 14(10), pages 1839-1855, October.
    53. Elminejad, Ali & Havranek, Tomas & Irsova, Zuzana, 2022. "Relative Risk Aversion: A Meta-Analysis," MetaArXiv b8uhe_v1, Center for Open Science.
    54. Shengli Chen & Zili Zhang, 2019. "Forecasting Implied Volatility Smile Surface via Deep Learning and Attention Mechanism," Papers 1912.11059, arXiv.org.
    55. Szabolcs Blazsek & Anna Downarowicz, 2008. "Regime switching models of hedge fund returns," Faculty Working Papers 12/08, School of Economics and Business Administration, University of Navarra.

Articles

  1. Gungor, Sermin & Luger, Richard, 2020. "Small-sample tests for stock return predictability with possibly non-stationary regressors and GARCH-type effects," Journal of Econometrics, Elsevier, vol. 218(2), pages 750-770.

    Cited by:

    1. Yijie Fei & Yiu Lim Lui & Jun Yu, 2024. "Testing Predictability in the Presence of Persistent Errors," Working Papers 202401, University of Macau, Faculty of Business Administration.
    2. Pitarakis, Jean-Yves, 2019. "Predictive Regressions," UC3M Working papers. Economics 28554, Universidad Carlos III de Madrid. Departamento de Economía.
    3. Christis Katsouris, 2023. "Predictability Tests Robust against Parameter Instability," Papers 2307.15151, arXiv.org.
    4. Giraldo, Carlos & Giraldo, Iader & Gomez-Gonzalez, Jose E. & Uribe, Jorge M., 2024. "Term Spread Spillovers to Latin America and Emergence of the ‘Twin Ds’," Documentos de trabajo 21169, FLAR.
    5. Fu, Hsuan & Luger, Richard, 2022. "Multiple testing of the forward rate unbiasedness hypothesis across currencies," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 232-245.

  2. Liu Xiaochun & Luger Richard, 2018. "Markov-switching quantile autoregression: a Gibbs sampling approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(2), pages 1, April.

    Cited by:

    1. Liu, Xiaochun, 2013. "Markov-Switching Quantile Autoregression," MPRA Paper 55800, University Library of Munich, Germany.
    2. Yunmi Kim & Lijuan Huo & Tae-Hwan Kim, 2020. "Dealing with Markov-Switching Parameters in Quantile Regression Models," Working papers 2020rwp-166, Yonsei University, Yonsei Economics Research Institute.
    3. Maruotti, Antonello & Petrella, Lea & Sposito, Luca, 2021. "Hidden semi-Markov-switching quantile regression for time series," Computational Statistics & Data Analysis, Elsevier, vol. 159(C).
    4. Donald Lien & Ziling Wang & Xiaojian Yu, 2021. "Optimal quantile hedging under Markov regime switching," Empirical Economics, Springer, vol. 60(5), pages 2177-2201, May.

  3. Jean-Marie Dufour & Richard Luger, 2017. "Identification-robust moment-based tests for Markov switching in autoregressive models," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 713-727, October.
    See citations under working paper version above.
  4. Sermin Gungor & Richard Luger, 2016. "Multivariate Tests of Mean-Variance Efficiency and Spanning With a Large Number of Assets and Time-Varying Covariances," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(2), pages 161-175, April. See citations under working paper version above.
  5. Gungor, Sermin & Luger, Richard, 2015. "Bootstrap Tests Of Mean-Variance Efficiency With Multiple Portfolio Groupings," L'Actualité Economique, Société Canadienne de Science Economique, vol. 91(1-2), pages 35-65, Mars-Juin.
    See citations under working paper version above.
  6. Liu, Xiaochun & Luger, Richard, 2015. "Unfolded GARCH models," Journal of Economic Dynamics and Control, Elsevier, vol. 58(C), pages 186-217.

    Cited by:

    1. Sylvia J. Soltyk & Felix Chan, 2023. "Modeling time‐varying higher‐order conditional moments: A survey," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 33-57, February.
    2. Stanislav Anatolyev, 2021. "Directional news impact curve," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 94-107, January.
    3. Liu, Xiaochun, 2017. "Unfolded risk-return trade-offs and links to Macroeconomic Dynamics," Journal of Banking & Finance, Elsevier, vol. 82(C), pages 1-19.
    4. Fiszeder, Piotr & Małecka, Marta & Molnár, Peter, 2024. "Robust estimation of the range-based GARCH model: Forecasting volatility, value at risk and expected shortfall of cryptocurrencies," Economic Modelling, Elsevier, vol. 141(C).
    5. Xiaochun Liu, 2017. "An integrated macro‐financial risk‐based approach to the stressed capital requirement," Review of Financial Economics, John Wiley & Sons, vol. 34(1), pages 86-98, September.
    6. Stanislav Anatolyev & Nikolay Gospodinov, 2015. "Multivariate return decomposition: theory and implications," FRB Atlanta Working Paper 2015-7, Federal Reserve Bank of Atlanta.
    7. Xiaochun Liu, 2018. "Structural Volatility Impulse Response Function and Asymptotic Inference," Journal of Financial Econometrics, Oxford University Press, vol. 16(2), pages 316-339.
    8. Liu, Xiaochun, 2019. "On tail fatness of macroeconomic dynamics," Journal of Macroeconomics, Elsevier, vol. 62(C).
    9. Liu, Xiaochun, 2017. "Can macroeconomic dynamics explain the time variation of risk–return trade-offs in the U.S. financial market?," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 275-293.
    10. León, Ángel & Ñíguez, Trino-Manuel, 2021. "The transformed Gram Charlier distribution: Parametric properties and financial risk applications," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 323-349.
    11. You, Yu & Liu, Xiaochun, 2020. "Forecasting short-run exchange rate volatility with monetary fundamentals: A GARCH-MIDAS approach," Journal of Banking & Finance, Elsevier, vol. 116(C).
    12. Simon Lalancette & Jean†Guy Simonato, 2017. "The Role of the Conditional Skewness and Kurtosis in VIX Index Valuation," European Financial Management, European Financial Management Association, vol. 23(2), pages 325-354, March.

  7. Sermin Gungor & Richard Luger, 2013. "Testing Linear Factor Pricing Models With Large Cross Sections: A Distribution-Free Approach," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(1), pages 66-77, January.

    Cited by:

    1. Sermin Gungor & Richard Luger, 2013. "Multivariate Tests of Mean-Variance Efficiency and Spanning with a Large Number of Assets and Time-Varying Covariances," Staff Working Papers 13-16, Bank of Canada.
    2. Pesaran, M. H. & Yamagata, T., 2012. "Testing CAPM with a Large Number of Assets (Updated 28th March 2012)," Cambridge Working Papers in Economics 1210, Faculty of Economics, University of Cambridge.
    3. Fan, Jianqing & Ke, Yuan & Liao, Yuan, 2021. "Augmented factor models with applications to validating market risk factors and forecasting bond risk premia," Journal of Econometrics, Elsevier, vol. 222(1), pages 269-294.
    4. Mardy Chiah & Daniel Chai & Angel Zhong & Song Li, 2016. "A Better Model? An Empirical Investigation of the Fama–French Five-factor Model in Australia," International Review of Finance, International Review of Finance Ltd., vol. 16(4), pages 595-638, December.
    5. M Hashem Pesaran & Takashi Yamagata, 2012. "Testing CAPM with a Large Number of Assets," Discussion Papers 12/05, Department of Economics, University of York.
    6. Auld, T., 2022. "Political markets as equity price factors," Cambridge Working Papers in Economics 2264, Faculty of Economics, University of Cambridge.
    7. Sermin Gungor & Richard Luger, 2014. "Bootstrap Tests of Mean-Variance Efficiency with Multiple Portfolio Groupings," Staff Working Papers 14-51, Bank of Canada.
    8. Daniele Bianchi & Massimo Guidolin & Francesco Ravazzolo, 2013. "Macroeconomic factors strike back: A Bayesian change-point model of time-varying risk exposures and premia in the U.S. cross-section," Working Paper 2013/19, Norges Bank.
    9. Yu, Xiufan & Yao, Jiawei & Xue, Lingzhou, 2024. "Power enhancement for testing multi-factor asset pricing models via Fisher’s method," Journal of Econometrics, Elsevier, vol. 239(2).

  8. Luger, Richard, 2012. "Finite-sample bootstrap inference in GARCH models with heavy-tailed innovations," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3198-3211.

    Cited by:

    1. Spierdijk, Laura, 2016. "Confidence intervals for ARMA–GARCH Value-at-Risk: The case of heavy tails and skewness," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 545-559.
    2. Fernanda Maria Müller & Fábio M Bayer, 2017. "Improved two-component tests in Beta-Skew-t-EGARCH models," Economics Bulletin, AccessEcon, vol. 37(4), pages 2364-2373.
    3. Bernardina Algieri & Arturo Leccadito & Pietro Toscano, 2021. "A Time-Varying Gerber Statistic: Application of a Novel Correlation Metric to Commodity Price Co-Movements," Forecasting, MDPI, vol. 3(2), pages 1-16, May.
    4. Szczygielski, Jan Jakub & Brzeszczyński, Janusz & Charteris, Ailie & Bwanya, Princess Rutendo, 2022. "The COVID-19 storm and the energy sector: The impact and role of uncertainty," Energy Economics, Elsevier, vol. 109(C).
    5. Bal'azs Csan'ad Cs'aji, 2018. "Score Permutation Based Finite Sample Inference for Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) Models," Papers 1807.08390, arXiv.org.
    6. Ghoudi, Kilani & Rémillard, Bruno, 2014. "Comparison of specification tests for GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 291-300.
    7. Liu, Xiaochun & Luger, Richard, 2015. "Unfolded GARCH models," Journal of Economic Dynamics and Control, Elsevier, vol. 58(C), pages 186-217.

  9. René Garcia & Richard Luger, 2012. "Risk aversion, intertemporal substitution, and the term structure of interest rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(6), pages 1013-1036, September. See citations under working paper version above.
  10. Liu, Yan & Luger, Richard, 2009. "Efficient estimation of copula-GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2284-2297, April.

    Cited by:

    1. Wang Ruihua & Wang Hongjun, 2020. "Correlation Analysis of Stock Market and Fund Market Based on M-Copula-EGARCH-M-GED Model," Journal of Systems Science and Information, De Gruyter, vol. 8(3), pages 240-252, June.
    2. Ruili Sun & Tiefeng Ma & Shuangzhe Liu & Milind Sathye, 2019. "Improved Covariance Matrix Estimation for Portfolio Risk Measurement: A Review," JRFM, MDPI, vol. 12(1), pages 1-34, March.
    3. Bodnar, Taras & Hautsch, Nikolaus, 2016. "Dynamic conditional correlation multiplicative error processes," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 41-67.
    4. Brechmann, Eike C. & Hendrich, Katharina & Czado, Claudia, 2013. "Conditional copula simulation for systemic risk stress testing," Insurance: Mathematics and Economics, Elsevier, vol. 53(3), pages 722-732.
    5. Brechmann Eike Christain & Czado Claudia, 2013. "Risk management with high-dimensional vine copulas: An analysis of the Euro Stoxx 50," Statistics & Risk Modeling, De Gruyter, vol. 30(4), pages 307-342, December.
    6. David T. Frazierz & Eric Renault, 2016. "Efficient Two-Step Estimation via Targeting," CIRANO Working Papers 2016s-16, CIRANO.
    7. Paolella, Marc S. & Polak, Paweł, 2015. "ALRIGHT: Asymmetric LaRge-scale (I)GARCH with Hetero-Tails," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 282-297.
    8. Martin Burda & Louis Belisle, 2019. "Copula Multivariate GARCH Model with Constrained Hamiltonian Monte Carlo," Working Papers tecipa-638, University of Toronto, Department of Economics.
    9. Burda Martin & Bélisle Louis, 2019. "Copula multivariate GARCH model with constrained Hamiltonian Monte Carlo," Dependence Modeling, De Gruyter, vol. 7(1), pages 133-149, January.
    10. Nikolaus Hautsch & Ostap Okhrin & Alexander Ristig, 2023. "Maximum-Likelihood Estimation Using the Zig-Zag Algorithm," Journal of Financial Econometrics, Oxford University Press, vol. 21(4), pages 1346-1375.
    11. Hafner, Christian & Reznikova, Olga, 2010. "Efficient estimation of a semiparametric dynamic copula model," LIDAM Reprints ISBA 2010033, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    12. Weiß, Gregor N.F. & Scheffer, Marcus, 2015. "Mixture pair-copula-constructions," Journal of Banking & Finance, Elsevier, vol. 54(C), pages 175-191.
    13. Bodnar, Taras & Hautsch, Nikolaus, 2013. "Copula-based dynamic conditional correlation multiplicative error processes," CFS Working Paper Series 2013/19, Center for Financial Studies (CFS).
    14. Nikoloulopoulos, Aristidis K. & Joe, Harry & Li, Haijun, 2012. "Vine copulas with asymmetric tail dependence and applications to financial return data," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3659-3673.
    15. Arthur Charpentier, 2015. "Prévision avec des copules en finance," Working Papers hal-01151233, HAL.
    16. Alp, Tansel & Demetrescu, Matei, 2010. "Joint forecasts of Dow Jones stocks under general multivariate loss function," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2360-2371, November.
    17. Bai, Xiwen & Lam, Jasmine Siu Lee, 2019. "A copula-GARCH approach for analyzing dynamic conditional dependency structure between liquefied petroleum gas freight rate, product price arbitrage and crude oil price," Energy Economics, Elsevier, vol. 78(C), pages 412-427.
    18. Gregor Weiß, 2013. "Copula-GARCH versus dynamic conditional correlation: an empirical study on VaR and ES forecasting accuracy," Review of Quantitative Finance and Accounting, Springer, vol. 41(2), pages 179-202, August.
    19. Silva Filho, Osvaldo Candido da & Ziegelmann, Flavio Augusto & Dueker, Michael J., 2012. "Modeling dependence dynamics through copulas with regime switching," Insurance: Mathematics and Economics, Elsevier, vol. 50(3), pages 346-356.
    20. Yan Cui & Qi Li & Fukang Zhu, 2020. "Flexible bivariate Poisson integer-valued GARCH model," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(6), pages 1449-1477, December.
    21. Zhang, Ran & Czado, Claudia & Min, Aleksey, 2011. "Efficient maximum likelihood estimation of copula based meta t-distributions," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1196-1214, March.
    22. Almeida, Carlos & Czado, Claudia, 2012. "Efficient Bayesian inference for stochastic time-varying copula models," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1511-1527.
    23. Brechmann, Eike C. & Joe, Harry, 2015. "Truncation of vine copulas using fit indices," Journal of Multivariate Analysis, Elsevier, vol. 138(C), pages 19-33.
    24. Frazier, David T. & Renault, Eric, 2017. "Efficient two-step estimation via targeting," Journal of Econometrics, Elsevier, vol. 201(2), pages 212-227.
    25. Spanhel, Fabian & Kurz, Malte S., 2016. "The partial copula: Properties and associated dependence measures," Statistics & Probability Letters, Elsevier, vol. 119(C), pages 76-83.
    26. Ausin, M. Concepcion & Lopes, Hedibert F., 2010. "Time-varying joint distribution through copulas," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2383-2399, November.

  11. Gungor, Sermin & Luger, Richard, 2009. "Exact distribution-free tests of mean-variance efficiency," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 816-829, December.

    Cited by:

    1. Sermin Gungor & Richard Luger, 2013. "Multivariate Tests of Mean-Variance Efficiency and Spanning with a Large Number of Assets and Time-Varying Covariances," Staff Working Papers 13-16, Bank of Canada.
    2. David Ardia & S'ebastien Laurent & Rosnel Sessinou, 2024. "High-Dimensional Mean-Variance Spanning Tests," Papers 2403.17127, arXiv.org.
    3. Pesaran, M. H. & Yamagata, T., 2012. "Testing CAPM with a Large Number of Assets (Updated 28th March 2012)," Cambridge Working Papers in Economics 1210, Faculty of Economics, University of Cambridge.
    4. M. Hashem Pesaran & Takashi Yamagata, 2017. "Testing for Alpha in Linear Factor Pricing Models with a Large Number of Securities," Discussion Papers 17/04, Department of Economics, University of York.
    5. Beaulieu, Marie-Claude & Dufour, Jean-Marie & Khalaf, Lynda, 2010. "Asset-pricing anomalies and spanning: Multivariate and multifactor tests with heavy-tailed distributions," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 763-782, September.
    6. Dufour, Jean-Marie & Khalaf, Lynda & Kichian, Maral, 2013. "Identification-robust analysis of DSGE and structural macroeconomic models," Journal of Monetary Economics, Elsevier, vol. 60(3), pages 340-350.
    7. M Hashem Pesaran & Takashi Yamagata, 2012. "Testing CAPM with a Large Number of Assets," Discussion Papers 12/05, Department of Economics, University of York.
    8. Auld, T., 2022. "Political markets as equity price factors," Cambridge Working Papers in Economics 2264, Faculty of Economics, University of Cambridge.

  12. René Garcia & Richard Luger, 2007. "The Canadian macroeconomy and the yield curve: an equilibrium-based approach," Canadian Journal of Economics, Canadian Economics Association, vol. 40(2), pages 561-583, May.
    See citations under working paper version above.
  13. Luger, Richard, 2006. "Exact permutation tests for non-nested non-linear regression models," Journal of Econometrics, Elsevier, vol. 133(2), pages 513-529, August.

    Cited by:

    1. Achim Zeileis & Torsten Hothorn, 2013. "A toolbox of permutation tests for structural change," Statistical Papers, Springer, vol. 54(4), pages 931-954, November.

  14. René Garcia & Richard Luger & Éric Renault, 2005. "Viewpoint: Option prices, preferences, and state variables," Canadian Journal of Economics, Canadian Economics Association, vol. 38(1), pages 1-27, February.

    Cited by:

    1. Wang, Xiao-Tian & Li, Zhe & Zhuang, Le, 2017. "Risk preference, option pricing and portfolio hedging with proportional transaction costs," Chaos, Solitons & Fractals, Elsevier, vol. 95(C), pages 111-130.
    2. Beare, Brendan K., 2011. "Measure preserving derivatives and the pricing kernel puzzle," Journal of Mathematical Economics, Elsevier, vol. 47(6), pages 689-697.
    3. Han, Hyojin & Khrapov, Stanislav & Renault, Eric, 2020. "The leverage effect puzzle revisited: Identification in discrete time," Journal of Econometrics, Elsevier, vol. 217(2), pages 230-258.

  15. Luger, Richard, 2003. "Exact non-parametric tests for a random walk with unknown drift under conditional heteroscedasticity," Journal of Econometrics, Elsevier, vol. 115(2), pages 259-276, August. See citations under working paper version above.
  16. Garcia, Rene & Luger, Richard & Renault, Eric, 2003. "Empirical assessment of an intertemporal option pricing model with latent variables," Journal of Econometrics, Elsevier, vol. 116(1-2), pages 49-83.
    See citations under working paper version above.
  17. Luger, Richard, 2001. "A modified CUSUM test for orthogonal structural changes," Economics Letters, Elsevier, vol. 73(3), pages 301-306, December.

    Cited by:

    1. Makram El-Shagi & Sebastian Giesen, 2013. "Testing for Structural Breaks at Unknown Time: A Steeplechase," Computational Economics, Springer;Society for Computational Economics, vol. 41(1), pages 101-123, January.
    2. Peiyun Jiang & Eiji Kurozumi, 2019. "Power properties of the modified CUSUM tests," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 48(12), pages 2962-2981, June.
    3. Godolphin, J.D., 2009. "New formulations for recursive residuals as a diagnostic tool in the fixed-effects linear model with design matrices of arbitrary rank," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2119-2128, April.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.