IDEAS home Printed from https://ideas.repec.org/r/fip/fedawp/2013-09.html
   My bibliography  Save this item

Misspecification-robust inference in linear asset pricing models with irrelevant risk factors

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Beaulieu, Marie-Claude & Dufour, Jean-Marie & Khalaf, Lynda & Melin, Olena, 2023. "Identification-robust beta pricing, spanning, mimicking portfolios, and the benchmark neutrality of catastrophe bonds," Journal of Econometrics, Elsevier, vol. 236(1).
  2. Adrian, Tobias & Crump, Richard K. & Moench, Emanuel, 2015. "Regression-based estimation of dynamic asset pricing models," Journal of Financial Economics, Elsevier, vol. 118(2), pages 211-244.
  3. Marie-Claude Beaulieu & Jean-Marie Dufour & Lynda Khalaf, 2020. "Arbitrage Pricing, Weak Beta, Strong Beta: Identification-Robust and Simultaneous Inference," CIRANO Working Papers 2020s-30, CIRANO.
  4. Gospodinov, Nikolay & Kan, Raymond & Robotti, Cesare, 2019. "Too good to be true? Fallacies in evaluating risk factor models," Journal of Financial Economics, Elsevier, vol. 132(2), pages 451-471.
  5. Laurinaityte, Nora & Meinerding, Christoph & Schlag, Christian & Thimme, Julian, 2024. "GMM weighting matrices in cross-sectional asset pricing tests," Journal of Banking & Finance, Elsevier, vol. 162(C).
  6. Antoine, Bertille & Dovonon, Prosper, 2021. "Robust estimation with exponentially tilted Hellinger distance," Journal of Econometrics, Elsevier, vol. 224(2), pages 330-344.
  7. Zhang, Xiang & Liu, Yangyi & Wu, Kun & Maillet, Bertrand, 2021. "Tradable or nontradable factors—what does the Hansen–Jagannathan distance tell us?," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 853-879.
  8. Raymond Kan & Cesare Robotti, 0. "Comment on: Pseudo-True SDFs in Conditional Asset Pricing Models," Journal of Financial Econometrics, Oxford University Press, vol. 18(4), pages 729-735.
  9. Gospodinov, Nikolay & Robotti, Cesare, 2021. "Common pricing across asset classes: Empirical evidence revisited," Journal of Financial Economics, Elsevier, vol. 140(1), pages 292-324.
  10. Barras, Laurent, 2019. "A large-scale approach for evaluating asset pricing models," Journal of Financial Economics, Elsevier, vol. 134(3), pages 549-569.
  11. Bryzgalova, Svetlana & Huang, Jiantao & Julliard, Christian, 2023. "Bayesian solutions for the factor zoo: we just ran two quadrillion models," LSE Research Online Documents on Economics 126151, London School of Economics and Political Science, LSE Library.
  12. Frank Kleibergen & Zhaoguo Zhan, 2022. "Misspecification and Weak Identification in Asset Pricing," Papers 2206.13600, arXiv.org.
  13. Alexis Akira Toda & Kieran James Walsh, 2017. "Fat tails and spurious estimation of consumption‐based asset pricing models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(6), pages 1156-1177, September.
  14. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2018. "Asymptotic variance approximations for invariant estimators in uncertain asset-pricing models," Econometric Reviews, Taylor & Francis Journals, vol. 37(7), pages 695-718, August.
  15. Craig Burnside, 2016. "Identification and Inference in Linear Stochastic Discount Factor Models with Excess Returns," Journal of Financial Econometrics, Oxford University Press, vol. 14(2), pages 295-330.
  16. Esfandiar Maasoumi & Almas Heshmati & Inhee Lee, 2021. "RETRACTED ARTICLE: Green innovations and patenting renewable energy technologies," Empirical Economics, Springer, vol. 60(1), pages 513-538, January.
  17. Antoine Giannetti, 2024. "A simple test of misspecification for linear asset pricing models," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 38(3), pages 305-330, September.
  18. Lin, Qi, 2021. "The q5 model and its consistency with the intertemporal CAPM," Journal of Banking & Finance, Elsevier, vol. 127(C).
  19. Sun, Yang & Zhang, Xuan & Zhang, Zhekai, 2022. "The reduced-rank beta in linear stochastic discount factor models," International Review of Financial Analysis, Elsevier, vol. 84(C).
  20. Svetlana Bryzgalova & Jiantao Huang & Christian Julliard, 2023. "Bayesian Solutions for the Factor Zoo: We Just Ran Two Quadrillion Models," Journal of Finance, American Finance Association, vol. 78(1), pages 487-557, February.
  21. Joachim Freyberger & Andreas Neuhierl & Michael Weber, 2020. "Dissecting Characteristics Nonparametrically," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2326-2377.
  22. Alain-Philippe Fortin & Patrick Gagliardini & O. Scaillet, 2022. "Eigenvalue tests for the number of latent factors in short panels," Swiss Finance Institute Research Paper Series 22-81, Swiss Finance Institute.
  23. Shi, Qi, 2020. "A much robust and updated evidences of the alternative real-estate based asset pricing," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
  24. Kleibergen, Frank & Zhan, Zhaoguo, 2015. "Unexplained factors and their effects on second pass R-squared’s," Journal of Econometrics, Elsevier, vol. 189(1), pages 101-116.
  25. Nikolay Gospodinov & Ibrahim Jamali, 2018. "Monetary policy uncertainty, positions of traders and changes in commodity futures prices," European Financial Management, European Financial Management Association, vol. 24(2), pages 239-260, March.
  26. Patrick Gagliardini & Elisa Ossola & O. Scaillet, 2019. "Estimation of Large Dimensional Conditional Factor Models in Finance," Swiss Finance Institute Research Paper Series 19-46, Swiss Finance Institute.
  27. Stefano Giglio & Dacheng Xiu, 2017. "Inference on Risk Premia in the Presence of Omitted Factors," NBER Working Papers 23527, National Bureau of Economic Research, Inc.
  28. Gagliardini, Patrick & Ossola, Elisa & Scaillet, Olivier, 2019. "A diagnostic criterion for approximate factor structure," Journal of Econometrics, Elsevier, vol. 212(2), pages 503-521.
  29. Gregory Connor & Robert A Korajczyk, 2024. "Semi-Strong Factors in Asset Returns," Journal of Financial Econometrics, Oxford University Press, vol. 22(1), pages 70-93.
  30. Bretscher, Lorenzo & Hsu, Alex & Tamoni, Andrea, 2020. "Fiscal policy driven bond risk premia," Journal of Financial Economics, Elsevier, vol. 138(1), pages 53-73.
  31. Li, Huan, 2020. "Asset pricing with long-run durable expenditure risk," Finance Research Letters, Elsevier, vol. 32(C).
  32. Beaulieu, Marie-Claude & Gagnon, Marie-Hélène & Khalaf, Lynda, 2016. "Less is more: Testing financial integration using identification-robust asset pricing models," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 45(C), pages 171-190.
  33. Wan, Runzhe & Li, Yingying & Lu, Wenbin & Song, Rui, 2024. "Mining the factor zoo: Estimation of latent factor models with sufficient proxies," Journal of Econometrics, Elsevier, vol. 239(2).
  34. Khalaf, Lynda & Schaller, Huntley, 2016. "Identification and inference in two-pass asset pricing models," Journal of Economic Dynamics and Control, Elsevier, vol. 70(C), pages 165-177.
  35. Christoffersen, Peter & Fournier, Mathieu & Jacobs, Kris & Karoui, Mehdi, 2021. "Option-Based Estimation of the Price of Coskewness and Cokurtosis Risk," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 56(1), pages 65-91, February.
  36. Aleksejs Krecetovs & Pasquale Della Corte, 2016. "Macro uncertainty and currency premia," 2016 Meeting Papers 624, Society for Economic Dynamics.
  37. Alain-Philippe Fortin & Patrick Gagliardini & Olivier Scaillet, 2023. "Latent Factor Analysis in Short Panels," Swiss Finance Institute Research Paper Series 23-44, Swiss Finance Institute.
  38. Kim, Jinyong & Kim, Kun Ho & Lee, Jeong Hwan, 2021. "Cross-sectional tests of asset pricing models with full-rank mimicking portfolios," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
  39. Patrick Gagliardini & Diego Ronchetti, 2020. "Comparing Asset Pricing Models by the Conditional Hansen-Jagannathan Distance," Journal of Financial Econometrics, Oxford University Press, vol. 18(2), pages 333-394.
  40. Sun, Chuanping, 2024. "Factor correlation and the cross section of asset returns: A correlation-robust machine learning approach," Journal of Empirical Finance, Elsevier, vol. 77(C).
  41. Lin, Xiaoji & Palazzo, Berardino & Yang, Fan, 2020. "The risks of old capital age: Asset pricing implications of technology adoption," Journal of Monetary Economics, Elsevier, vol. 115(C), pages 145-161.
  42. Laurinaityte, Nora & Meinerding, Christoph & Schlag, Christian & Thimme, Julian, 2020. "GMM weighting matrices incross-sectional asset pricing tests," Discussion Papers 62/2020, Deutsche Bundesbank.
  43. Xyngis, Georgios, 2017. "Business-cycle variation in macroeconomic uncertainty and the cross-section of expected returns: Evidence for scale-dependent risks," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 43-65.
  44. Gospodinov, Nikolay & Kan, Raymond & Robotti, Cesare, 2016. "On the properties of the constrained Hansen–Jagannathan distance," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 121-150.
  45. Momani, Mohammad Q.M., 2018. "Revisiting Pastor–Stambaugh liquidity factor," Economics Letters, Elsevier, vol. 163(C), pages 190-192.
  46. Cisil Sarisoy & Bas J.M. Werker, 2024. "Linear Factor Models and the Estimation of Expected Returns," Finance and Economics Discussion Series 2024-014, Board of Governors of the Federal Reserve System (U.S.).
  47. Bruzda, Joanna, 2019. "Complex analytic wavelets in the measurement of macroeconomic risks," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
  48. Gospodinov, Nikolay & Maasoumi, Esfandiar, 2021. "Generalized aggregation of misspecified models: With an application to asset pricing," Journal of Econometrics, Elsevier, vol. 222(1), pages 451-467.
  49. Shang, Hua & Yuan, Ping & Huang, Lin, 2016. "Macroeconomic factors and the cross-section of commodity futures returns," International Review of Economics & Finance, Elsevier, vol. 45(C), pages 316-332.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.