Autoregressive Random Forests: Machine Learning and Lag Selection for Financial Research
Author
Abstract
Suggested Citation
DOI: 10.1007/s10614-023-10429-9
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Zou, Hui, 2006. "The Adaptive Lasso and Its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1418-1429, December.
- Venus Khim-Sen Liew, 2004. "Which Lag Length Selection Criteria Should We Employ?," Economics Bulletin, AccessEcon, vol. 3(33), pages 1-9.
- T. Speed & Bin Yu, 1993. "Model selection and prediction: Normal regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 45(1), pages 35-54, March.
- Shaofeng Zhang & Wei Xiong & Wancheng Ni & Xin Li, 2015. "Value of big data to finance: observations on an internet credit Service Company in China," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 1(1), pages 1-18, December.
- Elie Bouri & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2021.
"Forecasting Realized Volatility of Bitcoin: The Role of the Trade War,"
Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 29-53, January.
- Elie Bouri & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2020. "Forecasting Realized Volatility of Bitcoin: The Role of the Trade War," Working Papers 202003, University of Pretoria, Department of Economics.
- Nicoletta Batini & Edward Nelson, 2001.
"The Lag from Monetary Policy Actions to Inflation: Friedman Revisited,"
International Finance, Wiley Blackwell, vol. 4(3), pages 381-400.
- Nicoletta Batini & Edward Nelson, 2001. "The Lag from Monetary Policy Actions to Inflation: Friedman Revisited," Discussion Papers 06, Monetary Policy Committee Unit, Bank of England.
- Tomas Havranek & Marek Rusnak, 2013.
"Transmission Lags of Monetary Policy: A Meta-Analysis,"
International Journal of Central Banking, International Journal of Central Banking, vol. 9(4), pages 39-76, December.
- Tomas Havranek & Marek Rusnak, 2012. "Transmission Lags of Monetary Policy: A Meta-Analysis," Working Papers 2012/10, Czech National Bank.
- Tomas Havranek & Marek Rusnak, 2012. "Transmission Lags of Monetary Policy: A Meta-Analysis," William Davidson Institute Working Papers Series wp1038, William Davidson Institute at the University of Michigan.
- Tomas Havranek & Marek Rusnak, 2012. "Transmission Lags of Monetary Policy: A Meta-Analysis," Working Papers IES 2012/27, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Oct 2012.
- Polyzos, Stathis & Samitas, Aristeidis & Katsaiti, Marina-Selini, 2020. "Who is unhappy for Brexit? A machine-learning, agent-based study on financial instability," International Review of Financial Analysis, Elsevier, vol. 72(C).
- Adamek, Robert & Smeekes, Stephan & Wilms, Ines, 2023.
"Lasso inference for high-dimensional time series,"
Journal of Econometrics, Elsevier, vol. 235(2), pages 1114-1143.
- Robert Adamek & Stephan Smeekes & Ines Wilms, 2020. "Lasso Inference for High-Dimensional Time Series," Papers 2007.10952, arXiv.org, revised Sep 2022.
- Mawuli Segnon & Stelios Bekiros, 2020. "Forecasting volatility in bitcoin market," Annals of Finance, Springer, vol. 16(3), pages 435-462, September.
- Jesús Gonzalo & Jean‐Yves Pitarakis, 2002.
"Lag length estimation in large dimensional systems,"
Journal of Time Series Analysis, Wiley Blackwell, vol. 23(4), pages 401-423, July.
- Jesus Gonzalo & Jean-Yves Pitarakis, 2001. "Lag Length Estimation in Large Dimensional Systems," Econometrics 0108003, University Library of Munich, Germany.
- Jesus Gonzalo & Jean-Yves Pitarakis, 2001. "Lag Length Estimation in Large Dimensional Systems," Econometrics 0108002, University Library of Munich, Germany.
- Kock, Anders Bredahl, 2016. "Consistent And Conservative Model Selection With The Adaptive Lasso In Stationary And Nonstationary Autoregressions," Econometric Theory, Cambridge University Press, vol. 32(1), pages 243-259, February.
- J. M. Culbertson, 1960. "Friedman on the Lag in Effect of Monetary Policy," Journal of Political Economy, University of Chicago Press, vol. 68(6), pages 617-617.
- Wenbo Wu & Jiaqi Chen & Liang Xu & Qingyun He & Michael L. Tindall, 2019. "A statistical learning approach for stock selection in the Chinese stock market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-18, December.
- Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2021.
"Forecasting realized volatility of bitcoin returns: tail events and asymmetric loss,"
The European Journal of Finance, Taylor & Francis Journals, vol. 27(16), pages 1626-1644, November.
- Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2019. "Forecasting Realized Volatility of Bitcoin Returns: Tail Events and Asymmetric Loss," Working Papers 201905, University of Pretoria, Department of Economics.
- Babak Fazelabdolabadi, 2019. "A hybrid Bayesian-network proposition for forecasting the crude oil price," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-21, December.
- Godfrey, Leslie G, 1978. "Testing against General Autoregressive and Moving Average Error Models When the Regressors Include Lagged Dependent Variables," Econometrica, Econometric Society, vol. 46(6), pages 1293-1301, November.
- Duguay, Pierre, 1994. "Empirical evidence on the strength of the monetary transmission mechanism in Canada: An aggregate approach," Journal of Monetary Economics, Elsevier, vol. 33(1), pages 39-61, February.
- Swanson, Norman R & Zeng, Tian, 2001. "Choosing among Competing Econometric Forecasts: Regression-Based Forecast Combination Using Model Selection," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(6), pages 425-440, September.
- Angeliki Skoura, 2019. "Detection of Lead-Lag Relationships Using Both Time Domain and Time-Frequency Domain; An Application to Wealth-To-Income Ratio," Economies, MDPI, vol. 7(2), pages 1-27, April.
- Baltagi, Badi H. & Bresson, Georges, 2011.
"Maximum likelihood estimation and Lagrange multiplier tests for panel seemingly unrelated regressions with spatial lag and spatial errors: An application to hedonic housing prices in Paris,"
Journal of Urban Economics, Elsevier, vol. 69(1), pages 24-42, January.
- Baltagi, Badi H. & Bresson, Georges, 2010. "Maximum Likelihood Estimation and Lagrange Multiplier Tests for Panel Seemingly Unrelated Regressions with Spatial Lag and Spatial Errors: An Application to Hedonic Housing Prices in Paris," IZA Discussion Papers 5227, Institute of Labor Economics (IZA).
- Francesco Audrino & Robert Fernholz & Roberto Ferretti, 2007. "A Forecasting Model for Stock Market Diversity," Annals of Finance, Springer, vol. 3(2), pages 213-240, March.
- A. Hatemi-J & R. S. Hacker, 2009. "Can the LR test be helpful in choosing the optimal lag order in the VAR model when information criteria suggest different lag orders?," Applied Economics, Taylor & Francis Journals, vol. 41(9), pages 1121-1125.
- Omer Ozcicek & W. DOUGLAS McMILLIN, 1999. "Lag length selection in vector autoregressive models: symmetric and asymmetric lags," Applied Economics, Taylor & Francis Journals, vol. 31(4), pages 517-524.
- Engle, Robert F., 1984. "Wald, likelihood ratio, and Lagrange multiplier tests in econometrics," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 13, pages 775-826, Elsevier.
- Periklis Gogas & Theophilos Papadimitriou & Emmanouil Sofianos, 2022. "Forecasting unemployment in the euro area with machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 551-566, April.
- Peter Winker, 2000. "Optimized Multivariate Lag Structure Selection," Computational Economics, Springer;Society for Computational Economics, vol. 16(1/2), pages 87-103, October.
- Cagan, Phillip & Gandolfi, Arthur, 1969. "The Lag in Monetary Policy as Implied by the Time Pattern of Monetary Effects on Interest Rates," American Economic Review, American Economic Association, vol. 59(2), pages 277-284, May.
- James H. Stock & Mark W. Watson, 2001. "Vector Autoregressions," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 101-115, Fall.
- Tanner, J. Ernest, 1979. "Are the lags in the effects of monetary policy variable?," Journal of Monetary Economics, Elsevier, vol. 5(1), pages 105-121, January.
- Fotiadis, Anestis & Polyzos, Stathis & Huan, Tzung-Cheng T.C., 2021. "The good, the bad and the ugly on COVID-19 tourism recovery," Annals of Tourism Research, Elsevier, vol. 87(C).
- Kilian, Lutz, 2001. "Impulse Response Analysis in Vector Autoregressions with Unknown Lag Order," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(3), pages 161-179, April.
- Scott Hacker & Abdulnasser Hatemi‐J, 2012. "A bootstrap test for causality with endogenous lag length choice: theory and application in finance," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 39(2), pages 144-160, May.
- Swanson, Norman R & White, Halbert, 1995. "A Model-Selection Approach to Assessing the Information in the Term Structure Using Linear Models and Artificial Neural Networks," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 265-275, July.
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.- Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2023.
"Machine learning advances for time series forecasting,"
Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 76-111, February.
- Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2020. "Machine Learning Advances for Time Series Forecasting," Papers 2012.12802, arXiv.org, revised Apr 2021.
- Christis Katsouris, 2023. "High Dimensional Time Series Regression Models: Applications to Statistical Learning Methods," Papers 2308.16192, arXiv.org.
- Yaser Abolghasemi & Stanko Dimitrov, 2021. "Determining the causality between U.S. presidential prediction markets and global financial markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4534-4556, July.
- Grigori Fainstein & Igor Novikov, 2011. "The Comparative Analysis of Credit Risk Determinants In the Banking Sector of the Baltic States," Review of Economics & Finance, Better Advances Press, Canada, vol. 1, pages 20-45, June.
- Ács, Attila, 2014. "Pénzintézeti mérlegadatok monetáris politikai újraértelmezése. A brókerkereskedő szervezetek reálgazdasági és likviditási jelentősége [Reconsidering the role of financial institutions balance sheet," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(2), pages 166-192.
- Sapkota, Niranjan, 2022. "News-based sentiment and bitcoin volatility," International Review of Financial Analysis, Elsevier, vol. 82(C).
- Eryilmaz, Unal, 2021. "Enflasyonist Koşullarda Türkiye Ekonomisine İlişkin Bir Para Arzı Tahmini [Money Supply Forecast for the Turkish Economy in Inflationary Conditions]," MPRA Paper 111685, University Library of Munich, Germany.
- Theodore Panagiotidis & Georgios Papapanagiotou, 2024.
"A note on the determinants of NFTs returns,"
Working Paper series
24-07, Rimini Centre for Economic Analysis.
- Theodore Panagiotidis & Georgios Papapanagiotou, 2024. "A note on the determinants of NFTs returns," Discussion Paper Series 2024_02, Department of Economics, University of Macedonia, revised Feb 2024.
- Muhammad Atiq-ur-Rehman & Ismat Nasim & Muhammad Ayub & Ruqayya Ibraheem, 2022. "Transmission Lags of Monetary Policy: Probing into Pakistan's Untamed Inflation," iRASD Journal of Economics, International Research Alliance for Sustainable Development (iRASD), vol. 4(2), pages 329-336, June.
- Polyzos, Stathis & Samitas, Aristeidis & Kampouris, Ilias, 2021. "Economic stimulus through bank regulation: Government responses to the COVID-19 crisis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
- Russell Davidson & Victoria Zinde‐Walsh, 2017.
"Advances in specification testing,"
Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 50(5), pages 1595-1631, December.
- Russell Davidson & Victoria Zinde-Walsh, 2017. "Advances in specification testing," Canadian Journal of Economics, Canadian Economics Association, vol. 50(5), pages 1595-1631, December.
- Russell Davidson & Victoria Zinde-Walsh, 2017. "Advances in specification testing," Post-Print hal-01684821, HAL.
- Sanchez-Fung, Jose R., 2002.
"Inflation targeting and monetary analysis in Chile and Mexico,"
Economics Discussion Papers
2002-7, School of Economics, Kingston University London.
- Jose Sanchez-Fung, 2004. "Inflation targeting and monetary analysis in Chile and Mexico," Money Macro and Finance (MMF) Research Group Conference 2003 82, Money Macro and Finance Research Group.
- Sanchez-Fung, Jose R, 2003. "Inflation targeting and monetary analysis in Chile and Mexico," Royal Economic Society Annual Conference 2003 179, Royal Economic Society.
- Lee, Ji Hyung & Shi, Zhentao & Gao, Zhan, 2022.
"On LASSO for predictive regression,"
Journal of Econometrics, Elsevier, vol. 229(2), pages 322-349.
- Ji Hyung Lee & Zhentao Shi & Zhan Gao, 2018. "On LASSO for Predictive Regression," Papers 1810.03140, arXiv.org, revised Feb 2021.
- Adrian C. Darnell, 1994. "A Dictionary Of Econometrics," Books, Edward Elgar Publishing, number 118.
- Staszewska-Bystrova, Anna & Winker, Peter, 2013. "Constructing narrowest pathwise bootstrap prediction bands using threshold accepting," International Journal of Forecasting, Elsevier, vol. 29(2), pages 221-233.
- Barbara Rossi, 2019.
"Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them,"
Economics Working Papers
1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
- Barbara Rossi, 2019. "Forecasting in the Presence of Instabilities: How Do We Know Whether Models Predict Well and How to Improve Them," Working Papers 1162, Barcelona School of Economics.
- Rossi, Barbara, 2020. "Forecasting in the Presence of Instabilities: How Do We Know Whether Models Predict Well and How to Improve Them," CEPR Discussion Papers 14472, C.E.P.R. Discussion Papers.
- Matteo Barigozzi & Christian Brownlees, 2019.
"NETS: Network estimation for time series,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(3), pages 347-364, April.
- Matteo Barigozzi & Christian T. Brownlees, 2013. "Nets: Network estimation for time series," Economics Working Papers 1391, Department of Economics and Business, Universitat Pompeu Fabra.
- Matteo Barigozzi & Christian Brownlees, 2013. "Nets: Network Estimation for Time Series," Working Papers 723, Barcelona School of Economics.
- Barigozzi, Matteo & Brownlees, Christian T., 2018. "Nets: network estimation for time series," LSE Research Online Documents on Economics 90493, London School of Economics and Political Science, LSE Library.
- David Staines, 2023. "Stochastic Equilibrium the Lucas Critique and Keynesian Economics," Papers 2312.16214, arXiv.org, revised Jun 2024.
- Daniel Hopp, 2022. "Benchmarking Econometric and Machine Learning Methodologies in Nowcasting," Papers 2205.03318, arXiv.org.
- Baltagi, Badi H. & Li, Qi, 1995. "Testing AR(1) against MA(1) disturbances in an error component model," Journal of Econometrics, Elsevier, vol. 68(1), pages 133-151, July.
More about this item
Keywords
Random regression forest; Optimal lag; Lasso; Ridge regression; Bayesian model averaging;All these keywords.
JEL classification:
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
- E61 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Policy Objectives; Policy Designs and Consistency; Policy Coordination
- G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
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:kap:compec:v:64:y:2024:i:1:d:10.1007_s10614-023-10429-9. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.