IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v64y2024ics1544612324005002.html
   My bibliography  Save this article

Asset allocation combining macro and micro information–Empirical test based on entropy pool model

Author

Listed:
  • Li, Tianyuan
  • Chen, Ping

Abstract

Macroeconomic environment is an essential factor affecting asset return, but it is difficult to construct portfolios using macro information quantitatively in traditional models. In this paper, we extend the Black-Litterman framework to build an efficient portfolio by using views containing macro information and prior market distribution reflecting micro information. In order to enhance the model's flexibility, entropy pool method is used. Empirical evidence shows that with reasonable allocation across economic stages, the newly constructed portfolio enjoys a higher level of Sharpe ratio compared to classic allocation models, and the result is robust under different circumstance.

Suggested Citation

  • Li, Tianyuan & Chen, Ping, 2024. "Asset allocation combining macro and micro information–Empirical test based on entropy pool model," Finance Research Letters, Elsevier, vol. 64(C).
    • Handle: RePEc:eee:finlet:v:64:y:2024:i:c:s1544612324005002
    DOI: 10.1016/j.frl.2024.105470
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612324005002
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2024.105470?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Panagiotis Schizas & Dimitrios D. Thomakos, 2015. "Market timing and trading strategies using asset rotation: non-neutral market positioning for exploiting arbitrage opportunities," Quantitative Finance, Taylor & Francis Journals, vol. 15(2), pages 285-298, February.
    2. Best, Michael J & Grauer, Robert R, 1991. "On the Sensitivity of Mean-Variance-Efficient Portfolios to Changes in Asset Means: Some Analytical and Computational Results," The Review of Financial Studies, Society for Financial Studies, vol. 4(2), pages 315-342.
    3. repec:dau:papers:123456789/4688 is not listed on IDEAS
    4. Li, Houjian & Li, Qingman & Huang, Xinya & Guo, Lili, 2023. "Do green bonds and economic policy uncertainty matter for carbon price? New insights from a TVP-VAR framework," International Review of Financial Analysis, Elsevier, vol. 86(C).
    5. Harry Markowitz, 1952. "The Utility of Wealth," Journal of Political Economy, University of Chicago Press, vol. 60(2), pages 151-151.
    6. Yeung Lewis Chan & James H. Stock & Mark W. Watson, 1999. "A dynamic factor model framework for forecast combination," Spanish Economic Review, Springer;Spanish Economic Association, vol. 1(2), pages 91-121.
    7. Li, Dongxin & Zhang, Li & Li, Lihong, 2023. "Forecasting stock volatility with economic policy uncertainty: A smooth transition GARCH-MIDAS model," International Review of Financial Analysis, Elsevier, vol. 88(C).
    8. Jobson, J D & Korkie, Bob M, 1981. "Performance Hypothesis Testing with the Sharpe and Treynor Measures," Journal of Finance, American Finance Association, vol. 36(4), pages 889-908, September.
    9. Han, Yingwei & Li, Jie, 2023. "The impact of global economic policy uncertainty on portfolio optimization: A Black–Litterman approach," International Review of Financial Analysis, Elsevier, vol. 86(C).
    Full references (including those not matched with items on IDEAS)

    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.
    1. Harris, Richard D. F. & Mazibas, Murat, 2022. "Portfolio optimization with behavioural preferences and investor memory," European Journal of Operational Research, Elsevier, vol. 296(1), pages 368-387.
    2. Candelon, B. & Hurlin, C. & Tokpavi, S., 2012. "Sampling error and double shrinkage estimation of minimum variance portfolios," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 511-527.
    3. Lagoarde-Segot, Thomas & Lucey, Brian M., 2007. "International portfolio diversification: Is there a role for the Middle East and North Africa?," Journal of Multinational Financial Management, Elsevier, vol. 17(5), pages 401-416, December.
    4. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2022. "Sparsity and stability for minimum-variance portfolios," Risk Management, Palgrave Macmillan, vol. 24(3), pages 214-235, September.
    5. Cheng Yan & Ji Yan, 2021. "Optimal and naive diversification in an emerging market: Evidence from China's A‐shares market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3740-3758, July.
    6. Markus Hirschberger & Ralph E. Steuer & Sebastian Utz & Maximilian Wimmer & Yue Qi, 2013. "Computing the Nondominated Surface in Tri-Criterion Portfolio Selection," Operations Research, INFORMS, vol. 61(1), pages 169-183, February.
    7. Thomas Lagoarde-Segot & Brian M. Lucey, 2006. "Portfolio allocations in the Middle East and North Africa," The Institute for International Integration Studies Discussion Paper Series iiisdp141, IIIS.
    8. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2021. "Cross-validated covariance estimators for high-dimensional minimum-variance portfolios," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(3), pages 309-352, September.
    9. Stadtmüller, Immo & Auer, Benjamin R. & Schuhmacher, Frank, 2022. "On the benefits of active stock selection strategies for diversified investors," The Quarterly Review of Economics and Finance, Elsevier, vol. 85(C), pages 342-354.
    10. Patrick Bielstein, 2018. "International asset allocation using the market implied cost of capital," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 32(1), pages 17-51, February.
    11. Erindi Allaj, 2020. "The Black–Litterman model and views from a reverse optimization procedure: an out-of-sample performance evaluation," Computational Management Science, Springer, vol. 17(3), pages 465-492, October.
    12. Okhrin, Yarema & Schmid, Wolfgang, 2006. "Distributional properties of portfolio weights," Journal of Econometrics, Elsevier, vol. 134(1), pages 235-256, September.
    13. Ghaemi Asl, Mahdi & Rashidi, Muhammad Mahdi & Tavakkoli, Hamid Raza & Rezgui, Hichem, 2024. "Does Islamic investing modify portfolio performance? Time-varying optimization strategies for conventional and Shariah energy-ESG-utilities portfolio," The Quarterly Review of Economics and Finance, Elsevier, vol. 94(C), pages 37-57.
    14. Rad, Hossein & Low, Rand Kwong Yew & Miffre, Joëlle & Faff, Robert, 2022. "The strategic allocation to style-integrated portfolios of commodity futures," Journal of Commodity Markets, Elsevier, vol. 28(C).
    15. Olaf Stotz, 2009. "Predicting returns of equity mutual funds," Journal of Asset Management, Palgrave Macmillan, vol. 10(3), pages 158-169, August.
    16. Daniel Kinn, 2018. "Reducing Estimation Risk in Mean-Variance Portfolios with Machine Learning," Papers 1804.01764, arXiv.org, revised Jul 2018.
    17. Ko, Hyungjin & Son, Bumho & Lee, Jaewook, 2024. "A novel integration of the Fama–French and Black–Litterman models to enhance portfolio management," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    18. Napat Rujeerapaiboon & Daniel Kuhn & Wolfram Wiesemann, 2016. "Robust Growth-Optimal Portfolios," Management Science, INFORMS, vol. 62(7), pages 2090-2109, July.
    19. Lara Dalmeyer & Tim Gebbie, 2021. "Geometric insights into robust portfolio construction," Papers 2107.06194, arXiv.org, revised Jul 2024.
    20. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2019. "Sparsity and Stability for Minimum-Variance Portfolios," Papers 1910.11840, arXiv.org.

    Corrections

    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:eee:finlet:v:64:y:2024:i:c:s1544612324005002. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

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