IDEAS home Printed from https://ideas.repec.org/p/ehl/lserod/117701.html
   My bibliography  Save this paper

Dynamic portfolio optimization with inverse covariance clustering

Author

Listed:
  • Wang, Yuanrong
  • Aste, Tomaso

Abstract

Market conditions change continuously. However, in portfolio investment strategies, it is hard to account for this intrinsic non-stationarity. In this paper, we propose to address this issue by using the Inverse Covariance Clustering (ICC) method to identify inherent market states and then integrate such states into a dynamic portfolio optimization process. Extensive experiments across three different markets, NASDAQ, FTSE and HS300, over a period of ten years, demonstrate the advantages of our proposed algorithm, termed Inverse Covariance Clustering-Portfolio Optimization (ICC-PO). The core of the ICC-PO methodology concerns the identification and clustering of market states from the analytics of past data and the forecasting of the future market state. It is therefore agnostic to the specific portfolio optimization method of choice. By applying the same portfolio optimization technique on a ICC temporal cluster, instead of the whole train period, we show that one can generate portfolios with substantially higher Sharpe Ratios, which are statistically more robust and resilient with great reductions in the maximum loss in extreme situations. This is shown to be consistent across markets, periods, optimization methods and selection of portfolio assets.

Suggested Citation

  • Wang, Yuanrong & Aste, Tomaso, 2023. "Dynamic portfolio optimization with inverse covariance clustering," LSE Research Online Documents on Economics 117701, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:117701
    as

    Download full text from publisher

    File URL: http://eprints.lse.ac.uk/117701/
    File Function: Open access version.
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Andrew Ang & Geert Bekaert, 2003. "How do Regimes Affect Asset Allocation?," NBER Working Papers 10080, National Bureau of Economic Research, Inc.
    2. Fama, Eugene F & French, Kenneth R, 1992. "The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    3. Barfuss, Wolfram & Massara, Guido Previde & Di Matteo, T. & Aste, Tomaso, 2016. "Parsimonious modeling with information filtering networks," LSE Research Online Documents on Economics 68860, London School of Economics and Political Science, LSE Library.
    4. Hansen, Bruce E, 1992. "The Likelihood Ratio Test under Nonstandard Conditions: Testing the Markov Switching Model of GNP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages 61-82, Suppl. De.
    5. repec:dau:papers:123456789/5717 is not listed on IDEAS
    6. Andrew Ang & Geert Bekaert, 2002. "International Asset Allocation With Regime Shifts," The Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1137-1187.
    7. Victor DeMiguel & Lorenzo Garlappi & Raman Uppal, 2009. "Optimal Versus Naive Diversification: How Inefficient is the 1-N Portfolio Strategy?," The Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 1915-1953, May.
    8. Tae-Hwy Lee & Ekaterina Seregina, 2020. "Optimal Portfolio Using Factor Graphical Lasso," Papers 2011.00435, arXiv.org, revised Apr 2023.
    9. Thaleia Zariphopoulou, 2001. "A solution approach to valuation with unhedgeable risks," Finance and Stochastics, Springer, vol. 5(1), pages 61-82.
    10. Isabelle Bajeux-Besnainou & James V. Jordan & Roland Portait, 2001. "An Asset Allocation Puzzle: Comment," American Economic Review, American Economic Association, vol. 91(4), pages 1170-1179, September.
    11. M Jackson & M D Staunton, 1999. "Quadratic programming applications in finance using Excel," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 50(12), pages 1256-1266, December.
    12. Jason Narsoo, 2017. "Performance Analysis of Portfolio Optimisation Strategies: Evidence from the Exchange Market," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 9(6), pages 124-132, June.
    13. He, Hua & Pearson, Neil D., 1991. "Consumption and portfolio policies with incomplete markets and short-sale constraints: The infinite dimensional case," Journal of Economic Theory, Elsevier, vol. 54(2), pages 259-304, August.
    14. Antonio Briola & Jeremy Turiel & Tomaso Aste, 2020. "Deep Learning modeling of Limit Order Book: a comparative perspective," Papers 2007.07319, arXiv.org, revised Oct 2020.
    15. Robert R. Grauer & Nils H. Hakansson, 1993. "On the Use of Mean-Variance and Quadratic Approximations in Implementing Dynamic Investment Strategies: A Comparison of Returns and Investment Policies," Management Science, INFORMS, vol. 39(7), pages 856-871, July.
    16. Nicol'o Musmeci & Tomaso Aste & Tiziana Di Matteo, 2016. "What does past correlation structure tell us about the future? An answer from network filtering," Papers 1605.08908, arXiv.org.
    17. Merton, Robert C., 1971. "Optimum consumption and portfolio rules in a continuous-time model," Journal of Economic Theory, Elsevier, vol. 3(4), pages 373-413, December.
    18. Tomaso Aste & T. Di Matteo, 2017. "Sparse Causality Network Retrieval from Short Time Series," Complexity, Hindawi, vol. 2017, pages 1-13, November.
    19. Buckley, Ian & Saunders, David & Seco, Luis, 2008. "Portfolio optimization when asset returns have the Gaussian mixture distribution," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1434-1461, March.
    20. Gah-Yi Ban & Noureddine El Karoui & Andrew E. B. Lim, 2018. "Machine Learning and Portfolio Optimization," Management Science, INFORMS, vol. 64(3), pages 1136-1154, March.
    21. Zeitsch, Peter J., 2019. "A jump model for credit default swaps with hierarchical clustering," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 737-775.
    22. 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.
    23. Farzan Soleymani & Eric Paquet, 2021. "Deep Graph Convolutional Reinforcement Learning for Financial Portfolio Management -- DeepPocket," Papers 2105.08664, arXiv.org.
    24. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    25. Yves-Laurent Kom Samo & Alexander Vervuurt, 2016. "Stochastic Portfolio Theory: A Machine Learning Perspective," Papers 1605.02654, arXiv.org.
    26. Ying Jiao & Huyên Pham, 2011. "Optimal investment with counterparty risk: a default-density model approach," Finance and Stochastics, Springer, vol. 15(4), pages 725-753, December.
    27. Lin, Wen-Ling & Engle, Robert F & Ito, Takatoshi, 1994. "Do Bulls and Bears Move across Borders? International Transmission of Stock Returns and Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 7(3), pages 507-538.
    28. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    29. Hakansson, Nils H., 1971. "Capital Growth and the Mean-Variance Approach to Portfolio Selection," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 6(1), pages 517-557, January.
    30. Simin, Timothy, 2008. "The Poor Predictive Performance of Asset Pricing Models," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 43(2), pages 355-380, June.
    31. Harry M. Markowitz & David Starer & Harvey Fram & Sander Gerber, 2020. "Avoiding the Downside: A Practical Review of the Critical Line Algorithm for Mean–Semivariance Portfolio Optimization," World Scientific Book Chapters, in: John B Guerard & William T Ziemba (ed.), HANDBOOK OF APPLIED INVESTMENT RESEARCH, chapter 17, pages 369-415, World Scientific Publishing Co. Pte. Ltd..
    32. Merton, Robert C, 1973. "An Intertemporal Capital Asset Pricing Model," Econometrica, Econometric Society, vol. 41(5), pages 867-887, September.
    33. Paul A. Samuelson, 2011. "Lifetime Portfolio Selection by Dynamic Stochastic Programming," World Scientific Book Chapters, in: Leonard C MacLean & Edward O Thorp & William T Ziemba (ed.), THE KELLY CAPITAL GROWTH INVESTMENT CRITERION THEORY and PRACTICE, chapter 31, pages 465-472, World Scientific Publishing Co. Pte. Ltd..
    34. Merton, Robert C, 1969. "Lifetime Portfolio Selection under Uncertainty: The Continuous-Time Case," The Review of Economics and Statistics, MIT Press, vol. 51(3), pages 247-257, August.
    35. Smail Tigani & Hasna Chaibi & Rachid Saadane, 2019. "Gaussian Mixture and Kernel Density-Based Hybrid Model for Volatility Behavior Extraction From Public Financial Data," Data, MDPI, vol. 4(1), pages 1-11, January.
    36. Eckhard Limpert & Werner A Stahel, 2011. "Problems with Using the Normal Distribution – and Ways to Improve Quality and Efficiency of Data Analysis," PLOS ONE, Public Library of Science, vol. 6(7), pages 1-8, July.
    37. Cox, John C. & Huang, Chi-fu, 1989. "Optimal consumption and portfolio policies when asset prices follow a diffusion process," Journal of Economic Theory, Elsevier, vol. 49(1), pages 33-83, October.
    38. A. Ford Ramsey & Barry K. Goodwin, 2019. "Value-at-Risk and Models of Dependence in the U.S. Federal Crop Insurance Program," JRFM, MDPI, vol. 12(2), pages 1-21, April.
    39. Ramchand, Latha & Susmel, Raul, 1998. "Volatility and cross correlation across major stock markets," Journal of Empirical Finance, Elsevier, vol. 5(4), pages 397-416, October.
    40. Brennan, Michael J. & Xia, Yihong, 2000. "Dynamic Asset Allocation under Inflation," University of California at Los Angeles, Anderson Graduate School of Management qt8p95456t, Anderson Graduate School of Management, UCLA.
    41. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    42. Xiao Zhong & David Enke, 2019. "Predicting the daily return direction of the stock market using hybrid machine learning algorithms," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-20, December.
    43. Antonio Briola & Jeremy Turiel & Riccardo Marcaccioli & Alvaro Cauderan & Tomaso Aste, 2021. "Deep Reinforcement Learning for Active High Frequency Trading," Papers 2101.07107, arXiv.org, revised Aug 2023.
    44. Pier Francesco Procacci & Tomaso Aste, 2021. "Portfolio Optimization with Sparse Multivariate Modelling," Papers 2103.15232, arXiv.org.
    45. Ahn, Hee-Joon & Cai, Jun & Cheung, Yan Leung, 2005. "Price clustering on the limit-order book: Evidence from the Stock Exchange of Hong Kong," Journal of Financial Markets, Elsevier, vol. 8(4), pages 421-451, November.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. David Vidal-Tom'as & Antonio Briola & Tomaso Aste, 2023. "FTX's downfall and Binance's consolidation: The fragility of centralised digital finance," Papers 2302.11371, arXiv.org, revised Dec 2023.

    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. Yuanrong Wang & Tomaso Aste, 2021. "Dynamic Portfolio Optimization with Inverse Covariance Clustering," Papers 2112.15499, arXiv.org, revised Jan 2022.
    2. Baele, Lieven, 2005. "Volatility Spillover Effects in European Equity Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 40(2), pages 373-401, June.
    3. George Chacko & Luis M. Viceira, 2005. "Dynamic Consumption and Portfolio Choice with Stochastic Volatility in Incomplete Markets," The Review of Financial Studies, Society for Financial Studies, vol. 18(4), pages 1369-1402.
    4. John Y. Campbell, 2000. "Asset Pricing at the Millennium," Journal of Finance, American Finance Association, vol. 55(4), pages 1515-1567, August.
    5. Ming‐yuan leon Li, 2009. "Change In Volatility Regimes And Diversification In Emerging Stock Markets," South African Journal of Economics, Economic Society of South Africa, vol. 77(1), pages 59-80, March.
    6. Campbell, John Y & Viceira, Luis, 2005. "The Term Structure of the Risk-Return Tradeoff," CEPR Discussion Papers 4914, C.E.P.R. Discussion Papers.
    7. Bruno Solnik & Thaisiri Watewai, 2016. "International Correlation Asymmetries: Frequent-but-Small and Infrequent-but-Large Equity Returns," PIER Discussion Papers 31., Puey Ungphakorn Institute for Economic Research, revised Jun 2016.
    8. Bruno Solnik & Thaisiri Watewai, 2016. "International Correlation Asymmetries: Frequent-but-Small and Infrequent-but-Large Equity Returns," PIER Discussion Papers 31, Puey Ungphakorn Institute for Economic Research.
    9. Gerrard, Russell & Kyriakou, Ioannis & Nielsen, Jens Perch & Vodička, Peter, 2023. "On optimal constrained investment strategies for long-term savers in stochastic environments and probability hedging," European Journal of Operational Research, Elsevier, vol. 307(2), pages 948-962.
    10. Michael W. Brandt & Amit Goyal & Pedro Santa-Clara & Jonathan R. Stroud, 2005. "A Simulation Approach to Dynamic Portfolio Choice with an Application to Learning About Return Predictability," The Review of Financial Studies, Society for Financial Studies, vol. 18(3), pages 831-873.
    11. Jakub W. Jurek & Luis M. Viceira, 2011. "Optimal Value and Growth Tilts in Long-Horizon Portfolios," Review of Finance, European Finance Association, vol. 15(1), pages 29-74.
    12. 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.
    13. Li, Minqiang, 2010. "Asset Pricing - A Brief Review," MPRA Paper 22379, University Library of Munich, Germany.
    14. Garcia, René & Tsafack, Georges, 2011. "Dependence structure and extreme comovements in international equity and bond markets," Journal of Banking & Finance, Elsevier, vol. 35(8), pages 1954-1970, August.
    15. Michael J. Brennan & Yihong Xia, 2002. "Dynamic Asset Allocation under Inflation," Journal of Finance, American Finance Association, vol. 57(3), pages 1201-1238, June.
    16. Mahan Tahvildari, 2021. "Forward indifference valuation and hedging of basis risk under partial information," Papers 2101.00251, arXiv.org.
    17. Brennan, Michael J. & Xia, Yihong, 2000. "Dynamic Asset Allocation under Inflation," University of California at Los Angeles, Anderson Graduate School of Management qt8p95456t, Anderson Graduate School of Management, UCLA.
    18. Yudong Wang & Chongfeng Wu & Li Yang, 2015. "Hedging with Futures: Does Anything Beat the Naïve Hedging Strategy?," Management Science, INFORMS, vol. 61(12), pages 2870-2889, December.
    19. Spierdijk, Laura & Umar, Zaghum, 2014. "Stocks for the long run? Evidence from emerging markets," Journal of International Money and Finance, Elsevier, vol. 47(C), pages 217-238.

    More about this item

    Keywords

    covariance structure; dynamic portfolio optimization; financial market states; information filtering networks; market regimes; portfolio management; temporal clustering; ES/K002309/1; EP/P031730/1; H2020-ICT-2018-2 825215;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:ehl:lserod:117701. 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: LSERO Manager (email available below). General contact details of provider: https://edirc.repec.org/data/lsepsuk.html .

    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.