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Liquidity Management of Canadian Corporate Bond Mutual Funds: A Machine Learning Approach

Author

Listed:
  • Rohan Arora
  • Chen Fan
  • Guillaume Ouellet Leblanc

Abstract

How do Canadian corporate bond mutual funds meet investor redemptions? We revisit this question using decision tree and random forest algorithms. We uncover new patterns in the decisions made by fund managers: the interaction between a larger, market-wide term spread and relatively less-liquid holdings increases the probability that a fund manager will sell less-liquid assets (corporate bonds) to meet redemptions. The evidence also shows that machine learning algorithms can extract new knowledge that is not apparent using a classical linear modelling approach.

Suggested Citation

  • Rohan Arora & Chen Fan & Guillaume Ouellet Leblanc, 2019. "Liquidity Management of Canadian Corporate Bond Mutual Funds: A Machine Learning Approach," Staff Analytical Notes 2019-7, Bank of Canada.
    • Handle: RePEc:bca:bocsan:19-7
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    File URL: https://www.bankofcanada.ca/2019/02/staff-analytical-note-2019-7/
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    References listed on IDEAS

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    1. Hal R. Varian, 2014. "Big Data: New Tricks for Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 3-28, Spring.
    2. Rohan Arora & Nadeem Merali & Guillaume Ouellet Leblanc, 2018. "Did Canadian Corporate Bond Funds Increase their Exposures to Risks?," Staff Analytical Notes 2018-7, Bank of Canada.
    3. Rohan Arora, 2018. "Redemption Runs in Canadian Corporate Bond Funds?," Staff Analytical Notes 2018-21, Bank of Canada.
    4. Goldstein, Itay & Jiang, Hao & Ng, David T., 2017. "Investor flows and fragility in corporate bond funds," Journal of Financial Economics, Elsevier, vol. 126(3), pages 592-613.
    5. Ben-Rephael, Azi, 2017. "Flight-to-liquidity, market uncertainty, and the actions of mutual fund investors," Journal of Financial Intermediation, Elsevier, vol. 31(C), pages 30-44.
    6. Maxime Leboeuf & James Pinnington, 2017. "What Explains the Recent Increase in Canadian Corporate Bond Spreads," Staff Analytical Notes 17-2, Bank of Canada.
    7. Chernenko, Sergey & Sunderam, Adi, 2016. "Liquidity transformation in asset management: Evidence from the cash holdings of mutual funds," ESRB Working Paper Series 23, European Systemic Risk Board.
    8. Chen, Qi & Goldstein, Itay & Jiang, Wei, 2010. "Payoff complementarities and financial fragility: Evidence from mutual fund outflows," Journal of Financial Economics, Elsevier, vol. 97(2), pages 239-262, August.
    9. Guillaume Ouellet Leblanc & Rohan Arora, 2018. "How do Canadian Corporate Bond Mutual Funds Meet Investor Redemptions?," Staff Analytical Notes 2018-14, Bank of Canada.
    10. Sergey Chernenko & Adi Sunderam, 2016. "Liquidity Transformation in Asset Management: Evidence from the Cash Holdings of Mutual Funds," NBER Working Papers 22391, National Bureau of Economic Research, Inc.
    11. Chakraborty, Chiranjit & Joseph, Andreas, 2017. "Machine learning at central banks," Bank of England working papers 674, Bank of England.
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    Cited by:

    1. Elyasiani, Elyas & Movaghari, Hadi, 2022. "Determinants of corporate cash holdings: An application of a robust variable selection technique," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 967-993.
    2. Dmytro Krukovets, 2020. "Data Science Opportunities at Central Banks: Overview," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 249, pages 13-24.

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    More about this item

    Keywords

    Financial markets; Financial stability;

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

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