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

Rohan Arora (), Chen Fan and Guillaume Ouellet Leblanc ()

No 2019-7, Staff Analytical Notes from Bank of Canada

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.

Keywords: Financial markets; Financial stability (search for similar items in EconPapers)
JEL-codes: G1 G20 G23 (search for similar items in EconPapers)
Pages: 12 pages
Date: 2019
New Economics Papers: this item is included in nep-big and nep-cmp
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Citations: View citations in EconPapers (2)

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