Expected Bond Liquidity

87 Pages Posted: 14 Jul 2020 Last revised: 11 Dec 2023

See all articles by Marcel Müller

Marcel Müller

Karlsruhe Institute of Technology (KIT) - Institute for Finance

Michael Reichenbacher

Karlsruhe Institute of Technology (KIT), Institute for Finance

Philipp Schuster

University of Stuttgart

Marliese Uhrig‐Homburg

Karlsruhe Institute of Technology

Date Written: December 8, 2023

Abstract

We propose a machine learning methodology for predicting the future liquidity distribution of individual bonds in the U.S. corporate bond market and use it to compute two forward-looking illiquidity measures: expected illiquidity and expected tail illiquidity as measure for downside liquidity risk. We find that bonds characterized by higher expected illiquidity have elevated systematic risk premiums, whereas expected tail illiquidity is predominantly reflected in the alpha. Investors in corporate bond funds preemptively sell their shares in response to anticipated liquidity declines in underperforming funds. All effects are much stronger compared to the standard approach of using today’s realized liquidity.

Keywords: bond liquidity, bid-ask spread, forecasting, asset pricing, bond funds, machine learning, downside risk

JEL Classification: C10, C53, G12, G17, G20

Suggested Citation

Müller, Marcel and Reichenbacher, Michael and Schuster, Philipp and Uhrig‐Homburg, Marliese, Expected Bond Liquidity (December 8, 2023). Available at SSRN: https://ssrn.com/abstract=3642604 or http://dx.doi.org/10.2139/ssrn.3642604

Marcel Müller

Karlsruhe Institute of Technology (KIT) - Institute for Finance ( email )

P.O. Box 6980
D-76049 Karlsruhe, DE
Germany
+49 721 6084 8187 (Phone)
+49 721 6084 8190 (Fax)

HOME PAGE: http://derivate.fbv.kit.edu/english/Staff_1444.php

Michael Reichenbacher

Karlsruhe Institute of Technology (KIT), Institute for Finance ( email )

Kaiserstraße 12
Karlsruhe, Baden Württemberg 76131
Germany

Philipp Schuster (Contact Author)

University of Stuttgart ( email )

Keplerstraße 17
D-70174 Stuttgart
Germany
+49 711 685-86001 (Phone)

Marliese Uhrig‐Homburg

Karlsruhe Institute of Technology

Kaiserstraße 12
Karlsruhe, Baden Württemberg 76131
Germany

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