Pricing Liquidity Risk with Heterogeneous Investment Horizons

Alessandro Beber, Joost Driessen, A. Neuberger, P Tuijp

Research output: Working paperOther research output

Abstract

We develop an asset pricing model with stochastic transaction costs and investors with heterogeneous horizons. Depending on their horizon, investors hold different sets of assets in equilibrium. This generates segmentation and spillover effects for expected returns, where the liquidity (risk) premium of illiquid assets is determined by investor horizons and the correlation between liquid and illiquid asset returns. We estimate our model for the cross-section of U.S. stock returns and find that it generates a good fit, mainly due to a combination of a substantial expected liquidity premium and segmentation effects, while the liquidity risk premium is small.
Original languageEnglish
PublisherSSRN
Number of pages99
DOIs
Publication statusPublished - Jan 2018

Fingerprint

Investment horizon
Liquidity risk
Investors
Pricing
Assets
Segmentation
Risk premium
Transaction costs
Asset pricing models
Asset returns
Cross section
Stock returns
Liquidity premium
Spillover effects
Expected returns

Keywords

  • liquidity premium
  • liquidity risk
  • investment horizon
  • holding period

Cite this

Beber, Alessandro ; Driessen, Joost ; Neuberger, A. ; Tuijp, P. / Pricing Liquidity Risk with Heterogeneous Investment Horizons. SSRN, 2018.
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Pricing Liquidity Risk with Heterogeneous Investment Horizons. / Beber, Alessandro; Driessen, Joost; Neuberger, A.; Tuijp, P.

SSRN, 2018.

Research output: Working paperOther research output

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AB - We develop an asset pricing model with stochastic transaction costs and investors with heterogeneous horizons. Depending on their horizon, investors hold different sets of assets in equilibrium. This generates segmentation and spillover effects for expected returns, where the liquidity (risk) premium of illiquid assets is determined by investor horizons and the correlation between liquid and illiquid asset returns. We estimate our model for the cross-section of U.S. stock returns and find that it generates a good fit, mainly due to a combination of a substantial expected liquidity premium and segmentation effects, while the liquidity risk premium is small.

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