Liquidity risk premium and asset pricing in US water transportation

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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Asset Pricing with Liquidity Risk: A Replication and Out-of-Sample Tests with the Recent US and the Japanese Market Data

Critical Finance Review ◽

10.1561/104.00000072 ◽

2019 ◽

Vol 8 (1-2) ◽

pp. 73-110 ◽

Cited By ~ 2

Author(s):

Eiichiro Kazumori ◽

Fei Fang ◽

Raj Sharman ◽

Fumiko Takeda ◽

Hong Yu

Keyword(s):

Asset Pricing ◽

Liquidity Risk ◽

Japanese Market ◽

Market Data ◽

Out Of Sample

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Tests of the risk premium on foreign currency futures impiled by the intertemporal asset pricing theory

Applied Financial Economics ◽

10.1080/758529176 ◽

1995 ◽

Vol 5 (2) ◽

pp. 85-94

Author(s):

Ramazan Gencay

Keyword(s):

Asset Pricing ◽

Risk Premium ◽

Foreign Currency ◽

Currency Futures ◽

Asset Pricing Theory ◽

Pricing Theory ◽

Intertemporal Asset Pricing

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Asset Pricing with Liquidity Risk

Market Liquidity ◽

10.1017/cbo9780511844393.011 ◽

2012 ◽

pp. 137-184 ◽

Cited By ~ 8

Author(s):

Yakov Amihud ◽

Haim Mendelson ◽

Lasse Heje Pedersen

Keyword(s):

Asset Pricing ◽

Liquidity Risk

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The Bias in Two-Pass Regression Tests of Asset-Pricing Models in Presence of Idiosyncratic Errors with Cross-Sectional Dependence

Review of Pacific Basin Financial Markets and Policies ◽

10.1142/s0219091519500127 ◽

2019 ◽

Vol 22 (02) ◽

pp. 1950012

Author(s):

Thomas Gramespacher ◽

Armin Bänziger

Keyword(s):

Asset Pricing ◽

Risk Premium ◽

Measurement Errors ◽

Factor Model ◽

Pricing Models ◽

Time Series Regression ◽

Cross Sectional ◽

Asset Pricing Models ◽

Slope Estimator ◽

Regression Tests

In two-pass regression-tests of asset-pricing models, cross-sectional correlations in the errors of the first-pass time-series regression lead to correlated measurement errors in the betas used as explanatory variables in the second-pass cross-sectional regression. The slope estimator of the second-pass regression is an estimate for the factor risk-premium and its significance is decisive for the validity of the pricing model. While it is well known that the slope estimator is downward biased in presence of uncorrelated measurement errors, we show in this paper that the correlations seen in empirical return data substantially suppress this bias. For the case of a single-factor model, we calculate the bias of the OLS slope estimator in the presence of correlated measurement errors with a first-order Taylor-approximation in the size of the errors. We show that the bias increases with the size of the errors, but decreases the more the errors are correlated. We illustrate and validate our result using a simulation approach based on empirical data commonly used in asset-pricing tests.

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