The conditional Fama-French model and endogenous illiquidity: A robust instrumental variables test

Abstract

We investigate conditional specifications of the five-factor Fama-French (FF) model, augmented with traditional illiquidity measures. The motivation for this time-varying methodology is that the traditional static approach of the FF model may be misspecified, especially for the endogenous illiquidity measures. We focus on the time-varying nature of the Jensen performance measure α and the market systematic risk sensitivity β, as these parameters are essentially universal in asset pricing models. To tackle endogeneity and other specification errors, we rely on our robust instrumental variables (RIV) algorithm implemented via a GMM approach. In this dynamic or time-varying conditional context, we generally find that the most significant factor is the market one, but illiquidity may matter depending on which states or estimation methods we consider. In particular, sectors whose returns embed a market illiquidity premium are more exposed to a binding funding constraint in times of crisis, which leads to deleveraging and a resulting decrease in systematic risk.

Impact of consumer confidence on the expected returns of the Tokyo Stock Exchange: A comparative analysis of consumption and production-based asset pricing models

“…On the other hand [ 34 ], use a distance instrument-based algorithm into a GMM framework, to study the impact of illiquidity on the returns of twelve sector portfolios. Consistently with [ 32 , 33 ], the authors conclude that the only relevant factor according to their dynamic GMM approach is the market risk premium.…”

“…247–251) explains that, under certain conditions, the Fama-MacBeth procedure is numerically equivalent to a pooled regression, and emphasizes the benefits of mapping this approach into the generalized method of moments (GMM), developed by [ 65 ]. Notably [ 66 ], introduces a GMM estimator that relies on distance instruments to estimate panel data regression models containing errors in variables [ 32 , 33 ]. use this approach to test the Fama-French five-factor model augmented with illiquidity measures, concluding that, in general, the most significant factor is RMRF, with measurement errors largely determining this result.…”

Performance measurement of ESG-themed megatrend investments in global equity markets using pure factor portfolios methodology

“…Based on our GMM-IV d estimates, the coefficients for value, investment and profitability are significant which are in contrary to Racicot et al . [ 34 , 98 , 99 ] who found that in most cases the market factor is the only variable which has significant explanatory power. The authors highlight that measurement errors may be the reason for their results.…”

“…The effect of liquidity or illiquidity is a critical factor which is clearly in the focus of researchers (see Amihud [ 96 ], Pástor and Stambaugh [ 97 ] or Racicot et al . [ 98 , 99 ]). Beyond liquidity, the applied factors are, in fact, very diverse: López-García et al .…”

Empirical Research on the Fama-French Three-Factor Model and a Sentiment-Related Four-Factor Model in the Chinese Blockchain Industry

“…Fama and French found that the FFFFM mainly has two defects: The first is that the model lacks the ability to describe the average return of small stocks, and the second weakness is that the HML (High Minus Low) factor is a redundancy factor. Racicot et al studied the FFFFM with traditional illiquidity measures and found the weakness of this model, especially for the endogenous illiquidity measures [23]. The robust instrumental variables (RIV) algorithm conducted by GMM (Generalized Method of Moment) was taken into consideration for correction.…”