A Comparison of Global Factor Models

Hanauer, Matthias X.

doi:10.2139/ssrn.3546295

Cited by 25 publications

(5 citation statements)

References 110 publications

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“…Recently, asset pricing models have typically contained at least four or five factors, though six are also commonly seen. See, for instance, Barillas and Shanken (2018), Fama and and French (2018), Kan et al (2024) or Hanauer (2020). Given the state of the literature, our choice of test assets and factors sits comfortably amidst the typical empirical asset pricing applications.…”

Section: Appendix B Details Of the Empirical Resultsmentioning

confidence: 99%

Testing and Ranking of Asset Pricing Models Using the GRS Statistic

Kamstra,

Shi

2024

JRFM

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We clear up an ambiguity in the statement of the GRS statistic by providing the correct formula of the GRS statistic and the first proof of its F-distribution in the general multiple-factor case. Casual generalization of the Sharpe-ratio-based interpretation of the single-factor GRS statistic to the multiple-portfolio case makes experts in asset pricing studies susceptible to an incorrect formula. We illustrate the consequences of using the incorrect formulas that the ambiguity in GRS leads to—over-rejecting and misranking asset pricing models. In addition, we suggest a new approach to ranking models using the GRS statistic p-value.

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Section: Appendix B Details Of the Empirical Resultsmentioning

confidence: 99%

Testing and Ranking of Asset Pricing Models Using the GRS Statistic

Kamstra,

Shi

2024

JRFM

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“…These factors have been shown to explain equity returns in international markets. For instance, the five‐factor version of the model of Fama and French (2015, 2018) excluding momentum has been shown to explain returns in global equity markets by Hanauer (2020) and in Australia by Chai et al . (2019).…”

Section: Methodsmentioning

confidence: 99%

“…These factors have been shown to explain equity returns in international markets. For instance, the five-factor version of the model of French (2015, 2018) excluding momentum has been shown to explain returns in global equity markets by Hanauer (2020) and in Australia by Chai et al (2019). Value and size premiums have been found in markets around the world (e.g., Bauman et al, 1998); Fama and French, 1998. Various studies highlight the profitability of momentum strategies internationally (e.g., Rouwenhorst, 1998Rouwenhorst, , 1999Chan et al, 2000;Chui et al, 2010;Fama and French, 2012;Asness et al, 2013).…”

Section: Factor Selectionmentioning

confidence: 99%

“…The method employed readily supports expansion of the number of equity factors alongside the integration of currency into the evaluation of global equity fund performance. This fills a gap in the literature, which often glosses over currency through examining returns in US dollars only (Griffin, 2002; Fama and French, 2012; Hou et al ., 2015; Dyakov and Wipplinger, 2020; Hanauer, 2020). One exception where currency factors have been incorporated alongside equity factors is Brusa et al ., (2016).…”

Section: Introductionmentioning

confidence: 99%

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Global equity fund performance adjusted for equity and currency factors

Gallagher

Harman²,

Schmidt³

et al. 2021

Accounting & Finance

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We present a method for evaluating performance of global equity funds that decomposes excess returns versus market indices into contributions from six equity and three currency factors plus alpha. We apply the method to a sample of institutional fund mandates, and uncover outperformance stemming from stock selection while finding that both equity and currency factor exposures detract from returns. Our methodological contribution is to propose a portfolio holding‐based approach for identifying return sources for funds investing internationally that can account for multiple factor exposures including those arising from currency.

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“…For studying the UK equity market, we follow Hanauer (2020) to replicate all following UK tradable factors:…”

Section: Data and Candidate Modelsmentioning

confidence: 99%

Tradable or nontradable factors—what does the Hansen–Jagannathan distance tell us?

Zhang

Liu

Wu³

et al. 2021

International Review of Economics & Finance

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We investigate the difference in pricing performance between tradable and nontradable factors in terms of explaining cross-sectional portfolio returns by comparing the Hansen-Jagannathan (HJ) distance misspecification measures. By constructing nontradable factors mimicking portfolios and incorporating them into the least misspecified tradable stochastic discount factor (SDF), we provide cross-country empirical evidence that this single proxy SDF dominates others to price crosssectional risky assets. Since nontradable factors mimicking portfolios (FMPs) are functions of current risky factors information about the economic state, therefore FMPs "hedge" the state variable risks and FMPs' returns describe the risk premiums.

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A Comparison of Global Factor Models

Cited by 25 publications

References 110 publications

Testing and Ranking of Asset Pricing Models Using the GRS Statistic

Testing and Ranking of Asset Pricing Models Using the GRS Statistic

Global equity fund performance adjusted for equity and currency factors

Tradable or nontradable factors—what does the Hansen–Jagannathan distance tell us?

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