2024-02-15

Overview

This README file provides information about the data and the computer code used to generate the results presented in Ardia et al. (2024), Is it alpha or beta? Decomposing hedge fund returns when models are misspecified, Journal of Financial Economics, 154, 103805. https://doi.org/10.1016/j.jfineco.2024.103805

By using the code, you agree to the following rules:

• You must cite the paper in working papers and published papers that use the code.
• You must place the DOI of this data/code repository in a footnote to help others find it.
• You assume all risk for the use of the code.

All datasets are proprietary. We do not have the rights to share any of the data. We provide pseudo data to illustrate the code usage.

The computer code is written in R. We provide the code to reproduce the tables and figures in the paper.

Data Availability and Provenance Statements

All datasets are proprietary. Factor data are available from other researchers' websites, while hedge fund data and mutual fund data come from commercial databases. See below for details.

Data Sources for the Factors

Please refer to Section 4.2 in the paper and Section III.B in the Supplementary Materials.

Data Sources for the Hedge Funds

Please refer to Section 4.1 in the paper and Section III.A in the Supplementary Materials.

Data Sources for the Mutual Funds

Please refer to Section III.A in Barras et al. (2022) and Section V of its Supplementary Material.

Summary of Availability

No data can be made publicly available. Data used in this paper and not provided as part of the public replication package will be preserved for one year after publication.

Datasets

We provide two pseudo datasets for running the code: Db_Factors_Pseudo.rda and Db_HF_Pseudo.rda located in the folder data.

Data File	Description
Db_Factors_Pseudo.rda	Matrix Factors of size 324 x 28 that contains monthly returns from 1994-01 to 2020-12 of 28 fake pseudo factors
	FF_EMKT market factor
	FF_HML value factor
	FF_SMB size factor
	FF_MOM momentum factor
	FF_CMA investment factor
	FF_RMW profitability factor
	FH_TERM_FH term factor
	FH_DFLT_FH default factor
	FH_PTFSBD straddle on bonds factor
	FH_PTFSCOM straddle on commodities factor
	FH_PTFSFX straddle on currencies factor
	AQR_VME_VAL global value factor
	AQR_VME_MOM global momentum factor
	AQR_TSMOM time-series momentum factor
	AQR_BAB_USA BAB factor
	BH_VARVIX variance factor
	KMPV_GCF carry factor
	PS_LIQ illiquidity factor
	KNS_dindrrevlv, KNS_dindmomrev, KNS_dindrrev, KNS_dseason, and KNS_dsue machine learning portfolios factors
	KNS_pc_d5, KNS_pc_d1, KNS_pc_d6, KNS_pc_d12, and KNS_pc_d2 machine learning principal components factors
Db_HF_Pseudo.rda	List Db_HF containing information for 2000 fake pseudo hedge funds
	id vector of size 2000 of fund id
	dates vector of size 324 of dates
	ret matrix of size 324 x 2000 of monthly returns [%]
	aum matrix of size 324 x 2000 of monthly aums [usd]
	strat vector of size 2000 of fund main strategy
	substrat vector of size 2000 of fund sub-strategy
	mf vector of size 2000 of fund management fees [%]
	pf vector of size 2000 of fund performance fees [%]
	hwm vector of size 2000 of fund highwater mark [true/false]
	hr vector of size 2000 of fund hurdle rate [true/false]
	np vector of size 2000 of fund notice period [month]
	lp vector of size 2000 of fund lookup period [year]

Computational Requirements

You must have R installed and a C++ compiler (such as GCC) to run Rcpp/RcppArmadillo.

Software Requirements

The file run_install_packages.R will install all dependencies (latest version) and should be run once before running other programs. See the file session_info.txt in the folder outputs to see the exact setup that generated the results in the paper.

Description of Programs/Code

• The file run_install_packages.R will install all dependencies (latest version) and should be run once before running other programs.
• The file run_results.R will generate all tables and figures in the paper using the pseudo data sets. Be careful, as it will overwrite the content of the outputs folder.

License for Code

The code is under the GPL-3 license; see the file LICENSE.txt. Moreover, if you use part of the computer code in your research, you must cite Ardia et al. (202x) and add a footnote pointing to the code/data repository.

Instructions to Replicators

• Run run_install_packages.R to install the missing packages.
• Run run_results.R to generate all tables (except Tables 8 and 9) and all figures in the papers. They will be saved in the folder outputs.

List of Tables/Figures and Programs

The provided code reproduces all tables and figures in the paper.

Figure/Table #	Line Number	Output file	Note
Table 1	27	Table1.txt
Table 2	86	Table2.txt
Table 4	153	Table4r2.txt	R2 in Table 4
Table 6	198	Table6a.txt, Table6b.txt
Table 5	267	Table5.txt
Table 4	309	Table4.txt
Table 7a	336	Table7a.txt
Table 7b	371	Table7b.txt
Figure 3a-4	385	Figure3a.pdf, Figure4.pdf
Table 11	505	Table11a.txt, Table11b.txt, Table11c.txt
Figure 2	628	Figure2a.pdf,Figure2b.pdf
Table 10	683	Table10.txt	Generate results for management fees. To generate each panel, uncomment other parts of the code
Figure 1	739	Figure1.pdf

Table 3 does not require any code to be run. Tables 8 and 9 are category-specific cases of Table 5 and Table 7. Please proceed as follows to generate them.

Table #	Note
Table 8	Uncomment line 248 and run the code for Table 5 above
Table 9	Uncomment line 248 and run the code for Table 7 above

References

Ardia D., Barras L., Gagilardini P., and O. Scaillet. 2024. Is it alpha or beta? Decomposing hedge fund returns when models are misspecified. Journal of Financial Economics 154:103805. https://doi.org/10.1016/j.jfineco.2024.103805

Barras L., Gagilardini P., and O. Scaillet. 2022. Skill, scale, and value creation in the mutual fund industry. Journal of Finance 77:601-638. https://doi.org/10.1111/jofi.13096

Carhart, M. 1997. On persistence in mutual fund performance. Journal of Finance 52:57-82. https://doi.org/10.1111/j.1540-6261.1997.tb03808.x

Fama, E. F., and K. R. French. 2015. A five-factor asset pricing model. Journal of Financial Economics 116:1-22. https://doi.org/10.1016/j.jfineco.2014.10.010

Frazzini, A., and L. H. Pedersen. 2014. Betting against beta. Journal of Financial Economics 111:1-25. https://doi.org/10.1016/j.jfineco.2013.10.005

Fung, W., and D. A. Hsieh. 2004. Hedge fund benchmarks: A risk-based approach. Financial Analysts Journal 60:65-80. https://doi.org/10.2469/faj.v60.n5.2657

Koijen, R. S. J., T. J. Moskowitz, L. H. Pedersen, and E. B. Vrugt. 2018. Carry. Journal of Financial Economics 127:197-225. https://doi.org/10.1016/j.jfineco.2017.11.002

Kozak, S., S. Nagel, and S. Santosh. 2020. Shrinking the cross-section. Journal of Financial Economics 135:271-92. https://doi.org/10.1016/j.jfineco.2019.06.008

Moskowitz, T. J., Y. H. Ooi, and L. H. Pedersen. 2012. Time series momentum. Journal of Financial Economics 104:228-50. https://doi.org/10.1016/j.jfineco.2011.11.003

Pastor, L., and R. F. Stambaugh. 2003. Liquidity risk and expected stock returns. Journal of Political Economy 111:642-85. https://doi.org/10.1086/374184

Acknowledgements

Some content on this page was copied from Hindawi. Other content was adapted from Fort (2016), Supplementary data, with the author's permission.