Subject. The article considers the development of special statistical methods for estimating and analyzing the liquidity risk. Objectives. The purpose is to improve the methodology for statistical appraisal and analysis of risk in equity trading. Methods. The study rests both on well-known methods for equity risk analysis and my own development results (calculation of equity annual illiquidity ratio, formation of illiquidity risk factor). The data analyzed in this paper come from the Moscow Exchange (MOEX) and cover January 2011 to May 2021. The sample included all common stocks traded on MOEX and issuers’ financial statements. I also apply analysis and synthesis, induction and deduction, and methods of comparison and grouping. Results. I calculated monthly illiquidity factor as zero-investment long-short portfolio. I examined the impact of illiquidity risk on the return dynamics of size, book-to-market ratio sorted portfolios. Conclusions. The study shows that expected equity returns are related cross-sectionally to the illiquidity factor. The evidence strongly supports the hypothesis that the illiquidity risk factor is priced. The premium for this risk is positive and offers higher expected returns in equities with strong illiquidity. However, for liquid equities no significant premium is revealed. The offered approach to the factor equity risk analysis based on illiquidity risk enables a true picture of how the risks impact the equity trading performance and how they can be improved in the future.
Keywords: hedging, portfolio, price anomaly, value
References:
Amihud Y., Mendelson H. Asset pricing and the bid-ask spread. Journal of Financial Economics, 1986, vol. 17, iss. 2, pp. 223–249. URL: Link90065-6
Brennan M.J., Chordia T., Subrahmanyam A. Alternative factor specifications, security characteristics, and the cross-section of expected stock returns. Journal of Financial Economics, 1998, vol. 49, iss. 3, pp. 345–373. URL: Link00028-2
Franzoni F., Nowak E., Phalippou L. Private equity performance and liquidity risk. The Journal of Finance, 2012, vol. 67, iss. 6, pp. 2341–2373. URL: Link
Hongtao Li, Novy-Marx R., Velikov M. Liquidity Risk and Asset Pricing. Critical Finance Review, 2019, vol. 8, iss. 1-2, pp. 223–255. URL: Link
Pontiff J., Singla R. ‘Liquidity Risk?’. Critical Finance Review, 2019, vol. 8, iss. 1-2, pp. 257–276. URL: Link
Hasbrouck J., Seppi D.J. Common factors in prices, order flows, and liquidity. Journal of Financial Economics, 2001, vol. 59, iss. 3, pp. 383–411. URL: Link00091-X
Huberman G., Halka D. Systematic liquidity. The Journal of Financial Research, 2001, vol. 24, iss. 2, pp. 161–178. URL: Link
Lo A.W., Wang J. Trading volume: Definitions, data analysis, and implications of portfolio theory. The Review of Financial Studies, 2000, vol. 13, iss. 2, pp. 257–300. URL: Link
Eisfeldt A.L. Endogenous Liquidity in Asset Markets. The Journal of Finance, 2004, vol. 59, iss. 1, pp. 1–30. URL: Link
Kogdenko V.G. [Specifics of analysis of companies operating in the digital economy]. Ekonomicheskii analiz: teoriya i praktika =Economic Analysis: Theory and Practice, 2018, vol. 17, iss. 3, pp. 424–438. (In Russ.) URL: Link
Lapteva E.A., Bezaev I.I. [Statistical and econometric assessment of risk]. Ekonomicheskii analiz: teoriya i praktika =Economic Analysis: Theory and Practice, 2018, vol. 17, iss. 2, pp. 365–378. (In Russ.) URL: Link
Sapozhnikova N.G. [Impairment of Assets and Corporation Risk]. Vestnik Voronezhskogo gosudarstvennogo universiteta. Ser.: Ekonomika i upravlenie = Proceedings of Voronezh State University. Series: Economics and Management, 2020, no. 2, pp. 105–115. URL: Link (In Russ.)
Ushakova N.V., Vasin A.S., Fatuev V.A. [A study of factors that affect the overall risk of owners of ordinary shares]. Ekonomicheskii analiz: teoriya i praktika =Economic Analysis: Theory and Practice, 2019, vol. 18, iss. 6, pp. 1111–1123. (In Russ.) URL: Link
Endovitsky D.A., Davnis V.V., Korotkikh V.V. Adaptive trend decomposition method in financial time series analysis. The Journal of Social Sciences Research, 2018, no. 3, pp. 104–109. URL: Link
Endovitsky D.A., Davnis V.V., Korotkikh V.V. On two hypotheses in economic analysis of stochastic processes. Journal of Advanced Research in Law and Economics, 2017, vol. 8, iss. 8, pp. 2391–2398. URL: Link.09
Fama E.F., French K.R. Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 1993, vol. 33, iss. 1, pp. 3–56. URL: Link90023-5
Fama E.F., French K.R. Choosing factors. Journal of Financial Economics, 2018, vol. 128, iss. 2, pp. 234–252. URL: Link
Fama E.F., French K.R. Size, value, and momentum in international stock returns. Journal of Financial Economics, 2012, vol. 105, iss. 3, pp. 457–472. URL: Link
Asness C.S., Frazzini A. The devil in HML’s details. The Journal of Portfolio Management, 2013, vol. 39, iss. 4, pp. 49–68. URL: Link
Hanauer M.X., Windmüller S. Enhanced Momentum Strategies (August 14, 2019). URL: Link
Ozornov S. Validity of Fama and French model on RTS Index. Review of Business and Economics Studies, 2015, vol. 3, iss. 4, pp. 22–43. URL: Link. (In Russ.)
Amihud Y. Illiquidity and stock returns: Cross-section and time-series effects. Journal of Financial Markets, 2002, vol. 5, iss. 1, pp. 31–56. URL: Link00024-6
Brown A. Did the Financial Crisis Kill Fama-French? Wilmott, 2020, iss. 109, pp. 16–18. URL: Link
