Reverse TOM Effect in May on United States capital market
Keywords:
Turn-of-the month effect, Halloween strategies, United States capital market
Abstract
Some circumstances could favor the increase of stock returns at the turn-of-the month. However, in the case of May, the influence of these circumstances could interfere with the selling stocks impact in the Halloween strategies framework. This paper approaches the behavior of returns from United States capital market in a time interval that starts in the last trading day of April, and it ends in the fourth trading day of May. For the period January 2010 – June 2025 we found abnormal low returns in this time interval.
References
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11. Breusch, T. S. and Pagan, A. R., 1979. A simple test for heteroscedasticity and random coefficient variation. Econometrica, 47(5), pp. 1287-1294.
12. Brown, P., Keim, D. B., Kleidon, A. W. and Marsh, T. A., 1983. Stock return seasonalities and the tax-loss selling hypothesis: Analysis of the arguments and Australian evidence. Journal of Financial Economics, 12(1), pp. 105-127.
13. Chowdhury, E. K. and Khan, I. I., 2024. Reactions of global stock markets to the Russia-Ukraine war: An empirical evidence. Asia-Pacific Financial Markets, 31(3), pp. 755-778.
14. Cortes, G. S., Gao, G. P., Silva, F. B. and Song, Z., 2022. Unconventional monetary policy and disaster risk: Evidence from the subprime and COVID–19 crises. Journal of International Money and Finance, 122, [online] Available at:
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16. Degenhardt, T. and Auer, B. R., 2018. The “Sell in May” effect: A review and new empirical evidence. The North American Journal of Economics and Finance, 43, pp. 169-205.
17. Dichtl, H. and Drobetz, W., 2015. Sell in May and go away: still good advice for investors?. International Review of Financial Analysis, 38, pp. 29-43.
18. Dickey, D.A. and Fuller, W.A., 1979. Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366a), pp. 427-431.
19. Dickey, D.A. and Fuller, W.A., 1981. Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica: Journal of the Econometric Society, pp. 1057-1072.
20. Dimson, E. and Marsh, P., 1999. Murphy's law and market anomalies. The Journal of Portfolio Management, 25(2), pp. 53-69.
21. Dimson, E. and Mussavian, M., 1998. A brief history of market efficiency. European Financial Management, 4(1), pp. 91-103.
22. Donders, M. W., Kouwenberg, R. and Vorst, T. C., 2000. Options and earnings announcements: an empirical study of volatility, trading volume, open interest and liquidity. European Financial Management, 6(2), pp. 149-171.
23. Dumontier, P. and Raffournier, B., 2002. Accounting and capital markets: a survey of the European evidence. European Accounting Review, 11(1), pp. 119-151.
24. Dzhabarov, C. and Ziemba, W. T., 2010. Do seasonal anomalies still work?. Journal of Portfolio Management, 36(3), pp.93-104.
25. Egger, P. H. and Zhu, J., 2020. The US–Chinese trade war: An event study of stock-market responses. Economic Policy, 35(103), pp. 519-559.
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28. Haggard, K. S. and Witte, H. D., 2010. The Halloween effect: trick or treat?. International Review of Financial Analysis, 19(5), pp. 379-387.
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30. Hensel, C. R., Sick, G. A. and Ziemba, W. T., 2000. A Long Term Examination of the Turn-of-the-Month Effect in the S&P 500. In Keim, D. B., & Ziemba, W. T. (Eds.) Security market imperfections in worldwide equity markets, Cambridge University Press, Cambridge, pp. 218-246.
31. Jacobsen, B. and Visaltanachoti, N., 2009. The Halloween effect in US sectors. Financial Review, 44(3), pp. 437-459.
32. Jansson, S., 1983. The fine art of window dressing. Institutional Investor, 17(12), pp. 139-140.
33. Jones, E., Danbolt, J. and Hirst, I., 2004. Company Investment Announcements and the Market Value of the Firm, European Journal of Finance, 10(5), pp. 437-452.
34. Keloharju, M., Linnainmaa, J. T. and Nyberg, P., 2016. Return seasonalities. The Journal of Finance, 71(4), pp. 1557-1590.
35. Kunkel, R. A., Compton, W. S. and Beyer, S., 2003. The turn-of-the-month effect still lives: the international evidence. International Review of Financial Analysis, 12(2), pp. 207-221.
36. Lakonishok, J., Shleifer, A., Thaler, R. H. and Vishny, R. W., 1991. Window dressing by pension fund managers. NBER Working Paper No. 3617, [online] Available at:
37. Lakonishok, J. and Smidt, S., 1986. Volume for winners and losers: Taxation and other motives for stock trading. The Journal of Finance, 41(4), pp. 951-974.
38. Lakonishok, J. and Smidt, S., 1988. Are seasonal anomalies real? A ninety-year perspective. The Review of Financial Studies, 1(4), pp. 403-425.
39. Levy, R. A., 1967. Random walks: Reality or myth. Financial Analysts Journal, 23(6), pp. 69-77.
40. Lloyd, R., Zhang, C. and Rydin, S., 2017. The Halloween Indicator is More a Treat than a Trick. Journal of Accounting & Finance (2158-3625), 17(6), [online] Available at:
41. Maberly, E. D. and Waggoner, D. F., 2000. Closing the question on the continuation of turn-of-the-month effects: evidence from the S&P 500 Index futures contract. FRB Atlanta Working Paper 2000-11, [online] Available at:
42. Magnusson, G., 2021. Trick or treat? The Halloween effect in stock markets revisited. Managerial Finance, 47(2), pp. 209-226.
43. Marquering, W., Nisser, J. and Valla, T., 2006. Disappearing anomalies: a dynamic analysis of the persistence of anomalies. Applied Financial Economics, 16(4), pp. 291-302.
44. Ogden, J. P., 1987. The end of the month as a preferred habitat: A test of operational efficiency in the money market. Journal of Financial and Quantitative Analysis, 22(3), pp. 329-343.
45. Ogden, J. P., 1990. Turn‐of‐month evaluations of liquid profits and stock returns: A common explanation for the monthly and January effects. The Journal of Finance, 45(4), pp. 1259-1272.
46. Oh, M. and Kim, D., 2024. Effect of the US–China trade war on stock markets: A financial contagion perspective. Journal of Financial Econometrics, 22(4), pp. 954-1005.
47. Pandey, D. K., 2025. Effects of Israel-Iran conflict: insights on global stock indices and currencies. Journal of Economic Studies, 52(4), pp. 762-783.
48. Patel, N. and Sewell, M., 2015. Calendar anomalies: a survey of the literature. International Journal of Behavioural Accounting and Finance, 5(2), pp. 99-121.
49. Pettengill, G. N. and Jordan, B. D., 1988. A comprehensive examination of volume effects and seasonality in daily security returns. Journal of Financial Research, 11(1), pp. 57-70.
50. Schwert, G. W., 2002. Anomalies and Market Efficiency. NBER Working Paper No. 9277, [online] Available at:
51. Sharma, S. S. and Narayan, P. K., 2014. New evidence on turn-of-the-month effects. Journal of International Financial Markets, Institutions and Money, 29, pp. 92-108.
52. Stefanescu, R. and Dumitriu, R., 2024. TOM Effect from US capital market during the meteorological seasons, [online] Available at:
53. Stefanescu, R. and Dumitriu, R., 2025. The returns of US capital market in the first days of purchase transactions associated to the Halloween strategies, [online] Available at:
54. Swinkels, L. and Van Vliet, P., 2012. An anatomy of calendar effects. Journal of Asset Management, 13(4), pp. 271-286.
55. Thaler, R., 1987. Anomalies: seasonal movements in security prices II: weekend, holiday, turn of the month, and intraday effects. Journal of Economic Perspectives, 1(2), pp. 169-177.
56. Wei, X. and Han, L., 2021. The impact of COVID-19 pandemic on transmission of monetary policy to financial markets. International Review of Financial Analysis, 74, [online] Available at:
57. Woolridge, J. R. and Snow, C. C., 1990. Stock market reaction to strategic investment decisions. Strategic Management Journal, 11(5), pp. 353-363.
58. Zhang, C. Y. and Jacobsen, B., 2021. The Halloween indicator, “Sell in May and Go Away”: Everywhere and all the time. Journal of International Money and Finance, 110(C), [online] Available at:
59. Ziemba, W. T. and Hensel, C. R., 1994. Worldwide security market anomalies. Philosophical Transactions of the Royal Society of London. Series A: Physical and Engineering Sciences, 347(1684), pp. 495-509.
2. Akaike, H., 1974. A new look at the statistical model identification. IEEE transactions on automatic control, 19(6), pp. 716-723.
3. Alexander, S. S., 1961. Price movements in speculative markets: Trends or random walks. Industrial Management Review (pre-1986), 2(2), pp. 7-26.
4. Andrade, S. C., Chhaochharia, V. and Fuerst, M. E., 2013. “Sell in May and Go Away” Just Won’t Go Away. Financial Analysts Journal, 69(4), pp. 94-105.
5. Arendas, P., Malacka, V. and Schwarzova, M., 2018. A closer look at the Halloween Effect: The case of the Dow Jones Industrial Average. International Journal of Financial Studies, 6(2), pp. 1-12.
6. Ariel, R. A., 1987. A monthly effect in stock returns. Journal of Financial Economics, 18(1), pp. 161-174.
7. Baker, S. R., Bloom, N., Davis, S. J., Kost, K. J., Sammon, M. C. And Viratyosin, T., 2020. The unprecedented stock market impact of COVID-19 . NBER Working Paper No. 26945, [online] Available at:
8. Bollerslev T., 1986. Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), pp. 307-27.
9. Bouman, S. and Jacobsen, B., 2002. The Halloween indicator, “sell in May and go away”: Another puzzle. American Economic Review, 92(5), pp. 1618-1635.
10. Boungou, W. and Yatié, A. (2022). The impact of the Ukraine–Russia war on world stock market returns. Economics Letters, 215, [online] Available at:
11. Breusch, T. S. and Pagan, A. R., 1979. A simple test for heteroscedasticity and random coefficient variation. Econometrica, 47(5), pp. 1287-1294.
12. Brown, P., Keim, D. B., Kleidon, A. W. and Marsh, T. A., 1983. Stock return seasonalities and the tax-loss selling hypothesis: Analysis of the arguments and Australian evidence. Journal of Financial Economics, 12(1), pp. 105-127.
13. Chowdhury, E. K. and Khan, I. I., 2024. Reactions of global stock markets to the Russia-Ukraine war: An empirical evidence. Asia-Pacific Financial Markets, 31(3), pp. 755-778.
14. Cortes, G. S., Gao, G. P., Silva, F. B. and Song, Z., 2022. Unconventional monetary policy and disaster risk: Evidence from the subprime and COVID–19 crises. Journal of International Money and Finance, 122, [online] Available at:
15. D’Amico, S. and King, T., 2023. Past and future effects of the recent monetary policy tightening. Chicago Fed Letter, No. 483, [online] Available at:
16. Degenhardt, T. and Auer, B. R., 2018. The “Sell in May” effect: A review and new empirical evidence. The North American Journal of Economics and Finance, 43, pp. 169-205.
17. Dichtl, H. and Drobetz, W., 2015. Sell in May and go away: still good advice for investors?. International Review of Financial Analysis, 38, pp. 29-43.
18. Dickey, D.A. and Fuller, W.A., 1979. Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366a), pp. 427-431.
19. Dickey, D.A. and Fuller, W.A., 1981. Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica: Journal of the Econometric Society, pp. 1057-1072.
20. Dimson, E. and Marsh, P., 1999. Murphy's law and market anomalies. The Journal of Portfolio Management, 25(2), pp. 53-69.
21. Dimson, E. and Mussavian, M., 1998. A brief history of market efficiency. European Financial Management, 4(1), pp. 91-103.
22. Donders, M. W., Kouwenberg, R. and Vorst, T. C., 2000. Options and earnings announcements: an empirical study of volatility, trading volume, open interest and liquidity. European Financial Management, 6(2), pp. 149-171.
23. Dumontier, P. and Raffournier, B., 2002. Accounting and capital markets: a survey of the European evidence. European Accounting Review, 11(1), pp. 119-151.
24. Dzhabarov, C. and Ziemba, W. T., 2010. Do seasonal anomalies still work?. Journal of Portfolio Management, 36(3), pp.93-104.
25. Egger, P. H. and Zhu, J., 2020. The US–Chinese trade war: An event study of stock-market responses. Economic Policy, 35(103), pp. 519-559.
26. Engle, R.F., 1982. Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica: Journal of the Econometric Society, pp. 987-1007.
27. Fama, E., 1970. Efficient capital markets: a review of theory and empirical work. Journal of Finance, 25, pp. 383-417.
28. Haggard, K. S. and Witte, H. D., 2010. The Halloween effect: trick or treat?. International Review of Financial Analysis, 19(5), pp. 379-387.
29. Han, L., Han, Y. and Tian, S., 2025. The disappearing turn-of-month effect. Finance Research Letters, 71, [online] Available at:
30. Hensel, C. R., Sick, G. A. and Ziemba, W. T., 2000. A Long Term Examination of the Turn-of-the-Month Effect in the S&P 500. In Keim, D. B., & Ziemba, W. T. (Eds.) Security market imperfections in worldwide equity markets, Cambridge University Press, Cambridge, pp. 218-246.
31. Jacobsen, B. and Visaltanachoti, N., 2009. The Halloween effect in US sectors. Financial Review, 44(3), pp. 437-459.
32. Jansson, S., 1983. The fine art of window dressing. Institutional Investor, 17(12), pp. 139-140.
33. Jones, E., Danbolt, J. and Hirst, I., 2004. Company Investment Announcements and the Market Value of the Firm, European Journal of Finance, 10(5), pp. 437-452.
34. Keloharju, M., Linnainmaa, J. T. and Nyberg, P., 2016. Return seasonalities. The Journal of Finance, 71(4), pp. 1557-1590.
35. Kunkel, R. A., Compton, W. S. and Beyer, S., 2003. The turn-of-the-month effect still lives: the international evidence. International Review of Financial Analysis, 12(2), pp. 207-221.
36. Lakonishok, J., Shleifer, A., Thaler, R. H. and Vishny, R. W., 1991. Window dressing by pension fund managers. NBER Working Paper No. 3617, [online] Available at:
37. Lakonishok, J. and Smidt, S., 1986. Volume for winners and losers: Taxation and other motives for stock trading. The Journal of Finance, 41(4), pp. 951-974.
38. Lakonishok, J. and Smidt, S., 1988. Are seasonal anomalies real? A ninety-year perspective. The Review of Financial Studies, 1(4), pp. 403-425.
39. Levy, R. A., 1967. Random walks: Reality or myth. Financial Analysts Journal, 23(6), pp. 69-77.
40. Lloyd, R., Zhang, C. and Rydin, S., 2017. The Halloween Indicator is More a Treat than a Trick. Journal of Accounting & Finance (2158-3625), 17(6), [online] Available at:
41. Maberly, E. D. and Waggoner, D. F., 2000. Closing the question on the continuation of turn-of-the-month effects: evidence from the S&P 500 Index futures contract. FRB Atlanta Working Paper 2000-11, [online] Available at:
42. Magnusson, G., 2021. Trick or treat? The Halloween effect in stock markets revisited. Managerial Finance, 47(2), pp. 209-226.
43. Marquering, W., Nisser, J. and Valla, T., 2006. Disappearing anomalies: a dynamic analysis of the persistence of anomalies. Applied Financial Economics, 16(4), pp. 291-302.
44. Ogden, J. P., 1987. The end of the month as a preferred habitat: A test of operational efficiency in the money market. Journal of Financial and Quantitative Analysis, 22(3), pp. 329-343.
45. Ogden, J. P., 1990. Turn‐of‐month evaluations of liquid profits and stock returns: A common explanation for the monthly and January effects. The Journal of Finance, 45(4), pp. 1259-1272.
46. Oh, M. and Kim, D., 2024. Effect of the US–China trade war on stock markets: A financial contagion perspective. Journal of Financial Econometrics, 22(4), pp. 954-1005.
47. Pandey, D. K., 2025. Effects of Israel-Iran conflict: insights on global stock indices and currencies. Journal of Economic Studies, 52(4), pp. 762-783.
48. Patel, N. and Sewell, M., 2015. Calendar anomalies: a survey of the literature. International Journal of Behavioural Accounting and Finance, 5(2), pp. 99-121.
49. Pettengill, G. N. and Jordan, B. D., 1988. A comprehensive examination of volume effects and seasonality in daily security returns. Journal of Financial Research, 11(1), pp. 57-70.
50. Schwert, G. W., 2002. Anomalies and Market Efficiency. NBER Working Paper No. 9277, [online] Available at:
51. Sharma, S. S. and Narayan, P. K., 2014. New evidence on turn-of-the-month effects. Journal of International Financial Markets, Institutions and Money, 29, pp. 92-108.
52. Stefanescu, R. and Dumitriu, R., 2024. TOM Effect from US capital market during the meteorological seasons, [online] Available at:
53. Stefanescu, R. and Dumitriu, R., 2025. The returns of US capital market in the first days of purchase transactions associated to the Halloween strategies, [online] Available at:
54. Swinkels, L. and Van Vliet, P., 2012. An anatomy of calendar effects. Journal of Asset Management, 13(4), pp. 271-286.
55. Thaler, R., 1987. Anomalies: seasonal movements in security prices II: weekend, holiday, turn of the month, and intraday effects. Journal of Economic Perspectives, 1(2), pp. 169-177.
56. Wei, X. and Han, L., 2021. The impact of COVID-19 pandemic on transmission of monetary policy to financial markets. International Review of Financial Analysis, 74, [online] Available at:
57. Woolridge, J. R. and Snow, C. C., 1990. Stock market reaction to strategic investment decisions. Strategic Management Journal, 11(5), pp. 353-363.
58. Zhang, C. Y. and Jacobsen, B., 2021. The Halloween indicator, “Sell in May and Go Away”: Everywhere and all the time. Journal of International Money and Finance, 110(C), [online] Available at:
59. Ziemba, W. T. and Hensel, C. R., 1994. Worldwide security market anomalies. Philosophical Transactions of the Royal Society of London. Series A: Physical and Engineering Sciences, 347(1684), pp. 495-509.
Published
2025-12-25
How to Cite
Stefanescu, R., & Dumitriu, R. (2025). Reverse TOM Effect in May on United States capital market. Vanguard Scientific Instruments in Management, 21(1), 30-40. Retrieved from https://vsim-journal.info/index.php?journal=vsim&page=article&op=view&path[]=564
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Articles
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