The Impact of Information Dissemination (with an Emphasis on Information Discreteness and Continuity) on Time Series Industry Momentum

Subject Areas : Role of accounting in capital market efficiency and Informativeness

Fatemeh Ahmadi.NezamAbadi ^{1 *} , seyed rasoul hosayni ² , Azar Moslemi ³ , Abolfazl Saeidifar ⁴

1 -
2 - Assistant Professor, Department of Accounting, Faculty of Humanities, Zanjan University
3 - Assistant Professor, Department of Accounting, Khomein Branch, Islamic Azad University, Khomein, Iran
4 - Assistant Professor, Department of Mathematics and Statistics, Arak Branch, Islamic Azad University, Arak, Iran

Received: 2025-03-31 Accepted : 2025-06-09 Published : 2025-06-21

Keywords: Time series momentum, information discreteness, information noise, frog-in-the-pan hypothesis.,

Abstract :

The momentum effect is one of the most well-documented anomalies and one of the clearest pieces of evidence against efficient market theory, refuting it even at its most conservative levels. The time series momentum effect serves as an alternative framework to cross-sectional momentum, and both phenomena can be explained by the psychological behavior of investors. The impact of information dissemination on time series industry momentum is analyzed through two elements of information dissemination: information discreteness and information uncertainty.A systematic elimination method was used to select 120 companies from stock exchange firms, and the analysis was conducted across four random ten-stock portfolios.

Information discreteness measures the scale of information arrival and uncertainty, capturing the level of noise present in the information. To investigate the time series momentum effect, strategies with two categories of formation and holding periods—ranging from 3, 6, 9, ..., to 36 months between the years 2021 and 2023—were considered in order to eliminate external control effects such as strategy volatility management and volatility objectives. Since time series momentum represents a long-term investment strategy with variable behavior across different time horizons, its examination across twelve formation and holding period strategies revealed that information dissemination significantly impacts industry momentum in long-term formation and holding strategies. Given that the hypothesis regarding the effect of time series industry momentum being influenced by information dissemination was significant in most formation and holding strategies, this hypothesis is confirmed.

References:

- تلنگی و راعی، احمد؛ رضا، (1391). مدیریت سرمایه گذاری پیشرفته، انتشارات سمت‌ .
- فلاحی فیروز, پناهی حسین, & کریمی کندوله مریم. (2018). بررسی هم بستگی بین بازده ی بازار سهام، ارز و سکه در اقتصاد ایران؛ کاربردی از تبدیل هیلبرت-هوانگ.
- گرجی آرا و حسینی، محمد و حوریه السادات، (1401). مروری جامع بر مدیریت سرمایه گذاری و ریسک، انتشارات نگاه دانش‌ .
- هاشمی, س. ع., میرکی, ف., & فؤاد. (2013). بررسی بازده مازاد بر ریسک مومنتوم در بورس اوراق بهادار تهران. حسابداری و منافع اجتماعی, 3(1), 39-56.
Andrei, D., & Cujean, J. (2017). Information percolation, momentum and reversal. Journal of Financial Economics, 123(3), 617-645.‏
Asness, C. S., Moskowitz, T. J., & Pedersen, L. H. (2013). Value and momentum everywhere. The Journal of Finance, 68(3), 929–985.
Ball, R. (2009). The global financial crisis and the efficient market hypothesis: What have we learned? Journal of Applied Corporate Finance, 21(4), 8–16.
Barberis, N., Shleifer, A. and Vishny, R. (1998) ‘A model of investor sentiment’, Journal of Financial Economics, 49(3), pp. 307–343 .
Barroso, P. and Santa-Clara, P. (2015) ‘Momentum has its moments’, Journal of Financial Economics, 116(1), pp. 111-120.
Borgards, O. (2021). Dynamic time series momentum of cryptocurrencies. The North American Journal of Economics and Finance, 57, 101428.‏
Boubaker, S., Du, L., & Liu, Z. (2021). Industry momentum with correlation consolidation: evidence from China. Journal of Asset Management, 1-10.‏
Chan, L. K., Jegadeesh, N., & Lakonishok, J. (1996). Momentum strategies. The Journal of finance, 51(5), 1681-1713.‏
Chordia, T., Roll, R. and Subrahmanyam, A. (2001) ‘Market liquidity and Trading Activity’, The Journal of Finance, 56 (2), pp. 501-530 .
Connolly, R., & Stivers, C. (2003). Momentum and reversals in equity‐index returns during periods of abnormal turnover and return dispersion. The Journal of Finance, 58(4), 1521-1556.‏
Conrad, J. and Kaul, G. (1998) ‘An Antomy of Trading Strategies’, The Review of
Financial Studies, 11(3), pp. 489-519.
Cooper, M.J., Gutierrez, R.C. and Hameed, A. (2004) ‘Market States and Momentum’, The Journal of Finance, 59 (3), pp.1345-1365.
Da, Z., Gurun, U. G., & Warachka, M. (2014). Frog in the pan: Continuous information and momentum. The review of financial studies, 27(7), 2171-2218.‏
Daniel, K., Hirshleifer, D., & Subrahmanyam, A. (1998). Investor psychology and security market under‐and overreactions. the Journal of Finance, 53(6), 1839-1885.‏
Daniel, K., & Moskowitz, T. J. (2016). Momentum crashes. Journal of Financial economics, 122(2), 221-247.‏
Doukas, J. A., & McKnight, P. J. (2005). European momentum strategies, information diffusion, and investor conservatism. European Financial Management, 11(3), 313-338.‏
Du D, Denning K (2005) Industry momentum and common stocks. Financ Res Lett 2:107–124
Fama, E. F. (1965). The behavior of stock-market prices. Journal of Business, 38(1), 34–105.
Fama, E. F., and K. R. French. 2008. "Dissecting anomalies." The Journal of Finance 63 (4):1653-78.
Fang, Y. (2021). The time series momentum effect: the impact of information diffusion and time-varying risk (Doctoral dissertation, Loughborough University).‏
Goyal, A., & Jegadeesh, N. (2018). Cross-sec0tional and time-series tests of return predictability: What is the difference?. The Review of Financial Studies, 31(5), 1784-1824.‏
Grinblatt M, Han B (2005) Prospect theory, mental accounting, and momentum. J Financ Econ 78:311–339
Grundy, B. D., & Martin, J. S. M. (2001). Understanding the nature of the risks and the source of the rewards to momentum investing. The Review of Financial Studies, 14(1), 29-78.‏
Hong, H., & Stein, J. C. (1999). A unified theory of underreaction, momentum trading, and overreaction in asset markets. The Journal of finance, 54(6), 2143-2184.‏
Hou, K., Xue, C., & Zhang, L. (2020). Replicating anomalies. Review of Financial Studies, 33(5), 2019–2133 .
Huang, D., Li, J., Wang, L., & Zhou, G. (2020) ‘Time-series momentum: Is it there?’, Journal of Financial Economics, 135(3), pp. 774-794.
Huang, S., Lee, C. M., Song, Y., & Xiang, H. (2022). A frog in every pan: Information discreteness and the lead-lag returns puzzle. Journal of Financial Economics, 145(2), 83-102
Hutchinson, M. C., & O'Brien, J. (2020). Time series momentum and macroeconomic risk. International review of financial analysis, 69, 101469.‏
Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. The Journal of finance, 48(1), 65-91.‏
Jegadeesh, N., & Titman, S. (2001). Profitability of momentum strategies: An evaluation of alternative explanations. The Journal of finance, 56(2), 699-720.‏
Jiang, G.J. and Zhu, K.X. (2017) ‘Information Shocks and Short-Term Market Underreaction’, Journal of Financial Economics, 124(1), pp. 43-64.
Kim, A. Y., Tse, Y., & Wald, J. K. (2016). Time series momentum and volatility scaling. Journal of Financial Markets, 30, 103-124.‏
Li B, Stork T, Chai D, Ee MS, Ang HN (2014) Momentum effects in Australian eq9uities: revisit, armed with short-selling ban and risk factors. Pac Basin Financ J 27:1–31
Lin, C., Ko, K. C., Chen, Y. L., & Chu, H. H. (2016). Information discreteness, price limits and earnings momentum. Pacific-Basin Finance Journal, 37, 1-22.‏
Lou, D. (2012) ‘A Flow-Based Explanation for Return Predictability’, The Review of Financial Studies, 25(12), pp. 3457-3489.
Menkhoff, L., Sarno, L., Schmeling, M., & Schrimpf, A. (2012). Currency momentum strategies. Journal of Financial Economic, 106(3), 660–684.
Miffre, J., & Rallis, G. (2007). Momentum strategies in commodity futures markets. Journal of Banking & Finance, 31(6), 1863–1886.
Moskowitz, T. J., & Grinblatt, M. (1999). Do industries explain momentum?. The Journal of finance, 54(4), 1249-1290.‏
Moskowitz, T. J., Ooi, Y. H., & Pedersen, L. H. (2012). Time series momentum. Journal of financial economics, 104(2), 228-250.‏
Nijiman T, Swinkels L, Verbeek M (2004) Do countries or industries explain momentum in Europe? J Empir Financ 11:461–481.
O’Neal, E.S. (2000) ‘Industry Momentum and Sector Mutual Funds’, Financial Analysts Journal, 56(4),pp. 37-49.
Pitkäjärvi, A., Suominen, M., & Vaittinen, L. (2020). Cross-asset signals and time series momentum. Journal of Financial Economics, 136(1), 63-85.
Rouwenhorst, K. (1998) ‘International Momentum Strategies’, The Journal of Finance, 53(1), pp. 267-284.
Scowcroft, A., & Sefton, J. (2005). Understanding momentum. Financial Analysts Journal, 61(2), 64-82.‏
Tan, Y. M., & Cheng, F. F. (2019). Industry-and liquidity-based momentum in Australian equities. Financial Innovation, 5(1), 43.‏
Wiest, T. (2023). Momentum: what do we know 30 years after Jegadeesh and -Titman’s seminal paper?. Financial Markets and Portfolio Management, 37(1), 95-114.‏
Zhang, X. F. (2006). Information uncertainty and stock returns. The journal of Finance, 61(1), 105-137.‏Borgards, O. (2021). Dynamic time series momentum of cryptocurrencies. The North American Journal of Economics and Finance, 57, 101428.