AN INVESTMENT CHOICE PROBLEM AND CALENDAR ANOMALIES: A GROUP AHP MODEL FOR INVESTORS
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Published
Aug 28, 2020
Gabriella Marcarelli
Matteo Rossi Antonella Ferrarro Antonio Lucadamo
http://orcid.org/0000-0003-4085-4484
Matteo Rossi Antonella Ferrarro Antonio Lucadamo
Abstract
An investment choice can be influenced by numerous qualitative and quantitative factors that often conflict with one other. Therefore, portfolio management choice is a multi-criteria decision problem that requires flexible and analytic decision tools for investors. For this task, the Analytic Hierarchy Process (AHP) is suitable. We propose an AHP group-based model to analyze an investment choice problem looking at two financial markets including Spain and France. The evaluation criteria that we used in our model are the return of the stock market, performance of government bonds and calendar effects in the financial markets. The 2017 French and Spanish equity market returns and the government bond performances for each country are available in public databases. Mean tests were performed in order to analyze calendar anomalies for both of the markets from 2007-2017. The aim of our study is to propose a model that allows simultaneous evaluation of the impact of the previously mentioned factors on investment choice. Our analysis involves 69 students from the Department DEMM of the University of Sannio (Italy) who have worked on financial market simulators. The data were obtained using questionnaires. The common priority vector procedure (CPVP) was used to determine the individual priorities (derived by individual judgments matrices) and aggregate the individual priorities (derived by individual judgments matrices) to obtain the group preferences. The results show that the decision makers prefer to invest in diversified portfolios.
How to Cite
Marcarelli, G., Rossi, M., Ferrarro, A., & Lucadamo, A. (2020). AN INVESTMENT CHOICE PROBLEM AND CALENDAR ANOMALIES: A GROUP AHP MODEL FOR INVESTORS. International Journal of the Analytic Hierarchy Process, 12(2). https://doi.org/10.13033/ijahp.v12i1.726
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Keywords
AHP, calendar anomalies, government bonds, stock market, investment choice, consistency
References
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Jaffe, J. & Westerfield, R. (1985). The weekend effect in common stock returns: the international evidence. Journal of Finance, 40, 237-44.
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Al-Loughani, N.E., Al-Saad, K.M. and Ali, M.M. (2005). The holiday effect and stock return in the Kuwait stock exchange. Global Competitiveness, 13(1), 81–91.
Amenta, P., Lucadamo, A., & Marcarelli, G. (2020). On the transitivity and consistency approximated thresholds of some consistency indices for pairwise comparison matrices. Information Sciences, 507, 274-287. doi: https://doi.org/10.1016/j.ins.2019.08.042.
Amenta, P., Ishizaka, A., Lucadamo, A., Marcarelli, G. and Vyas, V. (2019). Computing a common preference vector in a complex multi-actor and multi-group decision system in Analytic Hierarchy Process context, Annals of Operations Research (ANOR), 284, 33–62. doi: https://doi.org/10.1007/s10479-019-03258-3
Amenta, P., Lucadamo, A. and Marcarelli, G. (2018). Approximate thresholds for Salo-Hamalainen index, IFAC-PapersOnLine, 11(11), 1655-1659. doi: https://doi.org/10.1016/j.ifacol.2018.08.219
Ariel, R.A. (1987). A monthly effect in stock returns. Journal of Financial Economics, 18(1), 161–174. doi: https://doi.org/10.1016/0304-405x(87)90066-3
Ariel, R.A. (1990). High stock returns before holidays: existence and evidence on possible causes. The Journal of Finance, 45(5), 1611–1626. doi: https://doi.org/10.1111/j.1540-6261.1990.tb03731.x
Barone, E. (1990). The Italian stock market: efficiency and calendar anomalies. Journal of Banking and Finance, 14(2–3), 483–510. doi: https://doi.org/10.1016/0378-4266(90)90061-6
Cao, X., Premachandra, I. M., Bhabra, G. S., & Pin Tang, Y. (2009). Firm size and the pre-holiday effect in New Zealand. International Research Journal of Finance and Economics.
Chen, H. and Singal, V. (2003). Role of speculative short sales in price formation: the case of the weekend effect. The Journal of Finance, 58(2), 685–706. doi: https://doi.org/10.1111/1540-6261.00541
Crawford, G., Williams, C. (1985). A note on the analysis of subjective judgment matrices. Journal of Mathematical Psychology, 29, 387–405. doi: https://doi.org/10.1016/0022-2496(85)90002-1
Christiano, L.J., Eichenbaum, M. and Evans, C.L. (1996). The effects of monetary policy shocks: evidence from the flow of funds. Review of Economics and Statistics, 78, 16–34. doi: https://doi.org/10.2307/2109845
Dodd, O. and Gakhovich, A. (2011). The holiday effect in Central and Eastern European financial markets. Investment Management and Financial Innovations, 8(4), 29–35.
Expert Choice Software, Expert Choice, Inc. (1994) 4922 Ellsworth Ave., Pittsburgh 15213.
Fama, E.F. (1965). The behavior of stock-market prices. The Journal of Business, 38(1), 34–105.
Forman, E., & Peniwati, K. (1998). Aggregating individual judgements and priorities with the analytic hierarchy process. European Journal of Operational Research, 108, 165–169. doi: https://doi.org/10.1016/s0377-2217(97)00244-0
French, K.R. (1980). Stock returns and the weekend effect. Journal of Financial Economics, 8(1), 55–69.
Gass, S., Rapcsak, T. (2004). Singular value decomposition in AHP. European Journal of Operational Research, 154, 573–584. doi: https://doi.org/10.1016/s0377-2217(02)00755-5
Gibbons, M. and Hess, P. (1981). Day of the week effects and asset returns. Journal of Business, 54, 579–596. doi: https://doi.org/10.1086/296147
Granger, C.W.J., Morgenstern, O. (1970) Predictability of stock market prices. Lexington, MA: Heath Lexington Books.
Grzybowski, A. (2016). New result on inconsistency indices and their relationship with the quality of priority vector estimation. Expert Systems with Applications, 43, 197–212. doi: https://doi.org/10.1016/j.eswa.2015.08.049
Gultekin, M. N. & Gultekin, N. B. (1983). Stock market seasonality. International evidence. Journal of Financial Economics, 12(4), 469-481. doi: https://doi.org/10.1016/0304-405x(83)90044-2
Hensel, C. R. & Ziemba, W. T. (1996). Investment results from exploiting turn-of-the-month effects. (Digest Summary). Journal of Portfolio Management, 22(3), 17-23. doi: https://doi.org/10.3905/jpm.1996.409556
Hogan, K.M., Oolson, G. and Rahmlow, H. (2000). A model for the prediction of corporate bankruptcy using the Analytic Hierarchy Process. Multi-Criteria Applications, 10, 85-102.
Hurson, C. and Zouponidis, C. (1995). On the use of multi-criteria decision aid methods to portfolio selection. Journal of Eruo-Asian Management, 1(2), 69-94.
Huston S.J. (2010). Measuring f literacy. The Journal of Consumer Affairs, 44(2), 296-316.
Jaffe, J. & Westerfield, R. (1985). The weekend effect in common stock returns: the international evidence. Journal of Finance, 40, 237-44.
Jang, J.Y. and Park, M.J. (2019). A study on global investors’ criteria for investment in the local currency bond markets using AHP methods: the case of the Republic of Korea. Risk,s 7(4), 1-20. doi: https://doi.org/10.3390/risks7040101
Khaksari, S., Kamath R. & Grieves, R. (1989). A new approach to determining optimum portfolio mix. The Journal of Portfolio Management, 15(3), 43-49. doi: https://doi.org/10.3905/jpm.1989.409201
Kim, C.W. and Park, J. (1994). Holiday effect and stock returns: further evidence. Journal of Financial and Quantitative Analysis, 29(1), 145–157. doi: https://doi.org/10.2307/2331196
Koczkodaj, W. (1993). A new definition of consistency of pairwise comparisons. Mathematical and Computer Modelling, 18, 79–84. doi: https://doi.org/10.1016/0895-7177(93)90059-8
Kok, K.L. and Wong, Y.C. (2004). Seasonal anomalies of stocks in ASEAN equity markets. Sunway Academic Journal, 1, 1–11.
Kontonikas, A. and Zivile, Z. (2018). Monetary policy and stock valuation: structural VAR identification and size effects. Quantitative Finance, 18, 837–48. doi: https://doi.org/10.1080/14697688.2017.1414516
Krosnick, J.A. (1991). Response strategies for coping with the cognitive demands of attitude measures in surveys. Applied Cognitive Psychology, 5, 213-236. doi: 10.1002/acp.2350050305. doi: https://doi.org/10.1002/acp.2350050305
Lakonishok, J. and Smidt, S. (1988). Are seasonal anomalies real? A ninety-year perspective. Review of Financial Studies, 1(4), 403–425. doi: https://doi.org/10.1093/rfs/1.4.403
Latif, M., Arshad, S., Fatima, M., & Farooq, S. (2011). Market efficiency, market anomalies, causes, evidences, and some behavioral aspects of market anomalies. Research Journal of Finance and Accounting - Institute of Management Sciences, 2(9/10)
Bahauddin Zakaria University, Multan, Pakistan.
Marcarelli, G. (2018) An integrated network model for performance management: a focus on healthcare organizations. International Journal of Managerial and Financial Accounting, 10(2), 163 – 180. doi: https://doi.org/10.1504/ijmfa.2018.10012812
Marrett, G.K. and Worthington, A.C. (2009). An empirical note on the holiday effect in the Australian stock market. Applied Financial Letters, 16, 1769–1772. doi: https://doi.org/10.1080/13504850701675474
Martel, J.M, Khoury, N.T. and Bergeron, M. (1988). An application of a multicriteria approach to portfolio comparisons., Journal of the Operational Research Society, 39(7), 617-628. doi: https://doi.org/10.1057/jors.1988.107
McConnell, J.J. and Xu, W. (2008). Equity returns at the turn of the month. Financial Analysts Journal, 64(2), 49–64. doi: https://doi.org/10.2469/faj.v64.n2.11
Naji, M.A., Mousrij, A., Cillo, V. and Chierici, R. (2019). Measuring the maintenance performance through fuzzy logic and analytical hierarchy process. International Journal of Managerial and Financial Accounting, 11(3/4), 290-319. doi: https://doi.org/10.1504/ijmfa.2019.10025665
Meneu, V. and Pardo, A. (2004). Pre-holiday effect, large trades and small investor behaviour. Journal of Empirical Finance, 11, 231–246. doi: https://doi.org/10.1016/j.jempfin.2003.01.002
Miller, J.A., Atkinson-Palombo, C.M. and Balling, R.C. (2006). Quantifying the ozone ‘weekend effect’ at various locations in Phoenix, Arizona. Atmospheric Environment, 40(39), 7644–7658. doi: https://doi.org/10.1016/j.atmosenv.2006.05.023
Mital, M., Del Giudice, M., and Papa, A. (2018). Comparing supply chain risks for multiple product categories with cognitive mapping and Analytic Hierarchy Process. Technological Forecasting and Social Change, 131, 159-170. doi: https://doi.org/10.1016/j.techfore.2017.05.036
Mylonakis, J. and Tserkezos, D. (2008). The January effect results in the Athens Stock Exchange (ASE). Global Journal of Finance and Banking Issues, 2(2), 44–55.
Pelaez, J., Lamata, M. (2003). A new measure of consistency for positive reciprocal matrices. Computer and Mathematics with Applications, 46, 1839– 1845. doi: https://doi.org/10.1016/s0898-1221(03)90240-9
Pettengill, G.N. (1989). Holiday closings and security returns. The Journal of Financial Research, 12(1), 57–67. doi: https://doi.org/10.1111/j.1475-6803.1989.tb00101.x
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), 57–70. doi: https://doi.org/10.1111/j.1475-6803.1988.tb00066.x
Piccolo, D. (2010). Statistica. Il Mulino.
Rossi, M. (2015). The efficient market hypothesis and calendar anomalies: A literature review. International Journal of Managerial and Financial Accounting, 7(3-4).
Rossi, M. and Fattoruso, G. (2017). The EMH and the market anomalies: an empirical analysis on Italian stock market. International Journal of Managerial and Financial Accounting, 9(3), 222 – 241. doi: https://doi.org/10.1504/ijmfa.2017.086689
Roy, J. K., Kolte, A., Sangvikar, B., & Pawar, A. (2019). Accessing the equity return volatility effect of east and south asian nations: The econometrics modelling method. International Journal of Recent Technology and Engineering, 8(3 Special Issue), 594–603. doi: https://doi.org/10.35940/ijrte.C1120.1083S19.
Rozeff, M. S., & Kinney, W. R. (1976). Capital market seasonality: the case of stock returns. Journal of Financial Economics, 3(4), 379-402. doi: https://doi.org/10.1016/0304-405x(76)90028-3
Saaty, T.L. (1980). The Analytic Hierarchy Process. New York: McGraw-Hill.
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