The January barometer in emerging markets: new evidence from the Gulf Cooperation Council stock exchanges
- Author(s)
-
DOIhttp://dx.doi.org/10.21511/imfi.16(4).2019.06
-
Article InfoVolume 16 2019, Issue #4, pp. 61-71
- Cited by
- 1087 Views
-
140 Downloads
This work is licensed under a
Creative Commons Attribution 4.0 International License
International investors’ interest in the capital markets in the region of Gulf countries has dramatically increased in last two decades. Thus, it would be motivating to investigate their characteristics, where the January anomaly is a major one. This paper studies the veracity of the January effect rule in the Gulf Cooperation Council (GCC) stock markets and examines the predictive power of January returns. Seven GCC stock markets are tested – the market indices in Bahrain, Abu Dhabi, Dubai, Kuwait, Oman, Qatar, and Saudi Arabia – from January 1, 2001 until December 31, 2018, a timeframe which has rarely been analyzed. Ordinary least square (OLS)-based dummy variable regression equation was used as the conventional econometric procedure in the works of financial calendar anomalies in stock markets. Some evidence is reported for the markets of Dubai and Kuwait. The paper also provides an additional explanation for the performance of stock market of Kuwait. The findings are opposite to the well documented evidence that emerging markets are less efficient and hence it is likely that several market anomalies are further pronounced. The results suggest that the predictive power of the January anomaly can be considered as a temporary anomaly in the GCC markets, since it is concentrated in only a couple of GCC markets and does not persist in time.
- Keywords
-
JEL Classification (Paper profile tab)G10, G14, G15
-
References43
-
Tables4
-
Figures1
-
- Figure 1. GCC market performance for the period 2000–2018
-
- Table 1. Descriptive statistics
- Table 2. Monthly returns on closing prices of GCC market indices (2000–2018)
- Table 3. Correlation structure in the GCC stock markets
- Table 4. Estimated parameters
-
- Al-Saad, K. (2004). Seasonality in the Kuwait Stock Exchange. Savings and Development, 28(4), 359-374.
- Aly, H., Mehdian, S., & Perry, M. J. (2004). An analysis of day-of-the-week effects in the Egyptian stock market. International Journal of Business, 9(3), 301-308.
- Arshad, Z., & Coutts, J. A. (1997). Security price anomalies in the London International Stock Exchange: A 60-year perspective. Applied Financial Economics, 7(5), 455-464.
- Ball, R. (1994). The Development, Accomplishments and Limitations of the Theory of Stock Market Efficiency. Managerial Finance, 20(2), 3-48.
- Bley, J., & Chen, K. H. (2006). Gulf Cooperation Council (GCC) stock markets: The dawn of a new era. Global Finance Journal, 17(1), 75-91.
- Bloch, H., & Pupp, R. (1983). The January Barometer revisited and rejected. The Journal of Portfolio Management, 9(2), 48-50.
- Bohl, M. T., & Salm, C. A. (2010). The Other January Effect: International Evidence. European Journal of Finance, 16(2), 173-182.
- Bouman, S., & Jacobsen, B. (2002). The Halloween Indicator, “Sell in May and Go Away”: Another Puzzle. American Economic Review, 92(5), 1618-1635.
- Brown, L. D., & Luo, L. (2006). The January Barometer: Further Evidence. Journal of Investing, 15(1).
- Bulter, K. C., & Malaikah, J. (1992). Efficiency and Inefficiency in Thinly Traded Stock Markets: Kuwait and Saudi Arabia. Journal of Banking and Finance, 16(1), 197-210.
- Chaffai, M., & Medhioub, I. (2018). Herding behavior in Islamic GCC stock market: a daily analysis. International Journal of Islamic and Middle Eastern Finance and Management, 11(2), 182-193.
- Claessens, S., Dooley, M. P., & Warner, A. (1995). Portfolio capital flows: Hot or cold? World Bank Economic Review, 9(1), 153-174.
- Cooper, M. J., Mcconnell, J. J., & Ovtchinnikov, A. V. (2006). The Other January Effect. Journal of Financial Economics, 82(2), 315-341.
- Darrat, A. F., Li, B., & Chung, R. (2013). The Other Month Effect: A Re-Examination of the “Other January” Anomaly. Review of Pacific Basin Financial Markets and Policies, 16(02), 1-23.
- Dodd, O., & Gakhovich, A. (2011). The holiday effect in Central and Eastern European financial markets. Investment Management and Financial Innovations, 8(4), 29-35.
- Ebid, S. (1990). Characteristics and behavior of UAE stock market. Journal of Economic and Administrative Sciences, 6, 19-61.
- Fuller, R. J. (1978). The January Barometer: What’s Its Batting Average. The Journal of Portfolio Management, 4(2), 5-7.
- Harshita, Singh, S., & Yadav, S. S. (2019). Unique calendar effects in the Indian stock market: Evidence and explanations. Journal of Emerging Market Finance, 18(1), 35-58.
- Haug, M., & Hirschey, M. (2006). The January effect. Financial Analysts Journal, 62(5), 78-88.
- Haugen, R. A., & Jorion, P. (1996). The January effect: Still there after all these years. Financial Analysts Journal, 52(1), 27-31.
- Haugen, R. A., & Lakonishok, J. (1988). The incredible January effect: the stock market’s unsolved mystery. Homewood, Illinois: Dow Jones-Irwin.
- Hirsch, Y. (1974). Stock trader’s almanac. The Hirsch Organization, Nyack, NY.
- Hirsch, J., & Hirsch,Y. (2007). Stock trader’s almanac. J. Wiley and Sons.
- Jacobs, B. I., & Levy, K. N. (1988). Calendar Anomalies: Abnormal Returns at Calendar Turning Points. Financial Analysts Journal, 44(6), 28-39.
- Kinney, J. W., & Rozeff, M. S. (1976). Time-Stratified Estimates of Portfolio Betas and Their Effect on the Capital Asset Pricing Model. Journal of Financial Economics, 3(4), 379-402.
- Leontitsis, A., & Siriopoulos, C. (2006a). Calendar Corrected Chaotic Forecast of Financial Time Series. International Journal of Business, 11(4), 367-374.
- Leontitsis, A., & Siriopoulos, C. (2006b). Nonlinear forecast of financial time series through dynamical calendar correction. Applied Financial Economics Letters, 2(5), 337-340.
- Maberly, E. D., & Pierce, R. M. (2004). Stock Market Efficiency Withstands another Challenge: Solving the “Sell in May/Buy after Halloween” Puzzle. Economic Journal Watch, 1(1), 29-46.
- Marshall, & Visaltanachoti, (2010). The Other January Effect: Evidence against market efficiency? Journal of Banking and Finance, 34(10), 2413-2424.
- Mills, T. C., Siriopoulos, C., Markellos, R. N., & Harizanis, D. (2000). Seasonality in the Athens stock exchange. Applied Financial Economics, 10(2), 137-142.
- Nourredine, K. (1998). Behavior of Stock Prices in the Saudi Arabian Financial Market: Empirical Research Findings. Journal of Financial Management and Analysis, 11(1), 48-55.
- Patel, J. B. (2012). A further analysis of small firm stock returns. Managerial Finance, 38(7), 653-659.
- Patel, J. B. (2015). The January Effect Anomaly Reexamined in Stock Returns. Journal of Applied Business Research, 32(1), 317.
- Plastun, A., Sibande, X., Gupta, R., & Wohar, M. E. (2019). Rise and fall of calendar anomalies over a century. The North American Journal of Economics and Finance, 49, 181-205.
- PWC Middle East. (2019). GCC capital markets watch, Q2.
- Ritter, J. R. (1988). The Buying and Selling Behavior of Individual Investors at the Turn of the Year. Journal of Finance, 43(3), 701-719.
- Schwert, G. (2002). Anomalies and market efficiency (NBER Working Paper No. 9277). Cambridge, MA: National bureau of economic research.
- Stivers, C., Sun, L., & Sun, Y. (2009). The other January effect: International, style, and subperiod evidence. Journal of Financial Markets, 12(3), 521-546.
- Wachtel, S. B. (1942). Certain observations on seasonal movements in stock prices. The journal of Business of the University of Chicago, 15(2), 184-193.
- Washer, K. N., Nippani, S., & Johnson, R. (2016). Santa Claus Rally and firm size. Managerial Finance, 42(8), 817-829.
- Zarour, B. (2006). The efficiency of Arab stock markets, its interrelationships and interactions with developed and developing stock markets (Ph.D. Thesis). School of Business, University of Patras.
- Zarour, B. (2007). The Halloween Effect Anomaly: Evidence from the MENA Equity Markets. Studies in Business and Economics, 13(1), 68-76.
- Zarour, B., & Siriopoulos, C. (2008). Transitory and Permanent Volatility Components: The Case of the Middle East Stock Markets. Review of Middle East Economics and Finance, 4(2), 80-92.
-
Semi-monthly effect in stock returns: new evidence from Bombay Stock Exchange
Shakila B. , Prakash Pinto
,
Iqbal Thonse Hawaldar 
doi: http://dx.doi.org/10.21511/imfi.14(3-1).2017.01
Investment Management and Financial Innovations Volume 14, 2017 Issue #3 pp. 160-172 Views: 2634 Downloads: 778 TO CITE АНОТАЦІЯSemi-monthly effect is a kind of calendar anomalies which is less explored in the financial literature. The main objective of this paper to investigate the presence of semi-monthly effect in selected sectoral indices of Bombay Stock Exchange (BSE). The study uses the daily stock returns of five sectoral indices viz S&P BSE Auto Index, S&P BSE Bankex, S&P BSE Consumer Durables Index, S&P BSE FMCG Index and S&P BSE Health Care Index for the period of 10 years starting from 1st April 2007 to 31st March 2017. The data were analyzed using two approaches namely calendar days approach and trading days approach. To test the equality of mean returns for the two halves of the month, Mann-Whitney U test is used. The empirical results of the study did not provide any evidence for the presence of semi-monthly effect in the selected sectoral indices. Nevertheless, BSE Auto Index showed significant difference in the mean returns of first half and second half of trading month during the study period.
-
Bank-specific vs. macro-economic factors: what drives profitability of commercial banks in Saudi Arabia
Farkhanda Shamim ,
Bora Aktan ,
Mohammed Attaitalla Abdulla ,
Nabeel Mohammed Yaseen Sakhi
doi: http://dx.doi.org/10.21511/bbs.13(1).2018.13
Banks and Bank Systems Volume 13, 2018 Issue #1 pp. 139-149 Views: 1653 Downloads: 248 TO CITE АНОТАЦІЯThe goal of this study is to determine the elements that contribute to the profitability of commercial banks in Saudi Arabia. The study is important due to the fact that Saudi vision 2030 foresees Saudi Arabia as a global investment powerhouse and fulfilling this objective requires a profitable banking sector. The method chosen for the study is multiple regression analysis. The sample data is taken for the period ranging 2009 and 2015 for the 12 local banks. The research concludes that bank’s internal factors specifically, bank size, liquidity, credit risk and operational efficiency are significantly determining the profitability in the banks as compared to the economy’s macro-economic variables.
-
Calendar anomalies in the Ukrainian stock market
Guglielmo Maria Caporale , Alex Plastun
doi: http://dx.doi.org/10.21511/imfi.14(1).2017.11
Investment Management and Financial Innovations Volume 14, 2017 Issue #1 pp. 104-114 Views: 1625 Downloads: 400 TO CITE АНОТАЦІЯThis paper is a comprehensive investigation of calendar anomalies in the Ukrainian stock market. It employs various statistical techniques (average analysis, Student’s t-test, ANOVA, the Kruskal-Wallis test, and regression analysis with dummy variables) and a trading simulation approach to test for the presence of the following anomalies: day-of-the-week effect; turn-of-the-month effect; turn-of-the-year effect; month-of-the-year effect; January effect; holiday effect; Halloween effect. The results suggest that in general calendar anomalies are not present in the Ukrainian stock market, but there are a few exceptions, i.e. the turn-of-the-year and Halloween effect for the PFTS index, and the month-of-the-year effect for UX futures. However, the trading simulation analysis shows that only trading strategies based on the turn-of-the-year effect for the PFTS index and the month-of-the-year effect for the UX futures can generate exploitable profit opportunities that can be interpreted as evidence against market efficiency.
