Abstract
In this article we investigate the problem of detection of the statistically significant dependences of stock trading return, which occur in particular days of the month and which could be important for creating profitable investment strategies. This problem is formulated as two hypotheses, stating that the stock trading return of the last five days of the month is greater than the average total monthly return, and the return generated over the first half of the month is significantly larger than that of the second half. By using the advanced methods of statistical analysis we researched the indications of these calendar effects for 24 stocks of the Vilnius stock exchange. The investigation did not fully confirm any of the hypotheses, but found out strong relation of risk level to the researched periods of the month. We explored the dependency of this effect to the volatility and volume of the traded stocks. The research results revealed that stocks of small and moderate volume have high volatility on the last days of the month, and the stocks of high volume have high volatility on the first part of month.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Achelis, S.B.: Technical Analysis from A to Z, 2nd edn. McGraw-Hill, New York (2000)
Thomsett Michael, C.: Getting started in fundamental analysis, p. 232. Wiley, Chichester (2006)
Sakalauskas, V., Kriksciuniene, D.: Statistical investigation on the day-of-week effect in emerging stock markets. In: Artificial intelligence and applications: proceedings of the international conference, Innsbruck, Austria, February 11-13, pp. 146–151 (2008) ISBN 978-88986-709-3
Sakalauskas, V., Kriksciuniene, D.: Neural networks approach to the detection of weekly seasonality in stock trading. In: Fyfe, C., Kim, D., Lee, S.-Y., Yin, H. (eds.) IDEAL 2008. LNCS, vol. 5326, pp. 444–451. Springer, Heidelberg (2008)
Sullivan, R., Timmermann, A., White, H.: Dangers of Data-Driven Inference: The Case of Calendar Effects in Stock Returns, Working Paper, University of California, San Diego (1998)
Balaban, E., Bayar, A., Kan, O.B.: Stock returns, seasonality and asymmetric conditional volatility in World Equity Markets. Applied Economics Letters 8, 263–268 (2001)
Flannery, M.J., Protopapadakis, A.A.: From T-bills to common stocks: investigating the generality of intra-week return seasonality. Journal of Finance 43, 431–450 (1988)
Brooks, C., Persand, G.: Seasonality in Southeast Asian stock markets: some new evidence on day-of-the-week effects. Applied Economics Letters 8, 155–158 (2001)
Tang, G.Y.N.: Day-of-the-week effect on skewness and kurtosis: a direct test and portfolio effect. The European Journal of Finance 2, 333–351 (1998)
Sakalauskas, V., Kriksciuniene, D.: The Impact of Taxes on Intra-Week Stock Return Seasonality. In: Bubak, M., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds.) ICCS 2008, Part II. LNCS, vol. 5102, pp. 504–513. Springer, Heidelberg (2008)
Kamath, R., Chusanachoti, J.: An investigation of the day-of-the-week effect in Korea: has the anomalous effect vanished in the 1990s? International Journal of Business 7, 47–62 (2002)
Reschenhofer, E.: Unexpected Features of Financial Time Series: Higher-Order Anomalies and Predictability. Journal of Data Science 2(2004), 1–15 (2004)
Basher, S.A., Sadorsky, P.: Day-of-the-week effects in emerging stock markets. Applied Economics Letters 13, 621–628 (2006)
Thaler, R.: The effect. Journal of Economic Perspectives (1), 197–201 (1987a)
Thaler, R.: Seasonal movements in security prices II: weekend, holiday, turn of the month, and intraday effects. Journal of Economic Perspectives (1) (2), 169–177 (1987b)
Mills, T.C., Coutts, J.A.: Anomalies and calendar affects in the new FT-SE indices. European Journal of Finance (1), 79–93 (1995)
Sullivan, R., Timmermann, A., White, H.: Dangers of data mining: the case of calendar effects in stock returns. Journal of Econometrics (105), 249–286 (2001)
Kohers, G., Kohers, N., Pandey, V., Kohers, T.: The disappearing day-of-the-week effect in the world’s largest equity markets. Applied Economics Letters 11, 167–171 (2004)
Steeley, J.M.: A note on information seasonality and the disappearance of the weekend effect in the UK stock market. Journal of Banking and Finance 25, 1941–1956 (2001)
Brooks, C., Persand, G.: Seasonality in Southeast Asian stock markets: some new evidence on the day-of-the-week effects. Applied Economics Letters 8, 155–158 (2001)
Aggarwal, R., Rivoli, P.: Seasonal and day-of-the-week effects in four emerging stock markets. Financial Rev. 24, 541–550 (1989)
NASDAQ OMX Group (2009), http://www.nasdaqomxbaltic.com/
StatSoft Inc. Electronic Statistics Textbook. StatSoft, Tulsa (2006), http://www.statsoft.com/textbook/stathome.html
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Sakalauskas, V., Kriksciuniene, D. (2009). Research of the Calendar Effects in Stock Returns. In: Abramowicz, W., Flejter, D. (eds) Business Information Systems Workshops. BIS 2009. Lecture Notes in Business Information Processing, vol 37. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03424-4_9
Download citation
DOI: https://doi.org/10.1007/978-3-642-03424-4_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-03423-7
Online ISBN: 978-3-642-03424-4
eBook Packages: Computer ScienceComputer Science (R0)