Forecasting the value effect of Seasoned Equity Offering announcements: Evidence from BRICS and comparative analysis to USA and European Markets

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Published: Jan 27, 2017
DOI: https://doi.org/10.5750/jpm.v10i2.1240
Keywords:
SEO BRICS Value effect Neural Networks Abnormal return

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Zhuqing Huang
Kostantinos Nikolopoulos

Abstract

Purpose –The purpose of this paper is to forecast the value effect of the SEO announcements based on the BRICS stock markets, and to make comparisons with the US and European markets.Design/methodology/approach –China and Russia are picked as representations of the BRICS based on the analysis of the economic growth of the five countries. Historical data from Shanghai Stock Exchange (SSE) and Moscow Stock Exchange (MSE) between 2010 and 2014 were involved. The authors use the abnormal return to quantify the value effect of SEOs and different models were built with the chosen factors. Modelling tools include EViews and SAS, and comparisons were made among the models.Findings –Positive market reactions were observed within two and three days after the SEOs in SSE and MSE respectively, negative market reactions exist in a long-run period after the announcements. The best model for the prediction is the auto-neural model.Research limitations/implications – The sample size could be larger in order to raise the precision of the prediction.Originality/value – Many empirical studies of the SEOs are based on developed markets. However the emerging markets may react differently. This research focuses on the stock markets in BRICS, which could be seen as representations of the emerging markets, thus could provide ideas and clues for relevant stakeholders in emerging markets before the SEO announcements.Keywords SEO, BRICS, Value effect, Neural Networks, SSE, MSEPaper type Research paper

Article Details

Issue
Vol. 10 No. 2 (2016)
Section
Articles

References

Anderson, D.R., Sweeney, D.J., Williams, T. A., Freeman, J., Shoesmith, E., 2014. Statistics for Business and Economics. 3rd ed. UK: Cengage Learning.

Anon., 1995. A neural network approach to stock market holding period returns. American Business Review, 13(2), pp. 61-64.

Asquith, P., Mullins, D.W., 1986. Equity issues and offering dilution. Journal of Financial Economics 15 (1–2), pp. 61–89.

Bayless, M. and Jay, N.R., 2013. What motivates seasoned equity offerings?. Managerial Finance, 39(3), pp. 251-271.

Bohren, O., Eckbo, B.E., Michalsen, D., 1997. Why underwrite rights offerings? Some new evidence. Journal of Financial Economics 46 (2), 223–261.

Bozos, K., Duxbury, D. 2008. The price and volume effects of seasoned equity offers: Evidence from the athens exchange. In: European Financial Management Association 17th Annual Meeting: <http://www.efmaefm.org>.

Brocklebank, John; Held, Gerhard;, 1997. Data Mining with The SAS System. [Online] Available at: http://www.sascommunity.org/seugi/SEUGI1997/BROCKLEB_DATAMIN.PDF [Accessed 29 August 2015].

Cai, K., 2013. Stock Price Reactions And Long Run. The Journal of Applied Business Research Performance of Rule 144A Equity Issuance, 29(6), pp. 1615-1622

Chaudhuri, A., De, K. and Chatterjee, D., 2013. Discovering stock price prediction rules of Bombay stock exchange using rough fuzzy multi-layer perception networks

Corby, C.E., Stohs, M.H., 1998. Investment opportunities and Irish equity offerings. The European Journal of Finance 4 (4), 357–367.

Dutta, A., Bandopadhyay, G., and Sengupta, S., 2012. Prediction of Stock Performance in the India Stock Market Using Logistic Regression. International Journal of Business and Information, 7(1), pp. 105-136.

Eckbo, B.E.; Masulis, R.W., 1995. Seasoned Equity Offerings: A Survey. In: Handbooks in OR & MS. s.l.:Elsevier Science B.V., pp. 1017-1071.

Fama, E.F., 1970. Efficient capital markets: A review of theory and empirical work. The Journal of Finance 25 (2), 383–417.

Fama, E.F., French, K.R., 1988. Dividend yields and expected stock returns.

Gao, M., 2014. Researching for Co-movement between China Stock Market and World Stock Markets. Ph.D. China Agricultural University. (A Chinese reference)

Han, D., Ma, L. and Yu, C., 2008. Financial Prediction: Application of Logistic Regression with Factor Analysis. Dalian, IEEE

Holzinger, K.J., and Harman, H.H., 1939. Factor analysis. Review of educational Research, Methods of Research in Education, 9 (5),528-531.

IMF, World Economic Outlook, April, 2015, http://www.imf.org.

Jung, Kooyul, Kim, Y.C., and Stulz. R.M., 1996. Timing, investment opportunities, managerial discretion and the security issue decision. Journal of Financial Economics. 42, 159-185.

Kalay and Shimrat, 1987. Firm value and seasoned equity issues: Price pressure, wealth redistribution, or negative information. Journal of Financial Economics, vol.19, 109-126.

Kohzadi, N.; Boyd, M.S.; Kermanshahi, B.; Kaastra, I.;, 1996. A comparison of artificial neural network and time series models for forecasting commodity prices. Neuralcomputing, Volume 10, pp. 169-181.

Masulis, R.W. and Korwar, A.N., 1986. Seasoned equity offerings: An empirical investigation. Journal of Financial Economics, vol.15, 91-118

McLean, R.D., Pontiff, J., and Watanabe, A., 2009. Share issuance and cross-sectional returns: International evidence. Journal of Financial Economics 94, 1-17.

Mensi, W., Hammoudeh, S., Reboredo, J.C., Nguyen, D.K., 2014. Do global factors impact BRICS stock markets? A quantile regression approach. Emerging Markets Review, 19 (2014), 1–17.

Mikkelson, W.H. and Partch, M.P., 1986. Valuation effects of security offerings and the issuance process. Journal of Financial Economics, Vol.15, 31-61

Myers, S.C., and Majluf, N.S., 1984. Corporate financing an investment decisions when firms have information that investors do not have. Journal of Financial Economics, 13(2), 187-221.

O’Neill, J.,2001. Building Better Global Economic BRICs. Global Economics, paper No. 66: < http://www.goldmansachs.com/our-thinking/archive/building-better.html>

Pascal, Quiry; Maurizio, Dallocchio; Yann, Fur Le; Antonio, Salvi;, 2009. Corperate Finance. 2nd ed. s.l.:Wiley.

Rahman, M. and Mustafa, M., 2014. Dynamic influences of exchange rate and M2 on Russia’s stock market. Indian Journal of Economics & Business, Vol. 13, No. 3, 405-418.

Richard A. Brealey; Stewart C. Myers; Franklin Allen; 2011. Principles of Corporate Finance. 10th ed. McGraw Hill.

Solomon, H. and Rosner, B., 1954. Factor Analysis. Review of Educational Research, Statistical Methodology in Educational Research 24 (5), 421-438.

Wong, W.K., Xia, M., and Chu, W.C., 2010. Adaptive neural network model for time-series forecasting. European Journal of Operational Research 207 (2), 807-816.

Zhang, G.P., Qi, M., 2005. Neural network forecasting for seasonal and trend time series. European Journal of Operational Research 160 (2), 501–514.