Skip to main content
SpringerLink
Log in

Financial analysis based sectoral portfolio optimization under second order stochastic dominance

  • Published:
Annals of Operations Research Aims and scope Submit manuscript

Abstract

The study proposes to include the financial analysis (FA) in optimal portfolio selection. The role of FA in investment decisions is well recognized. While comparing two stocks on FA of their companies it is important to have both drawn from the same sector of economy. This reason motivated us to propose a sectoral portfolio optimization (SPO) which, instead of looking to optimize among all stocks together, focuses on optimizing stocks within each sector on the basis of FA. These stocks are then pooled together and an optimal portfolio is formed from them with their FA weights and mean returns. In context of FA, the four financial ratios included in present study are return on asset (profitable ratio), debt-assets ratio (solvency ratio), current ratio (liquidity ratio), and price-to-earning ratio (valuation ratio). The risk in a portfolio is quantified using the second order stochastic dominance and to this effect constraints are added in the selection process to generate optimal portfolios for rational risk averse investors. The performance of the optimal portfolios from the proposed model is tested against the portfolios from the traditional second order stochastic dominance model [named (SSDP) in this work], the benchmark index and four 5-star rated mutual funds of India from diversified equity. The out-of-sample analysis is carried on mean returns, Sharpe ratio, Sortino ratio, and also their ability to dominate the benchmark index in almost second order stochastic dominance sense over the tolerable violation regions. The stock price data for the period April 2004 to November 2014 of S&P BSE 500 index is used for testing the models. The optimal portfolios generated from the SPO perform better than the portfolios generated from the (SSDP), the benchmark index and the MFs, indicating effectiveness of FA in SPO framework.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Notes

  1. http://www.bseindia.com/indices/IndicesWatch_sector.aspx?iname=BSE500&index_Code=17.

References

  • Achelis, H. (2000). Technical analysis from A-to-Z. New York: McGraw Hill Professional.

    Google Scholar 

  • Angelelli, E., Mansini, R., & Speranza, M. G. (2008). A comparison of MAD and CVaR models with real features. Journal of Banking and Finance, 32(7), 1188–1197.

    Article  Google Scholar 

  • Austrailian shareholder’s association. Top 15 financial Ratios. http://members.lincolnindicators.com.au/Content/FileStore/Research/top-15-financial-ratios.pdf.

  • Baumann, P., & Trautmann, N. (2013). Portfolio-optimization models for small investors. Mathematical Methods of Operations Research, 77(3), 345–356.

    Article  Google Scholar 

  • Bruni, R., Cesarone, F., Scozzari, A., & Tardella, F. (2012). A new stochastic dominance approach to enhanced index tracking problems. Economics Bulletin, 32(4), 3460–3470.

    Google Scholar 

  • Chan, L., Jegadeesh, N., & Lakonishok, J. (1996). Momentum strategies. Journal of Finance, 51(5), 1681–1713.

    Article  Google Scholar 

  • Cheong, M. P., Sheble, G. B., Berleant, D., Teoh, C. C., Argaud, J. P., & Dancre, M. et al. (2007). Second order stochastic dominance portfolio optimization for an electric energy company. In Power Tech conference 2007 IEEE Lausanne. Paper ID 381, 819–824. doi:10.1109/PCT.2007.4538421.

  • Cooper, M. J., Gutirrez, R. C., & Hameed, A. (2004). Market states and momentum. Journal of Finance, 59(3), 1345–1365.

    Article  Google Scholar 

  • De Bondt Werner, F. M., & Thaler, R. (1985). Does the stock market overreact? Journal of Finance, XL(3), 793–805.

    Article  Google Scholar 

  • Dentcheva, D., & Ruszczynski, A. (2003). Optimization with stochastic dominance constraints. SIAM Journal on Optimization, 14(2), 548–566.

    Article  Google Scholar 

  • Dentcheva, D., & Ruszczynski, A. (2006). Portfolio optimization with stochastic dominance constraints. Journal of Banking and Finance, 30(2), 433–451.

    Article  Google Scholar 

  • Edirisinghe, N. C. P., & Zhang, X. (2007). Generalized DEA model of fundamental analysis and its application to portfolio optimization. Journal of Banking and Finance, 31(11), 3311–3335.

    Article  Google Scholar 

  • Ehrgott, M., Klamroth, K., & Schwehm, C. (2004). An MCDM approach to portfolio optimization. European Journal of Operational Research, 155(3), 752–770.

    Article  Google Scholar 

  • Fabian, C. I., Mitra, G., & Roman, D. (2011). Processing second-order stochastic dominance models using cutting-plane representations. Mathematical Programming, 130, 33–57.

    Article  Google Scholar 

  • Fama, E. F. (1991). Efficient capital markets. Journal of Finance, 46, 1575–1617.

    Article  Google Scholar 

  • Fishburn, P. C. (1977). Mean-risk analysis with risk associated with below-target returns. American Economic Review, 67(2), 116–126.

    Google Scholar 

  • Fridson, M. S., Alvarez, F., & Rubin, M. A. (2008). Financial statement analysis. New York: Wiley.

    Google Scholar 

  • George, T., & Hwang, C. Y. (2004). The 52-week high and momentum investing. Journal of Finance, LIX(5), 2145–2176.

    Article  Google Scholar 

  • Graham, B., & Dodd, D. (1934). Security analysis. New York: Whittlesey House, McGraw-Hill Book Co.

    Google Scholar 

  • Graham, B. (1949). The intelligent investor. New York: Harper & Bothers.

    Google Scholar 

  • Greenblatt, J. (2005). The little book that still beats the market. Hoboken: Wiley and Sons.

    Google Scholar 

  • Greig, A. C. (1992). Fundamental analysis and subsequent stock returns. Journal of Accounting and Economics, 15(2–3), 413–442.

    Article  Google Scholar 

  • Guerard, J. B., Takano, M, Jr, & Yamane, Y. (1993). The development of efficient portfolios in Japan with particular emphasis on sales and earnings forecasting. Annals of Operations Research, 45, 91–108.

    Article  Google Scholar 

  • Hadar, J., & Russell, W. (1969). Rules for ordering uncertain prospects. The American Economic Review, 59(1), 25–34.

    Google Scholar 

  • Harvey, C., Liechty, R. J., Liechty, M. W., & Mueller, P. (2003). Portfolio selection with higher moments. Working Paper, Duke University. http://ssrn.com/abstract=634141.

  • Holthausen, R. W., & Larcker, D. F. (1992). The prediction of stock returns using financial statement information. Journal of Accounting and Economics, 15(2–3), 373–411.

    Article  Google Scholar 

  • Hurson, C., & Zopounidis, C. (1995). On the use of multicriteria decision aid methods to portfolio selection. Journal of Euro-Asian Management, 1(2), 69–94.

    Google Scholar 

  • Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. Journal of Finance, 48(1), 65–91.

    Article  Google Scholar 

  • Konno, H., Shirakawa, H., & Yamazaki, H. (1993). A mean-absolute deviation-skewness portfolio optimisation model. Annals of Operations Research, 45, 205–220.

    Article  Google Scholar 

  • Konno, H., & Suzuki, K. (1995). A mean-variance-skewness portfolio optimization model. Journal of Operational Research Society of Japan, 38, 173–187.

    Article  Google Scholar 

  • Konno, H., & Yamazaki, H. (1991). Mean-absolute deviation portfolio optimization model and its application to Tokyo stock market. Management Science, 37(5), 519–531.

    Article  Google Scholar 

  • Kroll, Y., & Levy, H. (1980). Stochastic dominance: A review and some new evidence. Research in Finance, 2, 163–227.

    Google Scholar 

  • Leshno, M., & Levy, H. (2002). Preferred by all and preferred by most decision makers: Almost stochastic domi-nance. Management Science, 48(8), 1074–1085.

    Article  Google Scholar 

  • Levy, H. (1992). Stochastic dominance and expected utility: Survey and analysis. Management Science, 38, 555–593.

    Article  Google Scholar 

  • Levy, M. (2012). Almost stochastic dominance and efficient investment sets. American Journal of Operations Research, 2, 313–321.

    Article  Google Scholar 

  • Mansini, R., Ogryczak, W., & Speranza, M. G. (2007). Conditional value at risk and related linear programming models for portfolio optimization. Annals of Operations research, 152(1), 227–256.

    Article  Google Scholar 

  • Marler, R. T., & Arora, J. S. (2010). The weighted sum method for multi-objective optimization: New insights. Structural and Multidisciplinary Optimization, 41, 853–862.

    Article  Google Scholar 

  • Markowitz, H. M. (1952). Portfolio selection. Journal of Finance, 7, 77–91.

    Google Scholar 

  • Marshell, A. W., & Olkin, I. (1979). Inequalities: Theory of majorization and its applications. San Diego: Academic Press.

    Google Scholar 

  • Moskowitz, T. J., & Grinblatt, M. (1999). Do industries explain momentum? Journal of Finance, 54(4), 1249–1290.

    Article  Google Scholar 

  • Murphy, J. (1999). Technical analysis of the financial markets: A comprehensive guide 827 to trading methods and applications. New York: Prentice Hall Press.

    Google Scholar 

  • Neumann, J., & Morgenstern, O. (2001). Theory of games and economic behaviour. Princeton, New Jersy: Princeton University Press.

    Google Scholar 

  • Nie, Y., Wu, X., & Homem-de-Mello, T. (2012). Optimal path problems with second-order stochastic dominance constraints. Networks and Spatial Economics, 12, 561–587.

    Article  Google Scholar 

  • Ogryczak, W., & Ruszczynski, A. (1999). From stochastic dominance to mean- risk models: Semideviations as risk measures. European Journal of Operational Research, 116, 33–50.

    Article  Google Scholar 

  • Quirk, J. P., & Saposnik, R. (1962). Admissibility and measurable utility functions. Review of Economic Studies, 29, 140–146.

    Article  Google Scholar 

  • Rockafeller, R. T., & Uryasev, S. (2000). Optimization of conditional value-at-risk. Jounal of Risk, 2, 2142.

    Google Scholar 

  • Roman, D., Darby, D. K., & Mitra, G. (2006). Portfolio construction based on stochastic dominance and target return distributions. Mathematical Programming, 108, 541–569.

    Article  Google Scholar 

  • Roman, D., Darby, D. K., & Mitra, G. (2007). Mean-risk models using two risk measures: A multi-objective approach. Quantitative Finance, 7(4), 443–458.

    Article  Google Scholar 

  • Roman, D., & Mitra, G. (2008). Portfolio selection models: A review and new directions. Available from: http://bura.brunel.ac.uk/bitstream/2438/3879/1/Fulltext?origin=publication_detail.

  • Roman, D., Mitra, G., & Zverovich, V. (2013). Enhanced indexation based on second-order stochastic dominance. European Journal of Operational Research, 228, 273–281.

    Article  Google Scholar 

  • Samaras, G. D., Matsatsinis, N. F., & Zopounidis, C. (2008). A multi criterion DSS for stock evaluation using fundamental analysis. European Journal of Operational Research, 187(3), 1380–1401.

    Article  Google Scholar 

  • Seng-cho, T. C., Hsu, H., Yang, C., & Laid, F. (1997). A stock selection DSS combining AI and technical analysis. Annals of Operations Research, 75, 335–353.

    Article  Google Scholar 

  • Sharma, A., & Mehra, A. (2013). Portfolio selection with a minimax measure in safety constraint. Optimization, 62(11), 1473–1500.

    Article  Google Scholar 

  • Sharma, A., & Mehra, A. (2014). How smart is the strategy of investing in 52-week high hitting stocks with past positive net profit in Indian market? International Journal of Behavioural Accounting and Finance, 4(4), 325–337.

    Article  Google Scholar 

  • Sharpe, W. F. (1994). The Sharpe ratio. Journal of Portfolio Management, 21(1), 49–58.

    Article  Google Scholar 

  • Silva, A., Neves, R., & Horta, N. (2014). A hybrid approach to portfolio composition based on fundamental and technical indicators. Expert Systems with Applications, 42(4), 2036–2048.

    Article  Google Scholar 

  • Sortino, F. A., & Price, L. N. (1994). Performance measurement in a downside risk framework. Journal of Investing, 3(3), 59–64.

    Article  Google Scholar 

  • Steuer, R. E., & Na, P. (2003). Multiple criteria decision making combined with finance: A categorized bibliography. European Journal of Operational Research, 150(3), 496–515.

    Article  Google Scholar 

  • Steuer, R. E., Qi, Y., & Hirschberger, M. (2005). Multiple objectives in portfolio selection. Journal of Financial Decision Making, 1(1), 11–26.

    Google Scholar 

  • Whitmore, G. A. (1970). Third-degree stochastic dominance. The American Economic Review, 60, 457–459.

    Google Scholar 

  • Xidonas, P., Mavrotas, G., & Psarrasa, J. (2009). A multi criteria methodology for equity selection using financial analysis. Computers and Operations Research, 36, 3187–3203.

    Article  Google Scholar 

  • Xidonas, P., Mavrotas, G., & Psarras, J. (2010). Equity portfolio construction and selection using multiobjective mathematical programming. Journal of Global Optimization, 47, 185–209.

    Article  Google Scholar 

  • Yu, J. R., & Lee, W. Y. (2011). Portfolio rebalancing model with multiple criteria. European Journal of Operational Research, 209, 166–175.

    Article  Google Scholar 

  • Young, M. R. (1998). A minimax portfolio selection rule with linear programming solution. Management Science, 44, 673–683.

    Article  Google Scholar 

  • Yux, M., Inouez, H., & Shi, J. (2006). Portfolio optimization problems with linear programming models. http://www.ccfr.org.cn/cicf2006/cicf2006paper/20060111083050.

  • Zhao, S., Lu, Q., Han, L., Liu, Y., & Hu, F. (2015). A mean-CVaR-skewness portfolio optimization model based on asymmetric laplace distribution. Annals of Operations Research, 226(1), 727–739.

    Article  Google Scholar 

  • Zopounidis, C., & Doumpos, M. (2002). Multicriteria decision aid in financial decision making: Methodologies and literature review. Journal of Multi-criteria Decision Analysis, 11, 167–186.

    Article  Google Scholar 

Download references

Acknowledgments

The first author is thankful to the Council of Scientific and Industrial Research (CSIR), India, for financial support. The authors are indebted to the referees for their valuable suggestions.

Author information

Authors and Affiliations

  1. Department of Mathematics, Indian Institute of Technology Delhi, Hauz Khas, 10016, New Delhi, India

    Amita Sharma & Aparna Mehra

Authors
  1. Amita Sharma
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Aparna Mehra
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Amita Sharma.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sharma, A., Mehra, A. Financial analysis based sectoral portfolio optimization under second order stochastic dominance. Ann Oper Res 256, 171–197 (2017). https://doi.org/10.1007/s10479-015-2095-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10479-015-2095-y

Keywords

Search

Navigation