Nothing Special   »   [go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

Global portfolio construction with emphasis on conflicting corporate strategies to maximize stockholder wealth

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

Abstract

This study addresses stock selection modeling and portfolio construction and implementation in global and U.S. markets in the context of multi-objectives optimization framework. We will show how forecasted earnings acceleration factors can enhance returns in global and U.S. stock markets. We construct Markowitz portfolios for Global and U.S. domestic Markets that offer superior returns-to-risk ratios, relative to domestic portfolios. We show how stock repurchases and corporate exports can be estimated and implemented as the third objective to generate statistically significant excess returns in global and U.S. stock markets. It is particularly interesting to note the conflicting corporate strategies’ impacts on stockholder wealth.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Notes

  1. We refer the reader to the literature reviews of the low price-earnings multiple and other financial anomalies found in Nerlove (1968), Dimson (1988), Bloch et al. (1993), Levy (1999), Haugen (1999), Haugen and Baker (1996, 2010) and Guerard Jr. et al. (2015).

  2. Guerard Jr. et al. (2015) documented the stock selection effectiveness of CTEF, which accounts for up to 90 percent of the stock selection in the United States Expected Returns Model (USER) and the Global Expected Returns Model (GLER).

  3. Lakonishok and Vermalen reported premiums of 21.79, 24.09, and 18.54% on tender offers during the 1962–1986, 1962–1979, and 1980–1986 periods, respectively. They also reported cumulative abnormal returns of 12.54, 14.58, and 9.78% to non-tendering stockholders during the corresponding periods. Smaller firms produced the highest abnormal returns.

  4. A forecast of dividend levels can be obtained by studying past payout rates and attempting to predict future earnings levels. The amount left after common dividends are paid represents retained earnings or earnings reinvested in the firm. Firms target a target debt ratio by choosing between debt and equity repurchases rather than choosing between debt and equity issuances, see Bierman (2001). Repurchases and dividends are motivated by contracting future investment opportunities, see Bierman (2010).

  5. The corporate exports variable consolidates the dividend, net stock and debt buybacks and net stock and bond issues, as opposed to use traditional goal programming, minimizing the deviations from desired targeted levels, see Lee (1972), Guerard and Lawrence (1984), Bravo et al. (2010), and Caballero et al. (2006).

  6. An analysis of the ES components reveals that interest paid has risen faster than dividends paid during the 1971–2011 time period. Net debt issues have risen at an undiminished rate, with the notable exception of 2001–2005 and 2009. Stock repurchases rose substantially following the crash of October 1987. Net equity repurchases increased substantially in the 2002–2006 time period, and fell dramatically with the financial crisis. To illustrate the corporate fund generation process, Guerard [2010] showed the ten largest and smallest corporate exporter firms in 1983; the largest corporate exports firms that included AT&T, IBM, and several of the large oil companies dominated positive corporate exports in 1983 as they paid large dividends and interest and generally re-purchased more debt than was issued (which made a great deal of sense given the level of interest rates in 1983). A similar process occurred in 2006 as Microsoft, Pfizer, and the oil companies dominated the largest corporate exporting firm (IBM fell to only the 24th largest exporter in 2006). Dividends paid exceeded equity repurchased of the Compustat firms from 1971–2011, although equity repurchases have risen relatively to dividends since 1982. We examine the 1971–2011 period because Compustat does not maintain debt and equity issuance, and repurchases, prior to 1971.

  7. The global corporate sector is a net (zero) exporter porter of funds for 1997–2015. Dividends and interest paid are less than net common stock issuances plus net debt issuances. Common stock repurchases and debt repurchases occur less frequently with non-U.S. markets than with U.S. stocks.

  8. The estimation of factors, or betas, can be accomplished using firm fundamental data, as in the Rosenberg (1974), Rosenberg and Marathe (1979), and Menchero et al. (2010), or principal component analysis of historical stock returns, as in Blin et al. (1997), or Saxena and Stubbs (2012), or Guerard Jr. et al. (2014). The reader is referred to complete and excellent surveys of multi-factor models found in Rudd and Clasing (1982), Farrell Jr (1997), Grinold and Kahn (1999), Haugen (2001), Menchero et al. (2010), and Conner et al. (2010).

  9. Markowitz reminds researchers that Chapter 9 of his seminal Portfolio Selection (1959) introduced the semi-variance to portfolio construction.

  10. ITG estimate our transactions costs to be about 60 basis points, each-way, for 2011–2015.

  11. The first level is the information coefficient, IC, of a strategy in which the subsequent ranked returns are regressed as a function of the ranked financial strategy. The regression coefficient is the IC which is a randomly distributed variable to test the statistical significant of the individual variable or composite model strategies. The second level of investment testing is to estimate, with transactions costs, the Markowitz efficient frontier, by varying either the lambda or the targeted tracking error. The third level of testing is to apply the Markowitz and Xu (1994) Data Mining Corrections, DMC, to test whether the strategy is statistically different from any model that could have been used. Moreover, the regression coefficient of the DMC test indicates how much excess returns could be continued into the future.

  12. We tested an additional global stock universe initially containing approximately 16,000 securities in October 2014 covered by I\(\backslash \)B\(\backslash \)E\(\backslash \)S forecasters. We restrict ourselves to stocks covered by two I\(\backslash \)B\(\backslash \)E\(\backslash \)S, some 12,000 stocks in December 2014. We further restrict our universe to the largest 7500 market-capitalized global stocks because of liquidity issues. In the global 7500 stock universe, we tested an ES constraint as well as a common stock buyback, CSR constraint and a dividends-only, DIV, constraint. We found, for the December 2002–December 2014 time period, that the corporate exports constraint, using 70 as the portfolio characteristic, dominated the common stock buyback (or repurchase) and dividend-only constraints. See Fig. 7 for the CTEF tilt with ES constraint Barra attribution analysis. We find that global buybacks enhance returns. See Table 2. We ran an analysis of U.S. common stock buybacks and found that active returns increased, relative to CTEF, by 150 basis points; whereas the ES constraint increased returns by over 250 basis points, counter to the Fu and Huang (2016) U.S. result. It is interesting that corporate exports enhance global active returns particularly when corporate exports are positive in the U.S. and negative $ in non-U.S. stocks. Repurchasing stock and debt, and patying dividends, helps in global portfolio management, as it does in with U.S. stocks. In terms of portfolio active returns, corporate exports enhance portfolio returns globally on a relative basis.

References

  • Bierman, H. (2001). Increasing shareholder value. New York: Springer.

    Book  Google Scholar 

  • Bierman, H. (2010). My favorite two corporate finance puzzles. In R. J. Aronson, H. L. Parmet, & R. J. Thornton (Eds.), Variations in economic analysis: Essays in honor of Eli Schwartz. New York: Springer.

    Google Scholar 

  • Blin, J. M., Bender, S., & Guerard, J. B., Jr. (1997). Earnings forecasts, revisions and momentum in the estimation of efficient market-neutral Japanese and U.S. Portfolios. In A. Chen (Ed.), Research in finance (Vol. 15, pp. 93–114).

  • Bloch, M., Guerard, J. B., Jr., Markowitz, H. M., Todd, P., & Xu, G. (1993). A comparison of some aspects of the U.S. and Japanese equity markets. Japan & the World Economy, 5, 3–26.

  • Bravo, M., Pla-Santamaria, D., & Garcia-Bernabeu, A. (2010). Portfolio selection from multiple benchmarks: A goal programming to an actual case. Journal of Multi-Criteria Decision Analysis, 17, 155–166.

    Article  Google Scholar 

  • Brealey, R., Myers, S. C., & Allen, F. (2005). Principles of corporate finance. New York: McGraw-Hill/ Irwin.

    Google Scholar 

  • Bruce, B., & Epstein, C. B. (1994). The handbook of corporate earnings analysis. Chicago: Probus Publishing Company.

    Google Scholar 

  • Caballero, R. F., Ruiz, M. U., & Romero, C. (2006). Interactive meta-goal programming. European Journal of Operational Research, 175(2006), 135–154.

    Article  Google Scholar 

  • Conner, G., Goldberg, L., & Korajczyk, R. A. (2010). Portfolio risk analysis. Princeton: Princeton University Press.

    Book  Google Scholar 

  • Dann, L. (1981). Common stock repurchases: An analysis of returns to bondholders and stockholders. Journal of Financial Economics, 9, 115–138.

    Article  Google Scholar 

  • Deutsche Bank Market Research. (2014). The curb appeal of stock buybacks. Quantitative Strategy: The Quant View, 3.

  • Dhrymes, P. J., & Kurz, M. (1967). Investment, dividends, and external finance behavior of firms. In R. Ferber (Ed.), Determinants of investment behavior. New York: Columbia University Press.

    Google Scholar 

  • Dimson, E. (1988). Stock market anomalies. Cambridge: Cambridge University Press.

    Google Scholar 

  • Elton, E. J., Gruber, M. J., & Gültekin, M. N. (1981). Expectations and share prices. Management Science, 27, 975–987.

    Article  Google Scholar 

  • Fama, E. F., & Babiak, H. (1968). Dividend policy: An empirical analysis. Journal of the American Statistical Association, 63, 1132–1161.

    Article  Google Scholar 

  • Fama, E. F., & French, K. R. (1992). Cross-sectional variation in expected stock returns. Journal of Finance, 47(2), 427–465.

    Article  Google Scholar 

  • Fama, E. F., & French, K. R. (1995). Size and the book-to-market factors in earnings and returns. Journal of Finance, 50(1), 131–155.

    Article  Google Scholar 

  • Fama, E. F., & French, K. R. (2008). Dissecting anomalies. Journal of Finance, 63(4), 1653–1678.

    Article  Google Scholar 

  • Farrell, J. L., Jr. (1997). Portfolio management: Theory and applications. New York: McGraw-Hill/ Irwin.

  • Fu, F., & Huang, S. (2016). The persistence of long-run abnormal returns following stock repurchases and offerings. Management Science, 62, 964–984.

    Article  Google Scholar 

  • Graham, B., & Dodd, D. (1934). Security analysis: Principles and technique. New York: McGraw-Hill Book Company.

    Google Scholar 

  • Grinold, R., & Kahn, R. (1999). Active portfolio management. New York: McGraw-Hill/ Irwin.

    Google Scholar 

  • Guerard, J. B., Jr. (1997). Is there a cost to being socially responsible in investing? Journal of Forecasting, 16, 475–490.

  • Guerard, J. B., Jr. (2012). Global earnings forecast efficiency. Research in Finance, 28, 19–47.

  • Guerard, J. B., Jr., Bean, A. S., & Andrews, S. (1987). R&D Management and corporate financial policy. Management Science, 33, 1419–1427.

  • Guerard, J. B., Jr., Gultekin, M., & Stone, B. K. (1997). The role of fundamental data and analysts’ earnings breadth, forecasts, and revisions in the creation of efficient portfolios. In A. Chen (Ed.), Research in finance (Vol. 15, pp. 69–92).

  • Guerard, J. B., Jr., & Lawrence, K. D. (1984). Strategic planning and the problem of capital budgetibng in a steel firm: A multi-criteria approach. In T. Naylor & C. Thomas (Eds.), Optimization models for strategic planning. New York: North-Holland.

  • Guerard, J. B., Jr., Markowitz, H. M., & Xu, G. (2014). The role of effective corporate decisions in the creation of efficient portfolios. IBM Journal of Research and Development, 58(6), 11.

  • Guerard, J. B., Jr., Markowitz, H. M., & Xu, G. (2015). Earnings forecasting in a global stock selection model and efficient portfolio construction and management. International Journal of Forecasting, 31, 550–560.

  • Guerard, J. B., Jr., Rachev, R. T., & Shao, B. (2013). Efficient global portfolios: Big data and investment universes. IBM Journal of Research and Development, 57(5), 11.

  • Guerard, J. B., Jr., & Schwartz, E. (2007). Quantitative corporate finance. New York: Springer.

  • Guerard, J. B., Jr., Takano, M., & Yamane, Y. (1993). The development of efficient portfolios in Japan with particular emphasis on sales and earnings forecasting. In H. Konno, D. G. Luenberger, & J. M. Mulvey (Eds.), Financial engineering, Annals of Operations Research (Vol. 45, pp. 91–108).

  • Haugen, R. A. (1999). The inefficient stock market. Upper Saddle River, NJ: Prentice Hall.

    Google Scholar 

  • Haugen, R. A. (2001). Modern investment theory (5th ed.). Upper Saddle River, NJ: Prentice Hall.

    Google Scholar 

  • Haugen, R. A., & Baker, N. (1996). Communality in the determinants of expected results. Journal of Financial Economics, 41, 401–440.

    Article  Google Scholar 

  • Haugen, R., & Baker, N. (2010). Case closed. In J. B. Guerard (Ed.), The handbook of portfolio construction: Contemporary applications of Markowitz techniques. New York: Springer.

    Google Scholar 

  • Hawkins, E. H., Chamberlain, S. C., & Daniel, W. E. (1984). Earnings expectations and security prices. Financial Analysts Journal, 40(5), 24–38.

    Article  Google Scholar 

  • Hirschberger, M., Steuer, R. E., Utz, S., Wimmer, M., & Qi, Y. (2013). Computing the nondominated surface in tri-criterion portfolio selection. Operations Research, 61(1), 169–183.

    Article  Google Scholar 

  • Kijima, M. & Ohnishi, M. (1993). Mean-risk analysis of risk aversion and wealth effects on optimal portfolios with multiple investment opportunities. In H. Konno, D. G. Luenberger, & J. M. Mulvey (Eds.), Financial engineering, Annals of Operations Research (Vol. 45, pp. 147–163).

  • King, A. J. (1993). Asymmetric risk measures and tracking models for portfolio optimization under uncertainty. In H. Konno, D. G. Luenberger, & J. M. Mulvey (Eds.) Financial engineering, Annals of Operations Research (Vol. 45, pp. 165–177).

  • Konno, H., Pliska, S. R. & Suzuki, K. I. (1993a). Optimal portfolios with asymptotic criteria. In H. Konno, D. G. Luenberger, & J. M. Mulvey (Eds.), Financial engineering, Annals of Operations Research (Vol. 45, pp. 187–204).

  • Konno, H., H. Shirakawa, & H. Yamazaki. (1993b). A mean-absolute deviation—Skewness portfolio optimization model. In H. Konno, D. G. Luenberger, & J. M. Mulvey (Eds.), Financial engineering, Annals of Operations Research (Vol. 45, pp. 205–230).

  • Lakonishok, V., & Vermaelen, T. (1990). Anomalous price behavior around repurchase tender offers. Journal of Finance, 45, 455–477.

    Article  Google Scholar 

  • Lee, S. (1972). Goal programming for decision analysis. Philadelphia: Auerbach.

    Google Scholar 

  • Levy, H. (1999). Introduction to investments (2nd ed.). Cincinnati: South-Western College Publishing.

    Google Scholar 

  • Lo, A. W., Petrov, C., & Wierzbicki, M. (2003). It’s 11pm—Do you know where your liquidity is? The mean-variance-liquidity frontier. Journal of Investment Management, 1(1), 55–93.

    Google Scholar 

  • Markowitz, H. M. (1952). Portfolio selection. Journal of Finance, 7(1), 77–91.

    Google Scholar 

  • Markowitz, H. M. (1959). Portfolio selection: Efficient diversification of investment. Cowles Foundation Monograph (Vol. 16). New York: Wiley.

    Google Scholar 

  • Markowitz, H. M. (1987). Mean-variance analysis in portfolio choice and capital markets. Oxford: Basil Blackwell.

    Google Scholar 

  • Markowitz, H. M., & Xu, G. (1994). Data mining corrections. Journal of Portfolio Management, 21, 60–69.

    Article  Google Scholar 

  • McKinley Capital Management, Inc. (2006a). An assessment of the McKinley Capital emerging markets growth portfolio; A review of the factors, returns, and implementation.

  • McKinley Capital Management, Inc. (2006b). An assessment of a McKinley Capital Non-U.S. Developed Growth Portfolio—A review of the factors, returns, and implementation.

  • Menchero, J., Morozov, A., & Shepard, P. (2010). Global equity risk modeling. In J. B. Guerard (Ed.), The handbook of portfolio construction: Contemporary applications of Markowitz techniques. NewYork: Springer.

  • Nerlove, M. (1968). Factors affecting differences among rates of return on investments in individual common stocks. Review of Economics and Statistics, 50, 312–331.

    Article  Google Scholar 

  • Petrich, D. M., & Kahn, R. N. (2010). What matters most in portfolio construction? In J. B. Guerard (Ed.), The handbook of portfolio construction: Contemporary applications of Markowitz techniques. New York: Springer.

    Google Scholar 

  • Ramnath, S., Rock, S., & Shane, P. (2008). The financial forecasting literature: A taxonomy with suggestions for further research. International Journal of Forecasting, 24, 34–75.

    Article  Google Scholar 

  • Rosenberg, B. (1974). Extra-market components of covariance in security returns. Journal of Financial and Quantitative Analysis, 9, 263–274.

    Article  Google Scholar 

  • Rosenberg, S. A., & Marathe, V. (1979). Tests of capital asset pricing hypotheses. In H. Levy (Ed.), Research in finance (Vol. 1). Greenwich, CT: JAI Press.

    Google Scholar 

  • Rudd, A., & Clasing, H. K. (1982). Modern portfolio theory: The principles of investment management. Homewood, IL: Dow-Jones Irwin.

    Google Scholar 

  • Saxena, A., & Stubbs, R. A. (2012). An empirical case study of factor alignment using the USER model. Journal of Investing, 21, 25–44.

    Article  Google Scholar 

  • Schwartz, E., & Aronson, R. J. (1966). The corporate sector: A net exporter of funds. Southern Economic Journal, 33, 252–257.

    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. (2008). Portfolio selection in the presence of multiple criteria. In Handbook of financial engineering (pp. 3–24). New York: Springer.

  • Treynor, J. L. (2008). The invisible costs of trading. In J. L. Treynor (Ed.), Treynor on institutional investing. New York: Wiley.

    Google Scholar 

  • Utz, S., Wimmer, M., Hirschberger, M., & Steuer, R. E. (2014). Tri-criterion inverse portfolio optimization with application to socially responsible mutual funds. European Journal of Operational Research, 234(2), 491–498.

    Article  Google Scholar 

  • Wheeler, L. B. (1994). Changes in consensus earnings estimates and their impact on stock returns. In B. Bruce & C. B. Epstein (Eds.),The handbook of corporate earnings analysis.

  • Williams, J. B. (1938). The theory of investment value. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Yu, P. L. (1989). Multiple criteria decision making: Five basis concepts. In G. L. Nemhauser, A. H. G. Rinnooy Kan, & M. J. Todd (Eds.), Optimization (Vol. 1). Amsterdam: North-Holland.

    Chapter  Google Scholar 

Download references

Acknowledgements

The authors appreciate the comments of Ken Lawrence who was helpful in research conversations as well as updating multi-criteria references. The authors appreciate comments of Richard Brealey regarding portfolio construction with alternative techniques. The authors are appreciative of referee comments and suggestions prevented premature publication of this manuscript. Any errors remaining are the responsibility of the authors, primarily the principal author.

Author information

Authors and Affiliations

  1. McKinley Capital Management, Inc., 3301 C Street, Suite 500, Anchorage, AK, 99503, USA

    John B. Guerard Jr., Harry Markowitz, Ganlin Xu & Ziwei Wang

  2. Harry Markowitz Co., Inc., San Diego, CA, USA

    Harry Markowitz

  3. GuidedChoice.com, Inc., 8910 University Center Lane, Suite 400, San Diego, CA, 92122, USA

    Ganlin Xu

Authors
  1. John B. Guerard Jr.
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Harry Markowitz
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ganlin Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ziwei Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to John B. Guerard Jr..

Ethics declarations

Conflict of interest

The views and opinions expressed in this paper are those of the authors and may not represent or reflect those of McKinley Capital Management, LLC. All information contained herein is believed to be acquired from reliable sources but accuracy cannot be guaranteed. This paper is for informational purposes only, was prepared for academics and financially sophisticated and institutional audiences, and does not represent specific financial services or investment recommendations or advice.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Guerard, J.B., Markowitz, H., Xu, G. et al. Global portfolio construction with emphasis on conflicting corporate strategies to maximize stockholder wealth. Ann Oper Res 267, 203–219 (2018). https://doi.org/10.1007/s10479-016-2380-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10479-016-2380-4

Keywords

Search

Navigation