Z-score vs minimum variance preselection methods for constructing small portfolios
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DOIhttp://dx.doi.org/10.21511/imfi.17(1).2020.06
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Article InfoVolume 17 2020, Issue #1, pp. 64-76
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Several contributions in the literature argue that a significant in-sample risk reduction can be obtained by investing in a relatively small number of assets in an investment universe. Furthermore, selecting small portfolios seems to yield good out-of-sample performances in practice. This analysis provides further evidence that an appropriate preselection of the assets in a market can lead to an improvement in portfolio performance. For preselection, this paper investigates the effectiveness of a minimum variance approach and that of an innovative index (the new Altman Z-score) based on the creditworthiness of the companies. Different classes of portfolio models are examined on real-world data by applying both the minimum variance and the Z-score preselection methods. Preliminary results indicate that the new Altman Z-score preselection provides encouraging out-of-sample performances with respect to those obtained with the minimum variance approach.
- Keywords
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JEL Classification (Paper profile tab)C61, C63, G11
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References52
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Tables5
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Figures5
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- Figure 1. Ten preselected assets for each rebalancing date using Z-score preselection method
- Figure 2. Ten preselected assets for each rebalancing date using the minimum variance preselection method
- Figure 3. Out-of-sample compounded return for all models without preselection
- Figure 4. Out-of-sample compounded return for all models using minimum variance preselection
- Figure 5. Out-of-sample compounded return for all models using Z-score preselection
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- Table 1. List of portfolio strategies
- Table 2. List of 31 assets belonging to the investment universe considered
- Table 3. Out-of-sample results without preselection
- Table 4. Out-of-sample results using the minimum variance preselection
- Table 5. Out-of-sample results using Z-score preselection
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- Acerbi, C., & Tasche, D. (2002). On the coherence of expected shortfall. Journal of Banking & Finance, 26(7), 1487-1503.
- Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4), 589-609.
- Altman, E.I. (2002). Revisiting credit scoring models in a Basel 2 environment (NYU Working Paper No S-CDM-02-06).
- Altman, E.I. (2013). Predicting financial distress of companies: revisiting the Z-Score and ZETA models. In Handbook of Research Methods and Applications in Empirical Finance (chap 17, pp. 428-456). Edward Elgar Publishing.
- Altman, E. I., Haldeman, R. G., & Narayanan, P. (1977). ZETATM analysis A new model to identify bankruptcy risk of corporations. Journal of Banking & Finance, 1(1), 29-54.
- Altman, E. I., & Hotchkiss, E. (2006). Corporate Financial Distress and Bankruptcy: Predict and Avoid Bankruptcy, Analyze and Invest in Distressed Debt. John Wiley & Sons.
- Artzner, P., Delbaen, F., Eber, J., & Heath, D. (1999). Coherent measures of risk. Mathematical Finance, 9(3), 203-228.
- Bruni, R., Cesarone, F., Scozzari, A., & Tardella, F. (2017). On exact and approximate stochastic dominance strategies for portfolio selection. European Journal of Operational Research, 259(1), 322-329.
- Cesarone, F., & Colucci, S. (2018). Minimum risk versus capital and risk diversification strategies for portfolio construction. Journal of the Operational Research Society, 69(2), 183-200.
- Cesarone, F., Moretti, J., & Tardella, F. (2016). Optimally chosen small portfolios are better than large ones. Economics Bulletin, 36(4), 1876-1891.
- Cesarone, F., Moretti, J., & Tardella, F. (2018). Why small portfolios are preferable and how to choose them. The Journal of Financial Perspectives, 5(1), 103-116.
- Cesarone, F., Scozzari, A., & Tardella, F. (2013). A new method for mean-variance portfolio optimization with cardinality constraints. Annals of Operations Research, 205(1), 213-234.
- Cesarone, F., Scozzari, A., & Tardella, F. (2019). An optimization-diversification approach to portfolio selection. Journal of Global Optimization, 1-21.
- Cesarone, F., & Tardella, F. (2017). Equal risk bounding is better than risk parity for portfolio selection. Journal of Global Optimization, 68(2), 439-461.
- Chekhlov, A., Uryasev, S., & Zabarankin, M. (2005). Drawdown measure in portfolio optimization. International Journal of Theoretical and Applied Finance, 8(1), 13-58.
- Choueifaty, Y., & Coignard, Y. (2008). Toward maximum diversification. The Journal of Portfolio Management, 35(1), 40-51.
- Choueifaty, Y., Froidure, T., & Reynier, J. (2013). Properties of the most diversified portfolio. Journal of Investment Strategies, 2(2), 49-70.
- DeMiguel, V., Garlappi, L., & Uppal, R. (2009). Optimal versus naive diversification: How inefficient is the 1/N portfolio strategy? Review of Financial Studies, 22(5), 1915-1953.
- Choueifaty, Y., & Coignard, Y. (2008). Toward Maximum Diversification. The Journal of Portfolio Management Fall, 35(1), 40-51.
- Evans, J. L., & Archer, S. H. (1968). Diversification and the reduction of dispersion: an empirical analysis. The Journal of Finance, 23(5), 761-767.
- Fábián, C. I., Mitra, G., Roman, D., & Zverovich, V. (2011). An enhanced model for portfolio choice with SSD criteria: a constructive approach. Quantitative Finance, 11(10), 1525-1534.
- Gonzalez, F., Haas, F., Persson, M., Toledo, L., Violi, R., Wieland, M., & Zins, C. (2004). Market dynamics associated with credit ratings: a literature review (ECB occasional paper, 16).
- Goodwin, T. H. (1998). The information ratio. Financial Analysts Journal, 54(4), 34-43.
- Grothe, M. (2013). Market pricing of credit rating signals (ECB Working Paper).
- Hand, J. R., Holthausen, R. W., & Leftwich, R. W. (1992). The effect of bond rating agency announcements on bond and stock prices. The Journal of Finance, 47(2), 733-752.
- Hsueh, L. P., & Liu, Y A. (1992). Market anticipation and the effect of bond rating changes on common stock prices. Journal of Business Research, 24(3), 225-239.
- Hull, J., Predescu, M., & White, A. (2004). The relationship between credit default swap spreads, bond yields, and credit rating announcements. Journal of Banking & Finance, 28(11), 2789-2811.
- Jensen, M. C. (1968). The performance of mutual funds in the period 1945–1964. The Journal of Finance, 23(2), 389-416.
- Kliger, D., & Sarig, O. (2000). The information value of bond ratings. The Journal of Finance, 55(6), 2879-2902.
- Lhabitant, F. S. (2017). Portfolio Diversification.
- MacCann, B. B. (1989). The investor’s guide to fidelity funds. John Wiley & Sons Incorporated.
- Maillard, S., Roncalli, T., & Teiletche, J. (2010). The Properties of Equally Weighted Risk Contribution Portfolios. The Journal of Portfolio Management, 36(4), 60-70.
- Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77-91.
- Markowitz, H. (1959). Portfolio selection: Efficient diversification of investments (Cowles Foundation for Research in Economics at Yale University, Monograph 16). John Wiley & Sons Inc., New York.
- Meucci, A. (2009). Managing diversification. Risk, 22, 74-79.
- Micu, M., Remolona, E. M., & Wooldridge, P. D. (2006). The price impact of rating announcements: which announcements matter?
- Newbould, G. D., & Poon, P. S. (1993). The minimum number of stocks needed for diversification. Financial Practice and Education, 3(2), 85-87.
- Norden, L., & Weber, M. (2004). Informational efficiency of credit default swap and stock markets: The impact of credit rating announcements. Journal of Banking & Finance, 28(11), 2813-2843.
- Ogryczak, W., & Ruszczynski, A. (2002). Dual stochastic dominance and related mean-risk models. SIAM Journal on Optimization, 13(1), 60-78.
- Pflug, G., Pichler, A., & Wozabal, D. (2012). The 1/N investment strategy is optimal under high model ambiguity. Journal of Banking & Finance, 36, 410-417.
- Rachev, S., Biglova, A., Ortobelli, S., & Stoyanov, S. (2004). Different Approaches to Risk Estimation in Portfolio Theory. The Journal of Portfolio Management, 31(1), 103-112.
- Rockafellar, R., & Uryasev, S. (2000). Optimization of Conditional Value-at-Risk. Journal of Risk, 2(3), 21-42.
- Rockafellar, R. T., & Uryasev, S. (2002). Conditional Value-at-Risk for General Distributions. Journal of Banking & Finance, 26, 1443-1471.
- Roman, D., Mitra, G., & Zverovich, V. (2013). Enhanced indexation based on second-order stochastic dominance. European Journal of Operational Research, 228(1), 273-281.
- Roncalli, T. (2014). Introduction to risk parity and budgeting. Chapman & Hall/CRC Financial Mathematics Series, CRC Press, Boca Raton, FL.
- Sharpe, W. F. (1966). Mutual fund performance. Journal of Business, 39(1), 119-138.
- Sharpe, W. F. (1994). The sharpe ratio. The Journal of Portfolio Management, 21(1), 49-58.
- Sortino, F., & Satchell, S. (2001). Managing downside risk in financial markets.
- Statman, M. (1987). How many stocks make a diversified portfolio? Journal of Financial and Quantitative Analysis, 22(3), 353-363.
- Tang, G. Y. (2004). How efficient is naive portfolio diversification? An educational note. Omega, 32(2), 155-160.
- Tu, J., & Zhou, G. (2011). Markowitz meets Talmud: A combination of sophisticated and naive diversification strategies. Journal of Financial Economics, 99(1), 204-215.
- Valle, C. A., Roman, D., & Mitra, G. (2017). Novel approaches for portfolio construction using second order stochastic dominance. Computational Management Science, 14(2), 257-280.