Portfolio selection based on Extended Gini Shortfall risk measures

References

[1] C. Acerbi, Spectral measures of risk: A coherent representation of subjective risk aversion, J. Bank. Finance 26 (2002), no. 7, 1505–1518. 10.1016/S0378-4266(02)00281-9Suche in Google Scholar

[2] C. Acerbi and P. Simonetti, Portfolio optimization with spectral measures of risk, preprint (2002), https://arxiv.org/abs/cond-mat/0203607. Suche in Google Scholar

[3] C. Acerbi and D. Tasche, On the coherence of expected shortfall, J. Bank. Finance 26 (2002), no. 7, 1487–1503. 10.1016/S0378-4266(02)00283-2Suche in Google Scholar

[4] A. Adam, M. Houkari and J. P. Laurent, Spectral risk measures and portfolio selection, J. Bank. Finance 32 (2008), no. 9, 1870–1882. 10.1016/j.jbankfin.2007.12.032Suche in Google Scholar

[5] A. Ahmadi-Javid and M. Fallah-Tafti, Portfolio optimization with entropic value-at-risk, European J. Oper. Res. 279 (2019), no. 1, 225–241. 10.1016/j.ejor.2019.02.007Suche in Google Scholar

[6] P. Artzner, F. Delbaen, J. M. Eber and D. Heath, Coherent measures of risk, Math. Finance 9 (1999), no. 3, 203–228. 10.1111/1467-9965.00068Suche in Google Scholar

[7] B. N. Ashraf, Stock markets reaction to COVID-19: Cases or fatalities?, Res. Int. Bus. Finance 54 (2020), Article ID 101249. 10.1016/j.ribaf.2020.101249Suche in Google Scholar PubMed PubMed Central

[8] S. R. Baker, N. Bloom, S. J. Davis, K. Kost, M. Sammon and T. Viratyosin, The unprecedented stock market reaction to COVID-19, Rev. Asset Pricing Stud. 10 (2020), no. 4, 742–758. 10.1093/rapstu/raaa008Suche in Google Scholar

[9] A. Beck and N. Guttmann-Beck, FOM – a MATLAB toolbox of first-order methods for solving convex optimization problems, Optim. Methods Softw. 34 (2019), no. 1, 172–193. 10.1080/10556788.2018.1437159Suche in Google Scholar

[10] L. Ben Hssain, J. Agouram and G. Lakhnati, Impact of COVID-19 pandemic on Moroccan sectoral stocks indices, Sci. African 17 (2022), Article ID e01321. 10.1016/j.sciaf.2022.e01321Suche in Google Scholar PubMed PubMed Central

[11] M. Berkhouch, G. Lakhnati and M. B. Righi, Extended Gini-type measures of risk and variability, Appl. Math. Finance 25 (2018), no. 3, 295–314. 10.1080/1350486X.2018.1538806Suche in Google Scholar

[12] F. Bilen, Z. Csizmadia and T. Illés, Anstreicher–Terlaky type monotonic simplex algorithms for linear feasibility problems, Optim. Methods Softw. 22 (2007), no. 4, 679–695. 10.1080/10556780701223541Suche in Google Scholar

[13] K. H. Borgwardt, The Simplex Method: A Probabilistic Analysis, Vol. 1, Springer, Berlin, 2012. Suche in Google Scholar

[14] L. Ceriani and P. Verme, The origins of the Gini index: Extracts from Variabilità e Mutabilità (1912) by Corrado Gini, J. Econ. Inequal. 10 (2012), no. 3, 421–443. 10.1007/s10888-011-9188-xSuche in Google Scholar

[15] P. Cheridito and E. Kromer, Reward-risk ratios, J. Invest. Strategies 3 (2013), no. 1, 3–18. 10.21314/JOIS.2013.022Suche in Google Scholar

[16] G. Choquet, Theory of capacities, Ann. Inst. Fourier 5 (1953), 131–295. 10.5802/aif.53Suche in Google Scholar

[17] R. A. Dana, A representation result for concave Schur concave functions, Int. J. Math. Stat. Financ. Econ. 15 (2005), no. 4, 613–634. 10.1111/j.1467-9965.2005.00253.xSuche in Google Scholar

[18] G. Dantzig, Linear Programming and Extensions, Princeton University, Princeton, 2016. Suche in Google Scholar

[19] G. M. Davis and K. B. Ensor, Risk: Diversification and performance precursors for stocks, Amer. J. Math. Manag. Sci. 28 (2018), no. 3–4, 255–273. 10.1080/01966324.2008.10737728Suche in Google Scholar

[20] J. Dhaene, M. Denuit, M. J. Goovaerts, R. Kaas and D. Vyncke, The concept of comonotonicity in actuarial science and finance: Theory, Insurance Math. Econom. 31 (2022), no. 1, 3–33. 10.1016/S0167-6687(02)00134-8Suche in Google Scholar

[21] N. Engelhardt, M. Krause, D. Neukirchen and P. N. Posch, Trust and stock market volatility during the COVID-19 crisis, Financ. Res. Lett. 38 (2021), Article ID 101873. 10.1016/j.frl.2020.101873Suche in Google Scholar PubMed PubMed Central

[22] C. I. Fábián, G. Mitra, D. Roman and V. Zverovich, An enhanced model for portfolio choice with SSD criteria: A constructive approach, Quant. Finance 11 (2011), no. 10, 1525–1534. 10.1080/14697680903493607Suche in Google Scholar

[23] L. Favre and J. A. Galeano, Mean-modified value-at-risk optimization with hedge funds, J. Alternative Invest. 5 (2022), no. 2, 21–25. 10.3905/jai.2002.319052Suche in Google Scholar

[24] H. Föllmer and A. Schied, Preface to the third edition, Stochastic Finance, De Gruyter, Berlin (2011), https://www.degruyter.com/document/doi/10.1515/9781478004356-001/html. Suche in Google Scholar

[25] E. Furman, R. Wang and R. Zitikis, Gini-type measures of risk and variability: Gini shortfall, capital allocations, and heavy-tailed risks, J. Banking & Finance 83 (2017), 70–84. 10.1016/j.jbankfin.2017.06.013Suche in Google Scholar

[26] I. Gilboa and D. Schmeidler, Maxmin expected utility with non-unique prior, J. Math. Econom. 18 (1989), no. 2, 141–153. 10.1016/0304-4068(89)90018-9Suche in Google Scholar

[27] S. Guo, H. Xu and L. Zhang, Probability approximation schemes for stochastic programs with distributionally robust second-order dominance constraints, Optim. Methods Softw. 32 (2017), no. 4, 770–789. 10.1080/10556788.2016.1175003Suche in Google Scholar

[28] B. Grechuk, A. Molyboha and M. Zabarankin, Maximum entropy principle with general deviation measures, Math. Oper. Res. 34 (2009), no. 2, 445–467. 10.1287/moor.1090.0377Suche in Google Scholar

[29] H. Iiduka, Two stochastic optimization algorithms for convex optimization with fixed point constraints, Optim. Methods Softw. 34 (2019), no. 4, 731–757. 10.1080/10556788.2018.1425860Suche in Google Scholar

[30] E. Jondeau, S. H. Poon and M. Rockinger, Financial Modeling Under Non-Gaussian Distributions, Springer, London, 2007. Suche in Google Scholar

[31] H. Konno and H. Yamazaki, Mean-absolute deviation portfolio optimization model and its applications to Tokyo stock market, Manag. Sci. 37 (1991), no. 5, 519–531. 10.1287/mnsc.37.5.519Suche in Google Scholar

[32] S. Kusuoka, On law invariant coherent risk measures, Advances in Mathematical Economics, Springer, Tokyo (2001), 83–95. 10.1007/978-4-431-67891-5_4Suche in Google Scholar

[33] C. Lim, H. D. Sherali and S. Uryasev, Portfolio optimization by minimizing conditional value-at-risk via nondifferentiable optimization, Comput. Optim. Appl. 46 (2010), no. 3, 391–415. 10.1007/s10589-008-9196-3Suche in Google Scholar

[34] H. M. Markowits, Portfolio selection, J. Finance 7 (1952), no. 1, 71–91. 10.1111/j.1540-6261.1952.tb01525.xSuche in Google Scholar

[35] R. D. Martin, S. Z. Rachevand and F. Siboulet, Phi-alpha optimal portfolios and extreme risk management, Wilmott 6 (2003), 70–83. 10.1002/wilm.42820030619Suche in Google Scholar

[36] S. Nickel, C. Steinhardt, H. Schlenker, W. Burkart and M. Reuter-Oppermann, Ibm ilog cplex optimization studio, Angewandte Optimierung mit IBM ILOG CPLEX Optimization Studio, Springer, Berlin (2021), 9–23. 10.1007/978-3-662-62185-1_2Suche in Google Scholar

[37] W. Ogryczak and A. Ruszczyński, On consistency of stochastic dominance and mean-semideviation models, Math. Program. 89 (2001), no. 2, 217–232. 10.1007/PL00011396Suche in Google Scholar

[38] W. Ogryczak and T. Śliwiński, On solving the dual for portfolio selection by optimizing conditional value at risk, Comput. Optim. Appl. 50 (2011), no. 3, 591–595. 10.1007/s10589-010-9321-ySuche in Google Scholar

[39] S. Pisal, Rise of Facebook, Amazon, Apple, Netflix, Google during COVID-19 pandemic, 2021. Suche in Google Scholar

[40] G. G. Polak, D. F. Rogers and D. J. Sweeney, Risk management strategies via minimax portfolio optimization, European J. Oper. Res. 207 (2010), no. 1, 409–419. 10.1016/j.ejor.2010.04.025Suche in Google Scholar

[41] M. O. Rieger, Co-monotonicity of optimal investments and the design of structured financial products, Finance and Stochastics 15 (2011), no. 1, 27–55. 10.1007/s00780-009-0117-9Suche in Google Scholar

[42] R. T. Rockafellar and S. Uryasev, Optimization of conditional value-at-risk, J. Risk 2 (2000), 21–42. 10.21314/JOR.2000.038Suche in Google Scholar

[43] L. Rüschendorf, Mathematical Risk Analysis, Springer, Heidelberg, 2013. 10.1007/978-3-642-33590-7Suche in Google Scholar

[44] D. Schmeidler, Integral representation without additivity, Proc. Amer. Math. Soc. 97 (1986), no. 2, 255–261. 10.1090/S0002-9939-1986-0835875-8Suche in Google Scholar

[45] H. D. Sherali, J. Desai and T. S. Glickman, Allocating emergency response resources to minimize risk with equity considerations, Amer. J. Math. Manag. Sci. 24 (2004), no. 3–4, 367–410. 10.1080/01966324.2004.10737638Suche in Google Scholar

[46] P. Soto-Acosta, COVID-19 pandemic: Shifting digital transformation to a high-speed gear, Inform. Syst. Manag. 37 (2020), no. 4, 260–266. 10.1080/10580530.2020.1814461Suche in Google Scholar

[47] P. K. Srivastava and D. C. Bisht, A segregated advancement in the solution of triangular fuzzy transportation problems, Amer. J. Math. Manag. Sci 40 (2021), no. 2, 134–144. 10.1080/01966324.2020.1854137Suche in Google Scholar

[48] R. J. Vanderbei, Linear Programming, Springer, Cham, 2020. 10.1007/978-3-030-39415-8Suche in Google Scholar

[49] W. Wang, W. Li, N. Zhang and K. Liu, Portfolio formation with preselection using deep learning from long-term financial data, Expert Syst. Appl. 143 (2020), Article ID 113042. 10.1016/j.eswa.2019.113042Suche in Google Scholar

[50] J. Z. Wang, J. J. Wang, Z. G. Zhang and S. P. Guo, Forecasting stock indices with back propagation neural network, Expert Syst. Appl. 38 (2011), no. 11, 14346–14355. 10.1016/j.eswa.2011.04.222Suche in Google Scholar

[51] M. E. Yaari, The dual theory of choice under risk, Econometrica 55 (1987), 95–115. 10.2307/1911158Suche in Google Scholar