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References


Utility Theory

  • Bernoulli, D. (1954). Exposition of a New Theory on the Measurement of Risk. Econometrica, 22(1), 23–36.
  • von Neumann, J., & Morgenstern, O. (1944). Theory of Games and Economic Behavior. Princeton University Press.
  • Arrow, K. J. (1971). Essays in the Theory of Risk-Bearing. North-Holland.
  • Pratt, J. W. (1964). Risk aversion in the small and in the large. Econometrica, 32(1-2), 122-136.
  • Merton, R. C. (1971). Optimum Consumption and Portfolio Rules in a Continuous-Time Model. Journal of Economic Theory, 3(4), 373–413.
  • Kelly, J. L. (1956). A New Interpretation of Information Rate. Bell System Technical Journal, 35, 917–926.
  • Thorp, E. O. (1971). Portfolio Choice and the Kelly Criterion. Proceedings of the Business and Economics Section, American Statistical Association.

Markowitz Portfolio Theory

  • Markowitz, H. (1952). Portfolio Selection. Journal of Finance, 7(1), 77–91.
  • Sharpe, W. F. (1964). Capital Asset Prices: A Theory of Market Equilibrium under Conditions of Risk. Journal of Finance, 19(3), 425–442.

Principled Heuristics

  • 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.
  • Qian, E. (2005). Risk parity portfolios: Efficient portfolios through true diversification. PanAgora Asset Management.
  • Choueifaty, Y., & Coignard, Y. (2008). Toward Maximum Diversification. Journal of Portfolio Management, 35(1), 40–51.
  • Mercurio, P. J., Wu, Y., & Xie, H. (2020). An Entropy-Based Approach to Portfolio Optimization. Entropy, 22(3), 332. https://doi.org/10.3390/e22030332
  • Mercurio, P. J., Wu, Y., & Xie, H. (2020). Portfolio Optimization for Binary Options Based on Relative Entropy. Entropy, 22(7), 752. https://doi.org/10.3390/e22070752
  • López de Prado, Marcos, Building Diversified Portfolios that Outperform Out-of-Sample (May 23, 2016). The Journal of Portfolio Management Summer 2016, 42 (4) 59 - 69. https://doi.org/10.3905/jpm.2016.42.4.059

Risk Measures

  • Morgan, J. P. (1996). RiskMetrics-Technical Document. Morgan Guaranty Trust Company.
  • Artzner, P., Delbaen, F., Eber, J.-M., & Heath, D. (1999). Coherent Measures of Risk. Mathematical Finance, 9(3), 203–228.
  • Rockafellar, R. T., & Uryasev, S. (2000). Optimization of Conditional Value-at-Risk. Journal of Risk, 2(3), 21–41.
  • Rockafellar, R. T., & Uryasev, S. (2002). Conditional Value-at-Risk for General Loss Distributions. Journal of Banking & Finance, 26(7), 1443–1471.
  • Ahmadi-Javid, A. (2012). Entropic Value-at-Risk: A New Coherent Risk Measure. Journal of Optimization Theory and Applications, 155(3), 1105–1123.
  • Föllmer, H., & Schied, A. (2002). Convex Measures of Risk and Trading Constraints. Finance and Stochastics, 6(4), 429–447.

Online Learning

  • Cover, T. M. (1991). Universal Portfolios. Mathematical Finance, 1(1), 1–29.
  • Hannan, J. (1957). Approximation to Bayes Risk in Repeated Play. Contributions to the Theory of Games, 3, 97–139.
  • Abernethy, J., Hazan, E., & Rakhlin, A. (2008). Competing in the dark: An efficient algorithm for bandit linear optimization. Proceedings of the 21st Annual Conference on Learning Theory (COLT), 263-274.
  • Kivinen, J., & Warmuth, M. K. (1997). Exponentiated Gradient versus Gradient Descent for Linear Predictors. Information and Computation, 132(1), 1–63.

Distributionally Robust

  • Ben-Tal, A., & Nemirovski, A. (1999). Robust solutions of uncertain linear programs. Operations Research Letters, 25(1), 1–13. https://doi.org/10.1016/S0167-6377(99)00016-4
  • Hu, Z., & Hong, L. J. (2013). Kullback-Leibler divergence constrained distributionally robust optimization. Available at Optimization Online, 1(2), 9.
  • Mohajerin Esfahani, P., Kuhn, D. Data-driven distributionally robust optimization using the Wasserstein metric: performance guarantees and tractable reformulations. Math. Program. 171, 115–166 (2018). https://doi.org/10.1007/s10107-017-1172-1
  • Blanchet, J., Chen, L., & Zhou, X. Y. (2022). Distributionally robust mean-variance portfolio selection with Wasserstein distances. Management science, 68(9), 6382-6410.