참고문헌 (32)

1. Andersen ED, Gondzio J, Meszaros C, and Xu X (1996). Implementation of interior point methods for large scale linear programming, HEC/Universite de Geneve. 

2. Best MJ and Grauer RR (1991). On the sensitivity of mean-variance-efficient portfolios to changes in asset means: some analytical and computational results, The review of financial studies, 4, 315-342. 

   상세보기

3. Bixby RE (2002). Solving real-world linear programs: A decade and more of progress, Operations research, 50, 3-15. 

   상세보기

4. Brodie J, Daubechies I, De Mol C, Giannone D, and Loris I (2009). Sparse and stable Markowitz portfolios. In Proceedings of the National Academy of Sciences, 106, 12267-12272. 

   상세보기

5. Cai T, Liu W, and Luo X (2011). A constrained ℓ 1 minimization approach to sparse precision matrix estimation, Journal of the American Statistical Association, 106, 594-607. 

   상세보기

6. Candes E and Tao T (2007). The Dantzig selector: Statistical estimation when p is much larger than n, The annals of Statistics, 35, 2313-2351. 

   상세보기

7. Cesarone F, Scozzari A, and Tardella F (2011). Portfolio Selection Problems in Practice: A Comparison between Linear and Quadratic Optimization Models, arXiv preprint arXiv:1105.3594 

8. Chen C, Li X, Tolman C, Wang S, and Ye Y (2013). Sparse Portfolio Selection via Quasi-Norm Regularization, arXiv preprint arXiv:1312.6350 

9. DeMiguel V, Garlappi L, and Uppal R (2009). Optimal versus naive diversification: How inefficient is the 1/N portfolio strategy?, The Review of Financial Studies, 22, 1915-1953. 

   상세보기

10. Dantzig GB and Infanger G (1993). Multi-stage stochastic linear programs for portfolio optimization, Annals of Operations Research, 45, 59-76. 

    상세보기

11. Fan J, Liao Y, and Mincheva M (2013). Large covariance estimation by thresholding principal orthogonal complements, Journal of the Royal Statistical Society. Series B, Statistical methodology, 75. 

    상세보기

12. Fastrich B, Paterlini S, and Winker P (2015). Constructing optimal sparse portfolios using regularization methods, Computational Management Science, 12, 417-434. 

    상세보기

13. Koberstein A (2005). The dual simplex method, techniques for a fast and stable implementation, Unpublished doctoral thesis, Universitat Paderborn, Paderborn, Germany. 

14. Konno H and Wijayanayake A (1999). Mean-absolute deviation portfolio optimization model under transaction costs, Journal of the Operations Research Society of Japan, 42, 422-435. 

    상세보기

15. Konno H and Yamazaki H (1991). Mean-absolute deviation portfolio optimization model and its applications to Tokyo stock market, Management science, 37, 519-531. 

    상세보기

16. Ledoit O and Wolf M (2003). Improved estimation of the covariance matrix of stock returns with an application to portfolio selection, Journal of Empirical Finance, 10, 603-621. 

    상세보기

17. Lee TH and Seregina E (2020). Optimal Portfolio Using Factor Graphical Lasso, arXiv preprint arXiv:2011.00435 

18. Li J (2015). Sparse and stable portfolio selection with parameter uncertainty, Journal of Business & Economic Statistics, 33, 381-392. 

    상세보기

19. Lintner J (1965). The valuation of risk assets and the selection of risky investments in stock portfolios and capital budgets, In Stochastic Optimization Models in Finance, 131-155. 

20. Mansini R, Ogryczak W, and Speranza MG (2014). Twenty years of linear programming based portfolio optimization, European Journal of Operational Research, 234, 518-535. 

    상세보기

21. Markowitz H (1952). Portfolio Selection, The Journal of Finance, 7, 77-91. 

    상세보기

22. Millington T and Niranjan M (2017). Robust portfolio risk minimization using the graphical lasso. In International Conference on Neural Information Processing, 863-872, Springer. 

23. Murillo JML and Rodr'iguez AA (2008). Algorithms for Gaussian bandwidth selection in kernel density estimators. Advances in Neural Information Processing Systems. 

24. Pantaleo E, Tumminello M, Lillo F, and Mantegna RN (2011). When do improved covariance matrix estimators enhance portfolio optimization? An empirical comparative study of nine estimators, Quantitative Finance, 11, 1067-1080. 

    상세보기

25. Park S, Lee ER, Lee S, and Kim G (2019a). Dantzig type optimization method with applications to portfolio selection, Sustainability, 11, 3216. 

    상세보기

26. Park S, Song H, and Lee S (2019b). Linear programing models for portfolio optimization using a benchmark, The European Journal of Finance, 25, 435-457. 

    상세보기

27. Pun CS and Wong HY (2015). High-dimensional static and dynamic portfolio selection problems via l1 minimization, Working paper of the Chinese University of Hong Kong. 

28. Rockafellar RT and Uryasev S (2000). Optimization of conditional value-at-risk, Journal of risk, 2, 21-42. 

    상세보기

29. Ross SA (1976). The arbitrage theory of capital asset pricing, Handbook of the Fundamentals of Financial Decision Making: Part I, 11-30. 

30. Sharpe WF (1964). Capital asset prices: A theory of market equilibrium under conditions of risk, The Journal of Finance, 19, 425-442. 

    상세보기

31. Shen W, Wang J, and Ma S (2014). Doubly regularized portfolio with risk minimization, Twenty-Eighth AAAI Conference on Artificial Intelligence, 28, 1286-1292. 

32. Zhou S, Lafferty J, and Wasserman L (2010). Time varying undirected graphs, Machine Learning, 80, 295-319. 

    상세보기