A sparse enhanced indexation model with norm and its alternating quadratic penalty method

References

• Beasley, J. E., Meade, N., & Chang, T. J. (2003). An evolutionary heuristic for the index tracking problem. European Journal of Operational Research, 148(3), 621–643.
   Web of Science ®Google Scholar
• Blumensath, T., & Davies, M. E. (2009). Iterative hard thresholding for compressed sensing. Applied and Computational Harmonic Analysis, 27(3), 265–274.
   Web of Science ®Google Scholar
• Bonami, P., & Lejeune, M. (2009). An exact solution approach for portfolio optimization problems under stochastic and integer constraints. Operations research, 57(3), 650–670.
   Web of Science ®Google Scholar
• Bruni, R., Scozzari, A., Cesarone, F., & Tardella, F. (2012). A new stochastic dominance approach to enhanced index tracking problems. Economics Bulletin, 32(4), 3460–3470.
   Google Scholar
• Çay, S. B., Góez, J. C., & Terlaky, T. (2016). Effects of disjunctive conic cuts within a branch and conic cut algorithm to solve asset allocation problems. Technical Report 16T–005. Lehigh University.
   Google Scholar
• Dose, C., & Cincotti, S. (2005). Clustering of financial time series with application to index and enhanced index tracking portfolio. Physica A: Statistical Mechanics and its Applications, 355(1), 145–151.
   Web of Science ®Google Scholar
• Fang, Y. , & Wang, S. (2005). A fuzzy index tracking portfolio selection model. Lecture Notes in Computer Science, 3516, 554–561.
   Google Scholar
• Filippi, C., Guastaroba, G., & Speranza, M. G. (2016). A heuristic framework for the bi-objective enhanced index tracking problem. Omega, 65, 122–137.
   Web of Science ®Google Scholar
• Frank, L., & Friedman, J. (1993). A statistical view of some chemometrics regression tools. Technometrics, 35(2), 109–135.
   Web of Science ®Google Scholar
• Fu, W. (1998). Penalized regressions: the bridge versus the lasso. Journal of computational and graphical statistics, 7(3), 397–416.
   Web of Science ®Google Scholar
• Konno, H., & Yamazaki, H. (1991). Mean-absolute deviation portfolio optimization model and its applications to Tokyo stock market. Management science, 37(5), 519–531.
   Web of Science ®Google Scholar
• Konno, H., & Wijayanayake, A. (2001). Portfolio optimization problem under concave transaction costs and minimal transaction unit constraints. Mathematical Programming, 89(2), 233–250.
   Web of Science ®Google Scholar
• Lejeune, M. A. (2012). Game theoretical approach for reliable enhanced indexation. Decision Analysis, 9(2), 146–155.
   Web of Science ®Google Scholar
• Li, Q., & Bao, L. (2014). Enhanced index tracking with multiple time-scale analysis. Economic Modelling, 39, 282–292.
   Web of Science ®Google Scholar
• Lu, Z. (2014). Iterative hard thresholding methods for ℓ0 regularized convex cone programming. Mathematical Programming, 147(1–2), 125–154.
   Web of Science ®Google Scholar
• Lu, Z., & Zhang, Y. (2013). Sparse approximation via penalty decomposition methods. SIAM Journal on Optimization, 23(4), 2448–2478.
   Web of Science ®Google Scholar
• Markowitz, H. (1952). Portfolio selection. The journal of finance, 7(1), 77–91.
   Google Scholar
• Mulvey, J. M., & Shetty, B. (2004). Financial planning via multi-stage stochastic optimization. Computers & Operations Research, 31(1), 1–20.
   Web of Science ®Google Scholar
• Palmquist, J., & Krokhmal, P. (1999). Portfolio optimization with conditional value-at-risk objective and constraints. Department of Industrial & Systems Engineering, University of Florida, 4, 11–27.
   Google Scholar
• Ruiz-Torrubiano, R., & Suárez, A. (2009). A hybrid optimization approach to index tracking. Annals of Operations Research, 166(1), 57–71.
   Web of Science ®Google Scholar
• Tibshirani, R. (1996). Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society. Series B (Methodological), 58(1), 267–288.
   Web of Science ®Google Scholar
• Tsitsiklis, J. N. & Van Roy, B. (2001). Regression methods for pricing complex American-style options. IEEE Transactions on Neural Networks, 12(4), 694–703.
   PubMed Web of Science ®Google Scholar
• Xu, F., Wang, G., & Gao, Y. (2014). Nonconvex L1/2 regularization for sparse portfolio selection. Pacific Journal of Optimization, 10(1), 163–176.
   Web of Science ®Google Scholar
• Xu, F., Wang, M., Dai, Y., & Xu, D. (2017). A sparse enhanced indexation model with chance and cardinality constraints. Journal of Global Optimization, 70(3), 1–21.
   Google Scholar
• Xu, F., Xu, Z. & Xue, H. (2015). Sparse index tracking based on L1/2 model and algorithm. arXiv:1506.05867.\newpage
   Google Scholar
• Xu, Z., Chang, X., Xu, F., & Zhang, H. (2012). L1/2 regualrization: an iterative half thresholding algorithm. IEEE Transactions on Numerical Networks and Learning Systems, 23, 1013–1027.
   PubMed Web of Science ®Google Scholar
• Yu, H., & Wang, G. (2014). SART-type half-threshold filtering approach for CT reconstruction. IEEE Access, 2, 602–613.
   Web of Science ®Google Scholar