- No Reading Done
- Extensive Reading Done
- Intensive Reading Done
- Z. Jiang, D. Xu, and J. Liang, “A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem,” Deep Portf. Manag., pp. 1–31, 2017.
- A. Agarwal, E. Hazan, S. Kale, R. E. Schapire, C. Science, and O. Street, “Algorithms for Portfolio Management based on the Newton Method,” Online, pp. 9–16, 2006.
- G. Creamer and Y. Freund, “Automated trading with boosting and expert weighting,” Quant. Financ., vol. 10, no. 4, pp. 401–420, 2010.
- G. G. Creamer, “Can a corporate network and news sentiment improve portfolio optimization using the Black–Litterman model?,” Quant. Financ., vol. 15, no. 8, pp. 1405–1416, 2015.
- J. B. Heaton, N. G. Polson, and J. H. Witte, “Deep learning for finance: deep portfolios,” Appl. Stoch. Model. Bus. Ind., vol. 33, no. 1, pp. 3–12, Jan. 2017.
- J. Sirignano, “Deep Learning for Limit Order Books,” 2016.
- J. B. Heaton, N. G. Polson, and J. H. Witte, “Deep Portfolio Theory,” no. May, pp. 1–17, 2016.
- C. S. Forbes and W. Maneesoonthorn, “Discussion of ‘Deep learning for finance: deep portfolios,’” Appl. Stoch. Model. Bus. Ind., vol. 33, no. 1, pp. 13–15, 2017.
- Y.-W. Seo, J. A. Giampapa, and K. Sycara, “Financial news analysis for intelligent portfolio management,” no. CMU-RI-TR-04-04, 2004.
- K. Sycara, Katia P and Zeng, D and Decker, “Intelligent Agents in Portfolio Managment,” Agent Technol., no. 4, pp. 267—281, 1998.
- A. Borodin and R. E. Vincent, “Machine Learning and Markets **Can we learn to beat the best stock.”
- G. Ban, N. El Karoui, A. E. B. Lim, and G. Ban, “Machine Learning and Portfolio Optimization,” no. February 2017, pp. 1–50, 2016.
- B. Li, S. C. H. Hoi, D. Sahoo, and Z. Y. Liu, “Moving average reversion strategy for on-line portfolio selection,” Artif. Intell., vol. 222, pp. 104–133, 2015.
- X. Li, H. Xie, L. Chen, J. Wang, and X. Deng, “News impact on stock price return via sentiment analysis,” Knowledge-Based Syst., vol. 69, no. 1, pp. 14–23, 2014.
- L. Györfi, G. Lugosi, and F. Udina, “Nonparametric kernel-based sequential investment strategies,” Math. Financ., vol. 16, no. 2, pp. 337–357, 2006.
- B. Li, D. Sahoo, and S. C. H. Hoi, “OLPS: A Toolbox for On-Line Portfolio Selection,” J. Mach. Learn. Res., vol. 1, pp. 1–5, 2015.
- D. P. Helmbold, R. E. Schapire, Y. Singer, and M. K. Warmuth, “On-Line Portfolio Selection Using Multiplicative Updates,” Math. Financ., vol. 8, no. 4, pp. 325–347, Oct. 1998.
- B. Li and S. C. H. Hoi, “On-Line Portfolio Selection with Moving Average Reversion,” Proc. 29th Int. Conf. Mach. Learn., pp. 273–280, 2012.
- B. Li and S. C. H. Hoi, “Online Portfolio Selection: A Survey,” vol. V, no. 212, 2012.
- M. Hoffman, E. Brochu, and N. De Freitas, “Portfolio Allocation for Bayesian Optimization,” Conf. Uncertain. Artif. Intell., pp. 327–336, 2011.
- W. Shen, J. Wang, Y. G. Jiang, and H. Zha, “Portfolio choices with orthogonal bandit learning,” IJCAI Int. Jt. Conf. Artif. Intell., vol. 2015–January, no. Ijcai, pp. 974–980, 2015.
- X. Huo and F. Fu, “Risk-Aware Multi-Armed Bandit Problem with Application to Portfolio Selection,” 2014.
- O. Bondarenko, “Statistical Arbitrage and Securities Prices,” Rev. Financ. Stud., vol. 16, no. 3, pp. 875–919, 2003.
- Q. Song, A. Liu, and S. Y. Yang, “Stock portfolio selection using learning-to-rank algorithms with news sentiment,” Neurocomputing, vol. 264, pp. 20–28, 2017.
- C. Xiao and W. Chen, “Trading the Twitter Sentiment with Reinforcement Learning,” vol. i, 2018.
- T. M. Cover, “Universal Portfolios,” vol. I, no. 1, p. 1, 1991.
- A. Blum and A. Kalai, “Universal portfolios with and without transaction costs,” Mach. Learn., vol. 35, no. 3, pp. 193–205, 1999.
- K. J. Oh, T. Y. Kim, and S. Min, “Using genetic algorithm to support portfolio optimization for index fund management,” Expert Syst. Appl., vol. 28, no. 2, pp. 371–379, 2005.