Financial Asset Allocation and Portfolio Optimization Strategies Based on Stochastic Optimization Methods

[1] Qin, Y., Zhong, Y., Lei, Z., Peng, H., Zhou, F., & Tan, P. (2020). A hybrid parameter estimation for multi-asset modeling and dynamic allocation based on financial market microstructure model. International Journal on Artificial Intelligence Tools. Search in Google Scholar

[2] Tayal, S. T. (2020). A novel backtesting methodology for clustering in mean–variance portfolio optimization. Knowledge-Based Systems, 209, 106454. Search in Google Scholar

[3] Fons, E., Dawson, P., Yau, J., Zeng, X. J., & Keane, J. (2020). A novel dynamic asset allocation system using feature saliency hidden markov models for smart beta investing. Expert Systems with Applications, 163, 113720. Search in Google Scholar

[4] Hashemkhani, Z. S., Mehtari, T. H., Gharehgozlou, M., & Farahani, A. (2022). An asymmetric promethee ii for cryptocurrency portfolio allocation based on return prediction. Applied Soft Computing. Search in Google Scholar

[5] Sharma, A., & Mehra, A. (2017). Financial analysis based sectoral portfolio optimization under second order stochastic dominance. Annals of operations research (1), 256. Search in Google Scholar

[6] Harris, Richard, D., F., Stoja, & Evarist, et al. (2017). The dynamic black-litterman approach to asset allocation. European Journal of Operational Research. Search in Google Scholar

[7] Jan Obój, & Wiesel, J. (2021). Distributionally robust portfolio maximization and marginal utility pricing in one period financial markets. Mathematical Finance. Search in Google Scholar

[8] Soleymani, F., & Paquet, E. (2020). Financial portfolio optimization with online deep reinforcement learning and restricted stacked autoencoder - deepbreath. Expert Systems with Applications, 156, 113456. Search in Google Scholar

[9] Mulvey, John M.Sun, YifanWang, MengdiYe, Jing. (2020). Optimizing a portfolio of mean-reverting assets with transaction costs via a feedforward neural network. Quantitative finance, 20(8). Search in Google Scholar

[10] Josa-Fombellida, R., Lopez-Casado, P., & Pablo Rincon-Zapatero, J. (2018). Portfolio optimization in a defined benefit pension plan where the risky assets are processes with constant elasticity of variance. Insurance: Mathematics and Economics, 82(SEP.), 73-86. Search in Google Scholar

[11] Almahdi, S., & Yang, S. Y. (2017). An adaptive portfolio trading system: a risk-return portfolio optimization using recurrent reinforcement learning with expected maximum drawdown. Expert Systems with Applications, 87(nov.), 267-279. Search in Google Scholar