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Hamedinia, Hamed, Mohammadi Roudbari, Kiarash, Asadi, Behrang. (1403). Comparison of the portfolio optimization methods based on historical return approach and predicted return using ARIMA model. , (), -. doi: 10.22059/aie.2024.381585.1911
Hamed Hamedinia; Kiarash Mohammadi Roudbari; Behrang Asadi. "Comparison of the portfolio optimization methods based on historical return approach and predicted return using ARIMA model". , , , 1403, -. doi: 10.22059/aie.2024.381585.1911
Hamedinia, Hamed, Mohammadi Roudbari, Kiarash, Asadi, Behrang. (1403). 'Comparison of the portfolio optimization methods based on historical return approach and predicted return using ARIMA model', , (), pp. -. doi: 10.22059/aie.2024.381585.1911
Hamedinia, Hamed, Mohammadi Roudbari, Kiarash, Asadi, Behrang. Comparison of the portfolio optimization methods based on historical return approach and predicted return using ARIMA model. , 1403; (): -. doi: 10.22059/aie.2024.381585.1911

Comparison of the portfolio optimization methods based on historical return approach and predicted return using ARIMA model

Advances in Industrial Engineering
مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 28 مهر 1403
شناسه دیجیتال (DOI): 10.22059/aie.2024.381585.1911
نویسندگان
Hamed Hamedinia* 1؛ Kiarash Mohammadi Roudbari2؛ Behrang Asadi3
1University of Tehran - CEO at Algorithm Capital
2University of Amirkabir
3University of Tehran
چکیده
Risk assessment and the selection of an optimal portfolio selection are critical issues in financial research, investment firms, and among investors. Traditional optimization models like Mean-Variance, Value-at-Risk, Conditional Value-at-Risk, and Omega often rely on historical returns, which can be insufficient in optimizing return and reducing risk. Recently, Researches have used predictive return models in the optimization process. This study uses ARIMA model to predict stock returns alongside a mean-variance optimization model (ARIMA_MV) using Iranian exchange market data from 1395 to 1401. First, stock returns have been predicted using ARIMA model and error criteria such as MSE, MAD, HR, HR+ and HR- are estimated. The results show that Despite its simplicity, the ARIMA model has a relatively good performance in predicting the return of stock. Then, using the predicted return and the mean variance model, the optimal portfolio has been calculated in the sliding window process. The results show that portfolios calculated by ARIMA_MV model outperform the Tehran Exchange Index (TEDPIX), risk-adjusted criterion like Sharpe and Jensen's alpha ratios and mean_variance model with historical data (HMV). With the model developed in this project (ARIMA_MV), investment companies can offer shareholders higher returns and lower risks, potentially increasing company value in the capital market and boosting shareholder wealth.
کلیدواژه‌ها
ARIMA؛ Mean Variance؛ Portfolio Optimization؛ Historical Mean Variance
آمار
تعداد مشاهده مقاله: 45





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