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- Title
Optimal Daily Scalping Stock Trading Portfolio Based on Interval-Valued Prediction with ANN Approach.
- Authors
Sarvestani, Sajjad Soleimani; Reza Davoodi, Sayyed Mohammad; kheradmand, Ali
- Abstract
In the present study, using the method of neural networks, the interval related to the lowest and highest daily prices is predicted and, then based on it, a daily scalping trading system is formed, including buying and selling in the forecasted amounts. To reduce the risk of the trading system and increase the number of trading positions, the optimal daily scalping trading portfolio is developed in the mean-variance framework. The sample portfolio includes five shares of the Tehran Stock Exchange in 190-day period, taking into account trading costs, shows that the average daily return is 0.0028 and the Sharpe ratio is 0.6379, which is better than the Sharpe ratio of individual daily scalping trading of portfolio assets. The daily average of the total index in the research period is 0.0014 and the Sharp ratio is 0.0749, which shows that the trading system has a much better performance than the buy-hold strategy in equal-weighted portfolio.
- Publication
Financial Management Perspective / Chashm/&āz-i Mudīriyyat-i Mālī, 2022, Vol 12, Issue 39, p103
- ISSN
2645-4637
- Publication type
Article
- DOI
10.52547/JFMP.12.39.103