سيدعلي موسوي لولتي

Investing in the stock market plays a fundamental role in economic growth and development, as it enables the creation of investment opportunities, provides companies and governments with financial resources, and stimulates economic activity. Constructing a suitable portfolio for stock market activities is of great importance and requires skill in selecting and combining different stocks to achieve desirable performance and better returns. In addition, information about future market conditions plays a crucial role in determining capital management strategies. Accurately analyzing and forecasting future market conditions can help investors take risks when the market is expected to outperform and pursue high-return, higher-risk market opportunities. Conversely, it seems logical to take a risk-averse approach when information points to unfavorable market conditions. The aim of this study is therefore to construct a portfolio that takes future market conditions into account. The use of stock market indices is very effective in analyzing and forecasting future market conditions. These important tools help us understand the direction and trend of the market and identify significant changes. The industry stock market indices serve as representatives of the industries under consideration and enable investors to examine market fluctuations and trends and accurately assess the state of the industry. Accordingly, this study presents a novel approach that focuses on establishing a relationship with the forecast of the industry stock market indices and optimizing the models. Ultimately, this leads to the creation of an optimal participation pattern of the industry portfolio in different forecast scenarios. To eva‎luate the efficiency of the proposed approach, this study also used seasonal data from several stocks in the cement and chemical industries, covering the period from the beginning of summer 2013 to the end of autumn 2023. For validation, the results of this approach were compared with variance, semi variance, standard deviation, and evenly weighted portfolio models. The results show that the proposed approach is superior to competing models and provides better performance.

بهينه‌سازي سبد سرمايه‌گذاري , انتخاب سبد سرمايه‌گذاري , شاخص بورس , پيش‌بيني , بورس اوراق‌بهادار تهران

Portfolio Optimization , Portfolio selection , Stock Market Index , Forecasting , Tehran Stock Exchange

Seyed Ali Mousavi Loleti

Emran Mohammadi