ارتقاي سطح كارائي مديريت سرمايه گذاري دربازارسرمايه ايران با استفاده ازشبكه عصبي مصنوعي و منطق فازي

Promotion of Effective Level of Investment Management in Iran Capital Market using Artificial Neural Network and Fuzzy Logic

تخصيص بهينه منابع مالي يكي ازمهمترين مسا ئل بازار سرمايه است. در يك بازار سرمايه كارا از بعد عملياتي ،سرمايه در اختيار بهترين گزينه هاي سرمايه گذاري قرار ميگيرد. بنابراين استفاده ازابزارهاي مديريت مناسب جهت كسب بازدهي بيشتر،گامي در راستاي كاراترشدن مديريت معاملات بازاراست. با توجه به زمينه هاي استفاده از شبكه هاي عصبي و منطق فازي در سرمايه گذاري سهام و پيش بيني مالي ،بكارگيري آنها در انتخاب پر تفوي مناسب مي تواند نتايج مطلوبي براي سرمايه گذاران در پي داشته باشد.هدف اصلي اين پژوهش دستيابي به پرتفوي سرمايه گذاري بهينه دربازارسرمايه بابكارگيري شبكه عصبي مصنوعي ومنطق فازي است. همراه با مدل ماركويتز،از مدلهاي ايجادشده طريق شبكه عصبي مصنوعي ومدل فازي استفاده گرديد.از شركتهاي فعال در بورس اوراق بهادارتهران، كه از سال 1386الي 1395 داراي بازده مثبت بوده اند براي تشكيل پرتفوي سرمايه گذاري انتخاب شدند.براي ارزيابي پرتفو هاي پيشنهادي در حالت هاي مختلف، به مقايسه بازده پرتفو هاي مختلف بر اساس بازده ماهيانه وساليانه شركت هاي عضووبهينه سازي پرتفوهاي پيشنهادي بااستفاده ازالگوريتم ژنتيك پرداخته شده است. اين تحقيق نشان ميدهدكه استفاده ازمدلهاي فازي نسبت به مدلهاي مذكوربازدهي بالاتري رابراي سرمايه گذاران فراهم مي نمايد.

One of the most important problems in capital market is allocating financial resources in an optimal fashion. In an effective capital market, from an operational point of view, the capital is allocated for the best investment option. Therefore, in order to establish more output, making use of appropriate management tools is a step toward more effective market management of transactions. Regarding backgrounds of applying Artificial Neural Networks and Fuzzy Logic in stocks investment and financial prediction, applying them in selecting an appropriate portfolio can lead to desired results for investors. The major goal of the current research is to achieve an optimal investment portfolio in capital market by applying Artificial Neural Network and Fuzzy Logic. Accompanied by Markowitz Model, models were used which were created through Artificial Neural Network. In order to establish investment portfolio, some of those companies were selected which were active in Tehran stock exchange, and which have had positive efficiency from the year 1386 to 1395. In order to evaluate the suggested portfolios in different conditions, the output of different portfolios based on the monthly and yearly output of the member companies were compared and optimization of suggested portfolios using genetic algorithm were carried out. The study shows that using the Fuzzy models versus mentioned models would provide higher output for the investors.