کاربرد اختیارهای معامله در بازار مالی با استفاده از روش شبکه های عصبی
فصلنامه بورس اوراق بهادار

فصلنامه بورس اوراق بهادار

کاربرد اختیارهای معامله در بازار مالی با استفاده از روش شبکه های عصبی

نوع مقاله : مقاله پژوهشی

نویسنده
استادیار، گروه ریاضیات مالی، دانشکده علوم مالی، دانشگاه خوارزمی، تهران، ایران
چکیده
در بازار سرمایه ایران اوراق اختیار معامله فقط از نوع اروپایی خرید و فروش می‌گردد. در صورتی که در بازارهای جهانی، سایر اختیار معامله‌ها مثل اختیار آمریکایی، اختیار آسیایی، اختیار مانع، اختیار گذشته‌نگر و ... خرید و فروش می‌شوند. از آنجایی که اوراق اختیار معامله یک ابزار مناسب و پر استفاده برای پوشش ریسک است و خاصیت اهرمی نیز دارد لذا تنوع در بازار اوراق اختیار معامله، هم بازار مالی را گرم‌تر می‌کند و هم علاقمندان زیادی را به سمت خود جذب می‌کند. مدل‌های بسیاری زیادی برای ارزش‌گذاری اوراق اختیار معامله وجود دارد که مهم‌ترین آن مدل بلک-شولز کلاسیک است. اما این مدل به دلیل ضعف‌هایی که دارد از مدل‌های واقعی بازار دور است. بنابراین نیازمند به مدل‌های توسعه‌یافته است. مانند، مطالعه روی سری زمانی نشان می‌دهد که قیمت دارایی پایه با نوسانات آن رابطه عکس دارد. مدل الاستیسیته ثابت واریانس یک مدل مناسب برای نشان دادن این رابطه معکوس است. در این پژوهش، مدل الاستیسیته ثابت واریانس برای ارزش‌گذاری اوراق اختیار آمریکایی درنظر گرفته شده است که نوسان‌پذیری آن به صورت یک تابع از دو پارامتر الاستیسیته نوسان‌پذیری و مقیاس ثابت نوسان اولیه لحظه‌ای است. مطالعات نشان می‌دهد که روش‌های غیرپارامتریک مانند شبکه عصبی و ماشین یادگیری بهتر از سایر روش‌ها برای مدل‌سازی اقتصاد مناسب هستند. بنابراین در این پژوهش، از روش شبکه عصبی برای ارزش‌گذاری عددی اختیار معامله آمریکایی استفاده خواهد شد.
کلیدواژه‌ها
موضوعات

عنوان مقاله English

Application of options in the financial market using the neural networks method

نویسنده English

Maryam Rezaei
Assistant Professor, Department of Financial Mathematics, Faculty of Finance Sciences, Kharazmi University, Tehran, Iran
چکیده English

In Iran's capital market, only European-style options are bought and sold. In the case of global markets, other trading options such as American option, Asian option, barrier option, lookback option, etc. are bought and sold. Since warrants are a suitable and widely used tool for hedging risk and have leverage properties, diversity in the warrants market warms up the financial market and attracts many interested parties. There are many models for option pricing, the most important of which is the classic Black-Scholes model. But this model is far from the real market models due to its weaknesses. Therefore, it needs developed models. For example, the study of time series shows that the price of the underlying asset has an inverse relationship with its volatility. The constant elasticity of variance model is a suitable model to show this inverse relationship. In this research, the constant elasticity of variance model is considered for the valuation of American options, whose volatility is a function of two parameters of volatility elasticity and the scale parameter fixing the initial instantaneous volatility. Studies show that non-parametric methods such as neural network and machine learning are better suited for economic modeling than other methods. Therefore, in this research, the neural network method will be used for numerical valuation of American options.

کلیدواژه‌ها English

Learning solution
Neural networks
Option pricing
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