Abstract
Статья посвящена разработке и количественному обоснованию торговой стратегии, основанной на решении задачи регрессии по историческим данным, на примере цен акций коммерческого банка. С помощью языка программирования Python определена спецификация модели и проведено ее обучение. Расчеты показали эффективность торговой стратегии, основанной на открытии длинной или короткой позиции в зависимости от прогнозируемой динамики доходности, по сравнению со стратегией, предполагающей удержанием длинной позиции. The article is devoted to the development and quantitative justification of a trading strategy based on solving a regression problem based on historical data, using the example of commercial bank share prices. Using the Python programming language, the specification of the model was determined and it was trained. Calculations have shown the effectiveness of a trading strategy based on opening a long or short position depending on the predicted dynamics of profitability, compared to a strategy involving holding a long position.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callSimilar Papers
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
