首页|Data from University of Southampton Broaden Understanding of Machine Learning (I ntegrating LSTM Networks with Mean- Variance Optimization for Enhanced Portfolio Construction: An Empirical Study on UK Stock Market)
Data from University of Southampton Broaden Understanding of Machine Learning (I ntegrating LSTM Networks with Mean- Variance Optimization for Enhanced Portfolio Construction: An Empirical Study on UK Stock Market)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in artificial intelligence. According to news originating from Southampton, United Kingdom, by NewsRx correspondents, research stated, “Portfolio optimization has long been a central theme in finance.” Our news reporters obtained a quote from the research from University of Southam pton: “With ongoing advancements in machine learning, there is a significant opp ortunity to integrate predictive methods into portfolio optimization. This paper proposes leveraging Long Short-Term Memory (LSTM) networks alongside the establ ished Mean-Variance (MV) optimization framework to construct optimal portfolios. These portfolios aim to help financial investors effectively manage and mitigat e risk while maximizing returns. The study meticulously screened the leading sto cks of 12 prominent UK companies listed on the London Stock Exchange (LSE), know n for their influence and visibility. Initially, the study applies the LSTM netw orks to predict stock price volatility and integrates these predictions into the MV model to allocate portfolio weights effectively. To underscore the superiori ty of the proposed approach, the study compares cumulative returns from portfoli os optimized for maximum and minimum variance Sharpe ratios with real data again st the FTSE100 index over the same period.”
University of SouthamptonSouthamptonUnited KingdomEuropeCyborgsEmerging TechnologiesFinance and InvestmentInvestment and FinanceMachine Learning
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