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The investment industry is experiencing a significant transformation driven by technological advancements, particularly machine learning (ML). Asset managers are increasingly integrating ML algorithms into portfolio optimization processes to achieve higher returns while managing risk more effectively. This shift necessitates that investors understand the implications of these algorithms on their portfolios.
Machine learning offers innovative solutions to traditional portfolio optimization challenges, such as mean-variance optimization (MVO). By utilizing advanced techniques like artificial neural networks and LASSO models, investment professionals can create more efficient portfolios that account for complexities in data and investor expectations. As these methods gain traction, investors must stay informed to navigate the evolving landscape.
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