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Machine Learning for Portfolio Optimization by kritparey.chottaker.1458 is a document available to read on EtoBox.
This research explores portfolio construction using financial ratio indicators and machine learning classification methods to optimize investment returns. It demonstrates that portfolios created based on financial ratios can outperform randomly allocated portfolios by analyzing metrics such as the Sharpe ratio and portfolio performance. The study employs K Means Clustering and K Nearest Neighbor algorithms to identify and select investable assets, ultimately aiming to enhance investment decision-making for
- Author
- kritparey.chottaker.1458
- Language
- EN