Is this a unique feature?

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Is your feature request related to a problem/unavailable functionality? Please describe.

A stock recommendation model using Machine Learning analyzes an investor's portfolio to suggest stocks with similar characteristics but different specific offerings. It examines patterns in the investor's current holdings, such as industry sectors, market trends, and stock performance metrics. By leveraging algorithms like clustering, regression, and collaborative filtering, the model identifies alternative stocks that align with the investor's preferences while offering diversification opportunities. This approach helps investors discover new stocks that fit their risk tolerance and investment goals while maintaining a balanced portfolio, ultimately enhancing their potential for returns through more informed investment decisions

Proposed Solution

The proposed solution for a stock recommendation model using Machine Learning involves analyzing an investor's existing portfolio to suggest similar yet diverse stocks. It begins by collecting data on stock performance, historical trends, and financial metrics. By employing algorithms like K-means clustering for grouping similar stocks and collaborative filtering to identify relevant alternatives, the model can recommend stocks that align with the investor's preferences while promoting diversification. This approach enhances investment decisions by helping investors discover new opportunities that fit their risk tolerance and financial goals.

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If "yes" to above, please explain how you would technically implement this (issue will not be assigned if this is skipped)

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