<![CDATA[Investors aim to reduce risk and increase returns with an optimal portfolio. However, several challenges arise in portfolio construction. First, selecting assets can be difficult when there are many options, as traditional portfolio theories like risk parity and Markowitz theory only calculate optimal weights but do not automatically select assets. Second, these theories focus on covariances between stocks and overlook market data. Third, while the Sharpe ratio is used to evaluate investment performance, it does not account for risk when stock prices decline. To address these issues, this paper proposes a new approach to portfolio construction that focuses on sustainable trends. The k-means clustering technique is used to group assets, categorize them based on their characteristics, and calculate the Sharpe ratio to minimize the risk of price drops. This method also combines different approaches, including equal weighting, inverse volatility, risk parity, and Markowitz portfolio theory to optimize the portfolio.]]>
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