K-Means is a clustering algorithm used to group data into homogeneous groups based on similarities. In the context of market trends, the K-Means algorithm can be applied to identify groups of financial assets that exhibit similar behavior in terms of price, volatility or other indicators.
A common application of K-Means in market trends is investment portfolio analysis. By applying the K-Means algorithm to a historical data set of financial asset prices, investors can identify groups of assets that tend to move together in the market. This can help investors diversify their portfolios more effectively and make informed investment decisions based on trends identified by the K-Means algorithm.
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