This analysis presents an exponentially weighted correlation matrix of 25 major stocks from various sectors, offering insights into their recent co-movement patterns. By sourcing daily historical prices from Yahoo Finance and focusing on adjusted closing prices, we prioritized data consistency. The exponentially weighted covariance matrix was computed using an optimal span determined by minimizing the L2 norm against recent data, a choice that emphasizes current market trends over historical averages. The resulting covariance matrix was then normalized to a correlation matrix by dividing each entry by the product of the exponentially weighted standard deviations for each stock, thereby retaining the focus on recent dynamics. This color-coded correlation matrix uses darker hues to indicate stronger correlations, positive or negative, revealing how stocks have recently interacted in response to market changes. Analysts can use this to identify pairs of stocks that move together for hedging strategies or diverge for diversification. By focusing on recent movements, this exponentially weighted approach allows investors to make more informed portfolio decisions based on up-to-date relationships among stocks, adapting to shifts in market conditions with greater agility.