The latest articles on DEV Community by akshay-bhatnagar-05 (@akshaybhatnagar05). https://dev.to/akshaybhatnagar05 https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F4072394%2F7c8051ce-5c94-4bf6-8882-2caf44b78b26.png https://dev.to/akshaybhatnagar05 en akshay-bhatnagar-05 Tue, 11 Aug 2026 06:04:15 +0000 https://dev.to/akshaybhatnagar05/i-built-an-automated-system-that-tracks-presidential-stock-mentions-and-follows-the-price-for-4-days-3ohi https://dev.to/akshaybhatnagar05/i-built-an-automated-system-that-tracks-presidential-stock-mentions-and-follows-the-price-for-4-days-3ohi <p>Ever notice how a single offhand comment from a public figure can move a stock within hours? I wanted to actually track that — not just react to headlines after the fact, but systematically catch mentions and see what happens to the price next.</p> <p>So I built <strong>Wire Desk</strong>: a small automated pipeline that watches for statements referencing specific companies or sectors, classifies them as <em>direct</em> (his own words, via Truth Social/White House) vs. <em>indirect</em> (news coverage reporting on him), then follows the stock's price for four trading days so I can judge the reaction myself instead of trusting a headline.</p> <p>🔗 <strong>Live site:</strong> <a href="https://akshay-bhatnagar-05.github.io/trump-stock-tracker/" rel="noopener noreferrer">https://akshay-bhatnagar-05.github.io/trump-stock-tracker/</a><br> 🔗 <strong>Source:</strong> <a href="https://github.com/akshay-bhatnagar-05/trump-stock-tracker" rel="noopener noreferrer">https://github.com/akshay-bhatnagar-05/trump-stock-tracker</a></p> <h2> How it works </h2> <ol> <li> <strong>Three sources monitored daily</strong> — Truth Social (via an RSS mirror), official White House press releases, and news wires via NewsAPI</li> <li> <strong>Keyword matching</strong> against a watchlist of companies/tickers I care about</li> <li> <strong>Direct vs. indirect tagging</strong> — this turned out to be the most useful design decision. A statement <em>from</em> someone carries very different weight than a journalist writing <em>about</em> them, and treating those the same was the biggest flaw I noticed in similar tools</li> <li> <strong>4-day price tracking</strong> via yfinance, so I can see the actual before/after reaction instead of just the headline</li> <li> <strong>Daily email digest + a live dashboard</strong>, fully automated via GitHub Actions — the whole thing runs on a schedule with zero manual steps</li> </ol> <h2> The stack </h2> <ul> <li>Python (requests, yfinance, feedparser) for the detection/tracking logic</li> <li>GitHub Actions for the daily cron job</li> <li>A static HTML/CSS/JS dashboard, reading from a JSON file the script regenerates every run</li> <li>GitHub Pages for hosting — the whole thing costs $0 to run</li> </ul> <h2> What I deliberately avoided </h2> <p>While researching this, I found an open-source project that brute-forced <strong>31.5 million rule combinations</strong> against historical posting data to find a "61.3% hit rate." Their own README honestly flags the risk: testing that many combinations basically guarantees some will look great by pure chance (the classic multiple-comparisons/data-snooping problem). I wanted the opposite — simple, explainable logic over a big number that might just be noise.</p> <h2> Honest caveats </h2> <p>This is a research/awareness tool, not a trading signal. By the time a mention is caught here, it's already public, and a "confirmed" multi-day trend is usually already priced in. It's useful for staying informed fast — not for predicting anything.</p> <p>Would love feedback on the architecture, or if anyone's built something similar with different source coverage. Repo's open, feel free to fork it.</p> <p><em>Tags: #python #githubactions #webdev #opensource #finance</em></p> automation github python