Quantifying Funding Rumors: Signal-to-Noise Ratio in DeepSeek's Community Updates

Yesterday at 3 PM, I was running a multi-factor model when an abnormal pulse suddenly appeared in the "Institutional Research Heat" factor in my library—the social media spread volume of keywords from a top-tier private equity firm's meeting minutes spiked by 3.2 standard deviations within 15 minutes. I paused the backtest and took a look: DeepSeek investor exchange meeting minutes had leaked, with rumors claiming "financing obstacles" and "Liang Wenfeng's dissatisfaction." Anyone who has done quant trading knows that this kind of "news" is often just market noise. But noise itself is data, and it's worth analyzing its signal-to-noise ratio.