Yeah, I’ve been tracking that. The bots are exploiting micro‑scale inefficiencies, so the usual volatility clustering is getting smoothed out. In statistical terms, the distribution is shifting from a fat‑tailed lognormal to something closer to a normal distribution, but with occasional heavy tails when a bot hit a liquidity choke point. That means your traditional VaR models might underestimate risk if you keep using old parameters. Adjust the volatility forecast to a rolling window that captures the bot‑induced mean reversion, and you’ll get a cleaner signal.