This is a summary of links recently featured on Quantocracy as of Tuesday, 08/11/2026. To see our most recent links, visit the Quant Mashup. Read on readers!
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Autopsy No.003: Buying options for the big win [Morgue Labs]The pitch One screenshot: $6k into weekly calls, $1.2M out. The logic sounds like physics options have capped downside and uncapped upside, so keep buying cheap lottery tickets and one asymmetric win pays for everything. The post-2021 refinement adds a mechanism: find the gamma squeeze, ride the dealers' forced hedging, be the flywheel instead of the fuel. The test Twenty years of S&P
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Does AI Still Read the News Better Than the Market? [Tommi Johnsen]A well-known finance paper showed that an AI model could read a news headline about a company and say, better than chance, which way the stock would move. The same paper predicted the effect would fade as more traders started using the same tools. Thanks for reading! Subscribe for free to receive new posts and support my work. We tested that prediction with 2026 data, a different AI model, and
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Stop Using Pairwise Granger: PCMCI for Financial Causality [Aligrithm]Run pairwise Granger tests over a basket of thirty instruments and you get a causal network that looks like a plate of spaghetti. AUD/USD drives copper, copper drives the Aussie back, oil leads the loonie, the loonie leads oil, and somewhere in the mess a small-cap ETF appears to Granger-cause the ten-year yield. Most of those arrows are fake. They come from three things markets are drowning in:
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Excessively Volatile? Or Inexplicably Precise? [Alex Chinco]The dividend discount model (DDM) says that a stocks current price ought to reflect the discounted value of its expected future dividend stream (1) begin{equation*}mathrm{Price} = sum_{t=1}^{infty} frac{mathbb{E}[mathrm{Div}_{t}]}{(1{+}r)^t}end{equation*} mathbb{E}[mathrm{Div}_t] is the companys expected dividend in t years, and r > 0% is the firms discount rate. The Gordon