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Alan Oppenheim, MIT professor: "Every trader alive uses a moving average. Almost none of them know it's a filter, and funds pay quants $600K for the version they were never taught." a moving average is a filter. it smooths a jumpy price to reveal the slower signal hiding underneath....

214,907 Aufrufe • vor 21 Tagen •via X (Twitter)

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Terence Tao, UCLA professor and the most decorated mathematician alive: "Funds pay $750K to combine weak signals into one real edge. I proved the thing that makes it work and makes it dangerous: in any long enough sequence, hidden structure is unavoidable. it always accumulates. the whole job is telling the real structure from the noise that only looks like it." this free lecture is the most decorated mathematician alive on the exact problem sitting underneath every factor model, and it costs nothing. at the board it's simple. Tao's lifelong theme is the line between structure and randomness. The Erdős discrepancy problem asks a deceptively simple thing: can you write an endless string of plus-ones and minus-ones that stays perfectly balanced forever? Tao proved you cannot. No matter how cleverly you try, imbalance, hidden structure, is forced to accumulate as the sequence grows. There is no such thing as a long stream of pure, structureless noise. That's the whole idea, minus the jargon. Which is exactly why a multi-factor model can work, and exactly why it can kill you. Stack enough weak signals and real structure will appear, because at scale structure is unavoidable. But so will fake structure, patterns that exist only because the data is long enough to force them. Same point as the post above: finding structure is guaranteed. Knowing which structure is an edge is the rare and expensive part. the mathematics is free and public. what nobody can sell you is the judgment to tell the structure the market will pay you for from the structure that exists only because you looked hard enough. That judgment is the alpha, and it takes years to build.

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210,907 Aufrufe • vor 5 Tagen

Persi Diaconis, Stanford mathematician and former professional magician: "I spent fifty years proving one thing: almost nothing is as random as it looks. The 50.75% that built Renaissance wasn't luck. It was a tiny crack in the randomness, found and repeated a million times." this free lecture holds the exact idea the thread above is built on. and the man giving it isn't a trader. he's a stanford professor and former professional magician who spent his career on one question: where does real randomness end, and where does a hidden edge begin. here is his life's finding. a coin, a shuffle, a market, all look random, yet each hides a faint, measurable bias. on its own that bias is nothing, indistinguishable from luck. repeat it enough times and it stops being luck and becomes a law. that faint crack, found and repeated, is the whole distance between a 50.75% win rate and a hundred billion dollars. none of this is new or hidden. diaconis has taught it for decades, the math runs back to 1713, and the lecture is free. i mapped the full system in my article, expected value, kelly, and this. same point the thread makes: the edge was sitting in plain sight. here is the part the gurus skip. a faint edge only pays if you survive long enough to reach it, and that takes correct sizing and the patience to trust it through thousands of losing-looking trades. most quit while it still looks like randomness. the math is free. the nerve to hold it is the edge.

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229,785 Aufrufe • vor 24 Tagen

Marvin Minsky, the MIT scientist who founded AI: "Citadel pays PhDs $500K to find the perfect equation. The market doesn't have one. It's beaten by a swarm of dumb agents, the exact design Marvin Minsky said your brain runs on." the thread above is about swarm intelligence, letting a crowd of simple agents search the ugly, shifting landscape of a market that no clean equation can solve. minsky's entire life's work says that isn't a hack. it is how intelligence itself is built. he proved you don't need a smart central solver. you need many mindless specialists, each doing one tiny job, none understanding the whole. connect enough of them and something intelligent emerges from parts that are individually dumb. a market is exactly that: millions of simple agents, no one in charge, collectively solving a problem none of them can see. that is why the swarm beats the elegant math. a single closed-form equation assumes a clean, stable world. the market is nonlinear, non-stationary, full of traps. a swarm doesn't need to understand the landscape, it explores it from a thousand angles at once and can't get permanently stuck where one clever model would. minsky saw this in the mind decades before quants borrowed it for markets. he taught it at MIT, for free, in this lecture. same story i keep telling: the "new" AI idea running the funds is an old idea in a new wrapper. here is what the thread underplays, and minsky knew it. a swarm is only as good as how its agents are wired and rewarded. connect them wrong and a thousand dumb agents don't become a genius, they become expensive noise that overfits and blows up. the swarm is free. the architecture, knowing how to connect and constrain the agents, is the entire edge.

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45,129 Aufrufe • vor 13 Tagen

In 1963, Benoit Mandelbrot showed that cotton prices don't follow a bell curve. He showed it again with wheat, interest rates, stocks, and indices. Wall Street thanked him, gave him a medal, and kept using the bell curve. Every fund blowup since has been the invoice. Mandelbrot wasn't a Wall Street insider. He was a mathematician at IBM, an outsider the economics establishment spent 40 years trying to bury. Most of his career, mainstream finance journals wouldn't touch him. He was right anyway. The graveyard of blown-up funds keeps proving it. The thread above sells you a better filter. Mandelbrot spent his life on the assumption underneath every filter, the one every filter salesman needs you not to question. The assumption is that price moves cluster near the average and big moves are almost impossible. Every Sharpe ratio, every VaR, every risk model in every fund quietly runs on it. Mandelbrot proved for four decades, in papers Wall Street chose not to read, that real markets have fat tails, wild variance, and rough repeating patterns at every scale. The 10-sigma move isn't once in a hundred lifetimes. In markets, it shows up on a Tuesday. The self-similarity part is the tell. Take a crypto chart and cover the axis labels. You cannot tell if you're looking at a one-minute or a one-year timeframe. The roughness looks the same because the underlying process is the same. It does not average out at longer horizons. It just repeats. This is why every model that promises the tail is 1-in-10,000 blows up on schedule. LTCM died in 1998 and the industry called it once-a-millennium. 2008 repeated it a decade later. Crypto compresses the same lesson into weeks. 3AC, Luna, FTX, every leveraged desk that went to zero on a weekend was running on the bell curve Mandelbrot buried in 1963. The takeaway isn't that filters are useless. It's that no filter tells you how much to bet when it's right. Sizing is what survives the tail. The filter tells you where to look. Sizing decides whether you're still alive to look tomorrow. Build the filter. Build the swarm. Build the sharpest model of your generation. Just remember they're all fitting a world that doesn't exist, and the part that survives the tail, that part, you still have to bring yourself. His TED talk is from 2010. It's free. It was free in 1963 too.

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44,363 Aufrufe • vor 15 Tagen