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Di Krass

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math · quant · markets · AI the edge hides where nobody's looking.

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Wall Street doesn't predict prices - it prices the randomness in them. That is where the billions are, and it runs on one equation. The model trading desks actually use is Geometric Brownian Motion: dS = μS·dt + σS·dW μ (drift) is the slow expected trend. σ·dW is the random shock - a coin flip scaled by volatility. It is the engine under Black-Scholes, the formula that prices trillions in options. The idea is 125 years old. Louis Bachelier modeled prices as a random walk in 1900 - five years before Einstein used the same math for particles. His verdict: "the mathematical expectation of the speculator is zero." Sixty years later Eugene Fama won a Nobel for the same finding: prices are "no more predictable than the path of a series of cumulated random numbers." And the math is brutal. Drift grows with time (t); noise grows only with its square root (√t). Over one day the shock buries the trend - so daily direction is a coin flip, and traders invent reasons after the candle prints. The trap hides in one assumption: that returns are "normal." Real markets have fat tails. Black Monday 1987 (-22.6% in a day) was a 20-sigma event under the bell curve - impossible in billions of years. Nassim Taleb calls that bell curve "the great intellectual fraud." The equation that prices everything is blind to the one day it matters most. the edge was never the trend inside the wiggle. it is knowing how much of the wiggle is nothing. the full quant build is in the article below.

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