Robert Engle points out that hedge funds on Wall Street shell out between \$650,000 and \$950,000 a year for quant researchers who can tell the difference between mere correlation and true cointegration. Correlated prices drift apart over time, but cointegrated pairs share a long-run equilibrium and reliably snap back together. Engle won the Nobel Prize in 2003 for the Engle-Granger cointegration test he first published in 1987, and he’s now offering a free lecture on exactly how to spot these anchored relationships. He traces the whole setup back to public, decades-old econometric tools: the Engle-Granger step, the Johansen test, Ornstein–Uhlenbeck spreads, Kalman hedge ratios. None of it is secret. What pays the big bucks isn’t knowing the tests exist—it’s picking pairs that remain cointegrated as markets shift, and then rigorously monitoring them. That means rerunning tests, factoring in trading costs, and standing aside when the p-values drift into meaningless territory. Engle makes one blunt point: the easy edge is gone. Anyone can download R or Python packages and run the same cointegration tests. What still works is unglamorous: daily discipline. You need systems that flag when relationships break down, models that adjust for execution slippage, and the operational backbone to pull the plug when warning signs pop up. Few firms build that muscle. But that’s exactly the skill set commanding the highest salaries in quant land.