I kept thinking about how a stop-loss can protect a trader financially while revealing something about their behaviour. Every exit level tells a story: where someone admits they were wrong, how much risk they can tolerate, and when they might be forced out. That doesn’t mean every stop hunt is intentional, but predictable decisions can become useful information in a competitive market. That’s what drew me to Nillion. Its encrypted-computation approach explores how data can be processed without revealing the underlying information. The interesting possibility is whether sensitive trading conditions could remain private without sacrificing reliable execution. Still, privacy isn’t an edge by itself. A poor entry remains poor, and added complexity has to justify its cost. What interests me most is the shift in thinking: traders spend so much time predicting the market, yet rarely ask how much of their own strategy they reveal to it. Could keeping that information private become just as important as finding the right entry?
#nil $NIL @Nillion