Why did you guess the macro data correctly but still not make money? In the past, whenever there was a non-farm payroll, CPI, or interest rate decision, I always tried to guess the outcome in advance: weak data meant going long; strong data meant going short. But after losing more and more, I realized the market isn’t trading the data itself—it’s trading the difference between the data and expectations. A cooling labor market seems bullish for easing, but if the market has already priced that in, the actual release could trigger profit-taking. Strong data should suppress risk assets, yet if it’s not as strong as expected, BTC might still rise. Even more problematic: at the moment of data release, liquidity dries up, and price often sweeps long positions first, then short positions—you might end up right on direction, but your position is already liquidated. I used to open high-leverage trades before major data releases, convinced my logic was flawless—only for the price to spike sharply right after the number dropped, hitting my stop-loss before moving in the direction I anticipated. That’s when I finally understood: being right about the outlook doesn’t mean your trade structure is sound. Before major data releases, what truly matters isn’t just the outcome—it’s how much has already been priced in, how crowded the positions are, and whether you can withstand sudden volatility. When the risk-reward isn’t clear, waiting for the market to complete its first reaction is often more valuable than trying to catch those first few seconds. Remember: data tells the story, but the expectation gap determines price direction. Guessing the number is knowledge; surviving the volatility is trading.