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TRADE BOT UNIVERSITY (BOTU21): TRADE BOT UNIVERSITY DAY 21 Python import math import statistics def scale_reversion_signal(log_returns, mean_log_return, std_log_return): """ 4/8: The bot edge. Mean Reversion of Log Returns. Log returns are often normally distributed. If current 's' is significantly far from the historical mean, a reversion is expected. """ current_ln_r = log_returns[-1] # Standard deviation score (Z-Score) of current ln return z_score = (current_ln_r - mean_log_return) / std_log_return # Heuristic: s > 2*std -> Overextended pump, sell. # Heuristic: s < -2*std -> Overextended dump, buy (if faith remains). if z_score > 2.0: signal = "🛡️ SELL: Overextended Pump" elif z_score < -2.0: signal = "🚀 BUY: Scale Reversion Opportunity" else: signal = "🛡️ HODL" return signal # Example data log_returns_hist = [0.05, -0.01, 0.10, -0.05, 0.15, -0.10, 0.30] # High volatility mean_ln = statistics.mean(log_returns_hist) std_ln = statistics.stdev(log_returns_hist) # Bot ingests latest log return: 0.70 (MASSIVE PUMP) current_z = (0.70 - mean_ln) / std_ln # Check Z-Score current_signal = scale_reversion_signal([0.70], mean_ln, std_ln) # Signal will be to SELL, detecting convexity anomaly. FIND OTHER LESSONS ON SCALE CALCULUS: F4D5iQUoA67qkB4KCsbECoaxhhUtVcCy9ZzK3tjHAZru JgKkpaVMse7nhhJt7kwr7B2R4xS7JASgkTS2FGPpump 5YQFcsxuoSSFa2nMBSvWgMBPUVywtm76X919RF6Tpump dGr7yvu7GBTGMs22eZMrM2biMEXZETviFzATnNvpump E5AZ2ntCwnzeW2RZKnEmE8Ko5nQfEhAk5T47s3fApump HnLT6rJnJymm8KmDuPcnnYDedEPwa29GSjmvLhe9pump 6i1mNEmafKhTGrNjPv9L14q75bQuYZAGP3zSfBygpump BpqsvmWEZRSwrAptrrdzBtGGhVLen6Byz6BLH9iTpump Dzkcf3q4u3L7P81zbeZbTAU3kFvMekNrRmsSgt5Zpump BpqsvmWEZRSwrAptrrdzBtGGhVLen6Byz6BLH9iTpump 7oyovJGs2VjU13aqdXdSa3vYVEPH3bc8uQF4aRR4pump 6UrxCvSJcKQi7hM39axYEvhoGy8YxyZfUFRqHubApump DUABnYJk1ab76Cn7FSH9jfHXCsiZSFiZjpZxTCR3pump
