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TRADE BOT UNIVERSITY (BOTU22): TRADE BOT UNIVERSITY DAY 22 import math def rolling_scale_return(price_series, window): """ 5/8: Dynamic Analysis with Rolling Scale. Instead of full history, analyze log returns over short, medium, long windows. Use in moving average strategies applied to 's'. """ rolling_log_returns = [] if len(price_series) < window + 1: return [] for i in range(window, len(price_series)): # ln return from P_i-window to P_i ln_r_window = math.log(price_series[i] / price_series[i-window]) rolling_log_returns.append(ln_r_window) return rolling_log_returns # Bot ingesting minute-level price data # Short pump: Window of 5, Long pump: Window of 20 prices = [100, 101, 103, 110, 108, 115, 125, 130, 120, 110, 100] s_5 = rolling_scale_return(prices, 5) # Short-term momentum s_10 = rolling_scale_return(prices, 10) # Medium-term momentum # Pumping! Early s_5 > 0, signals a start of a potential pump. # Dump! Later s_5 turns negative quickly, signaling an exit. FIND OTHER LESSONS ON SCALE CALCULUS: F4D5iQUoA67qkB4KCsbECoaxhhUtVcCy9ZzK3tjHAZru JgKkpaVMse7nhhJt7kwr7B2R4xS7JASgkTS2FGPpump 5YQFcsxuoSSFa2nMBSvWgMBPUVywtm76X919RF6Tpump dGr7yvu7GBTGMs22eZMrM2biMEXZETviFzATnNvpump E5AZ2ntCwnzeW2RZKnEmE8Ko5nQfEhAk5T47s3fApump HnLT6rJnJymm8KmDuPcnnYDedEPwa29GSjmvLhe9pump 6i1mNEmafKhTGrNjPv9L14q75bQuYZAGP3zSfBygpump BpqsvmWEZRSwrAptrrdzBtGGhVLen6Byz6BLH9iTpump Dzkcf3q4u3L7P81zbeZbTAU3kFvMekNrRmsSgt5Zpump BpqsvmWEZRSwrAptrrdzBtGGhVLen6Byz6BLH9iTpump 7oyovJGs2VjU13aqdXdSa3vYVEPH3bc8uQF4aRR4pump 6UrxCvSJcKQi7hM39axYEvhoGy8YxyZfUFRqHubApump DUABnYJk1ab76Cn7FSH9jfHXCsiZSFiZjpZxTCR3pump 6wQhEVmjB2WzbxtNKJBfSQqCgTiJ5bvou83aUzGHpump BOX SET COMPLETION: Gkc1swosS1wRmB88TfmRP5HjdVLY3HK5kNdna3dtpump
