001 def today_radar(df: DataFrame, model) -> Signal | None:
002 X = build_features(df) # ret_1..ret_60, vol_ratio_5_20
003 p_up_5, p_up_10 = model.predict_proba(X)
004 score = 0.5 * p_up_5 + 0.5 * p_up_10 # 5G/10G mutlak yükseliş
005 conf = band_calibrate(score, prior) # geçmiş gerçek isabetle
006 if history_days < 30 or turnover_ma20 < MIN_LIQ:
007 return None # veri/likidite kapısı
008 return Signal(symbol, score, conf, reason, risk)
009
010 FEATURES = [ret_1, ret_3, ret_5, ret_10, ret_20, ret_60,
011 vol_ratio_2_20, vol_ratio_5_20, volatility_20,
012 sma20_gap, sma50_gap, drawdown_252, rsi_14,
013 macd_hist, obv_slope, seasonality_mean]
014
015 model = HistGradientBoostingClassifier(max_depth=None)
016 cv = walk_forward_splits(df, embargo=10) # sızıntısız doğrulama
017 assert backtest(model, cv).passed # güvenlik kapısı
018 snapshot.upsert(radar_rows, on='data_date,symbol')
019 evaluate_outcomes(as_of=today) # 5/10/20/40 iş günü
020 broadcast_telegram(strong_candidates)
021 def today_radar(df: DataFrame, model) -> Signal | None:
022 X = build_features(df) # ret_1..ret_60, vol_ratio_5_20
023 p_up_5, p_up_10 = model.predict_proba(X)
024 score = 0.5 * p_up_5 + 0.5 * p_up_10 # 5G/10G mutlak yükseliş
025 conf = band_calibrate(score, prior) # geçmiş gerçek isabetle
026 if history_days < 30 or turnover_ma20 < MIN_LIQ:
027 return None # veri/likidite kapısı
028 return Signal(symbol, score, conf, reason, risk)
029
030 FEATURES = [ret_1, ret_3, ret_5, ret_10, ret_20, ret_60,
031 vol_ratio_2_20, vol_ratio_5_20, volatility_20,
032 sma20_gap, sma50_gap, drawdown_252, rsi_14,
033 macd_hist, obv_slope, seasonality_mean]
034
035 model = HistGradientBoostingClassifier(max_depth=None)
036 cv = walk_forward_splits(df, embargo=10) # sızıntısız doğrulama
037 assert backtest(model, cv).passed # güvenlik kapısı
038 snapshot.upsert(radar_rows, on='data_date,symbol')
039 evaluate_outcomes(as_of=today) # 5/10/20/40 iş günü
040 broadcast_telegram(strong_candidates)
