Arena run #437

You are an Arena strategy executor. You must follow the strategy rules strictly and output ONLY valid JSON. You are NOT allowed to invent prices, fundamentals, earnings dates, or sentiment. If a field is null/empty, treat it as unknown. You are a constrained selector (no narrative).

{"task": "stage1_universe_scan", "region": "US", "strategy": {"key": "meanrev-v1", "name": "Two-Stage LLM Mean-Reversion (Arena v1)", "rules": {"max_positions": 10, "max_buys_per_run": 2, "avoid_overtrading": true, "max_sells_per_run": 2, "max_gross_leverage": 3.0, "fixed_position_size": 3000.0, "universe_symbols_eu": [], "universe_symbols_us": []}}, "selection_rules": {"horizon": "2-10 trading days", "target": "short-term mean reversion in liquid equities", "constraints": ["Select exactly 5 candidates", "Avoid earnings within 5 trading days (if known)", "Avoid highly binary/event-driven moves (if known)", "Avoid sector concentration: max 1 per sector unless clearly justified (sector may be unknown)"]}, "universe": [{"symbol": "PAGE_CFD.UK", "name": "PAGEGROUP PLC", "sector": "", "last_price": 205.8, "change_1d_pct": -13.091216216216218, "distance_from_ma200_pct": -20.507377691735872, "distance_from_ma50_pct": -9.456474873951793, "volatility_20d_pct": 113.15149478988747, "market_cap_usd": null, "avg_daily_volume_usd": null, "days_to_next_earnings": null, "earnings_confirmed": null, "news_sentiment_score": null, "news_headlines_last_3": [], "data_quality_note": "snapshot_ok_prices_technicals_only"}, {"symbol": "MCG_CFD.UK", "name": "MOBICO GROUP PLC", "sector": "", "last_price": 30.54, "change_1d_pct": 21.867517956903427, "distance_from_ma200_pct": 10.17176911546931, "distance_from_ma50_pct": 28.667486813057195, "volatility_20d_pct": 211.42235702559637, "market_cap_usd": null, "avg_daily_volume_usd": null, "days_to_next_earnings": null, "earnings_confirmed": null, "news_sentiment_score": null, "news_headlines_last_3": [], "data_quality_note": "snapshot_ok_prices_technicals_only"}, {"symbol": "UTG_CFD.UK", "name": "UNITE GROUP PLC/THE", "sector": "", "last_price": 567.5, "change_1d_pct": 3.4639927073837784, "distance_from_ma200_pct": -23.929923575376698, "distance_from_ma50_pct": -3.6875042216270137, "volatility_20d_pct": 73.84223442053181, "market_cap_usd": null, "avg_daily_volume_usd": null, "days_to_next_earnings": null, "earnings_confirmed": null, "news_sentiment_score": null, "news_headlines_last_3": [], "data_quality_note": "snapshot_ok_prices_technicals_only"}, {"symbol": "TRN_CFD.UK", "name": "TRAINLINE PLC", "sector": "", "last_price": 206.0, "change_1d_pct": -12.93322062552832, "distance_from_ma200_pct": -22.557701091522887, "distance_from_ma50_pct": -12.560104316644482, "volatility_20d_pct": 131.09279103846345, "market_cap_usd": null, "avg_daily_volume_usd": null, "days_to_next_earnings": null, "earnings_confirmed": null, "news_sentiment_score": null, "news_headlines_last_3": [], "data_quality_note": "snapshot_ok_prices_technicals_only"}, {"symbol": "DLN_CFD.UK", "name": "DERWENT LONDON PLC", "sector": "", "last_price": 1953.0, "change_1d_pct": 10.401356698699837, "distance_from_ma200_pct": 5.069478604951705, "distance_from_ma50_pct": 12.150447212111025, "volatility_20d_pct": 115.39088732649292, "market_cap_usd": null, "avg_daily_volume_usd": null, "days_to_next_earnings": null, "earnings_confirmed": null, "news_sentiment_score": null, "news_headlines_last_3": [], "data_quality_note": "snapshot_ok_prices_technicals_only"}, {"symbol": "STAN_CFD.UK", "name": "", "sector": "", "last_price": 1842.0, "change_1d_pct": 0.3541269408880332, "distance_from_ma200_pct": 31.43986196388351, "distance_from_ma50_pct": 4.292113036344269, "volatility_20d_pct": 75.84142956557304, "market_cap_usd": null, "avg_daily_volume_usd": null, "days_to_next_earnings": null, "earnings_confirmed": null, "news_sentiment_score": null, "news_headlines_last_3": [], "data_quality_note": "snapshot_ok_prices_technicals_only"}, {"symbol": "SGRO_CFD.UK", "name": "", "sector": "", "last_price": 838.6, "change_1d_pct": 14.312977099236646, "distance_from_ma200_pct": 23.337223471135403, "distance_from_ma50_pct": 14.881685289390623, "volatility_20d_pct": 61.79400737887707, "market_cap_usd": null, "avg_daily_volume_usd": null, "days_to_next_earnings": null, "earnings_confirmed": null, "news_sentiment_score": null, "news_headlines_last_3": [], "data_quality_note": "snapshot_ok_prices_technicals_only"}, {"symbol": "RHIM_CFD.UK", "name": "RHI MAGNESITA NV", "sector": "", "last_price": 2960.0, "change_1d_pct": 9.023941068139973, "distance_from_ma200_pct": 12.939755835694466, "distance_from_ma50_pct": 17.95826987098712, "volatility_20d_pct": 137.0123103901981, "market_cap_usd": null, "avg_daily_volume_usd": null, "days_to_next_earnings": null, "earnings_confirmed": null, "news_sentiment_score": null, "news_headlines_last_3": [], "data_quality_note": "snapshot_ok_prices_technicals_only"}, {"symbol": "BBY_CFD.UK", "name": "BALFOUR BEATTY PLC", "sector": "", "last_price": 759.18, "change_1d_pct": 5.222453222453205, "distance_from_ma200_pct": 33.313724414201815, "distance_from_ma50_pct": 8.832962232591, "volatility_20d_pct": 54.25956465831767, "market_cap_usd": null, "avg_daily_volume_usd": null, "days_to_next_earnings": null, "earnings_confirmed": null, "news_sentiment_score": null, "news_headlines_last_3": [], "data_quality_note": "snapshot_ok_prices_technicals_only"}, {"symbol": "JCQ_CFD.FR", "name": "", "sector": "", "last_price": 23.15, "change_1d_pct": -2.7310924369748024, "distance_from_ma200_pct": 12.41703173875155, "distance_from_ma50_pct": 2.726261802426566, "volatility_20d_pct": 60.277859704178006, "market_cap_usd": null, "avg_daily_volume_usd": null, "days_to_next_earnings": null, "earnings_confirmed": null, "news_sentiment_score": null, "news_headlines_last_3": [], "data_quality_note": "snapshot_ok_prices_technicals_only"}, {"symbol": "SHC_CFD.UK", "name": "SHAFTESBURY CAPITAL PLC", "sector": "", "last_price": 147.2, "change_1d_pct": 2.364394993045882, "distance_from_ma200_pct": 5.210906053879838, "distance_from_ma50_pct": 3.8182841489510233, "volatility_20d_pct": 60.09537427211038, "market_cap_usd": null, "avg_daily_volume_usd": null, "days_to_next_earnings": null, "earnings_confirmed": null, "news_sentiment_score": null, "news_headlines_last_3": [], "data_quality_note": "snapshot_ok_prices_technicals_only"}, {"symbol": "DUE_CFD.DE", "name": "DUERR AG", "sector": "", "last_price": 21.714, "change_1d_pct": -1.3000000000000012, "distance_from_ma200_pct": -0.1738475616862356, "distance_from_ma50_pct": -6.2186607330268036, "volatility_20d_pct": 73.1874204532971, "market_cap_usd": null, "avg_daily_volume_usd": null, "days_to_next_earnings": null, "earnings_confirmed": null, "news_sentiment_score": null, "news_headlines_last_3": [], "data_quality_note": "snapshot_ok_prices_technicals_only"}, {"symbol": "GDS_CFD.FR", "name": "", "sector": "", "last_price": 11.0, "change_1d_pct": 8.910891089108919, "distance_from_ma200_pct": 9.730830273339496, "distance_from_ma50_pct": 11.668324772095096, "volatility_20d_pct": 113.97071668246626, "market_cap_usd": null, "avg_daily_volume_usd": null, "days_to_next_earnings": null, "earnings_confirmed": null, "news_sentiment_score": null, "news_headlines_last_3": [], "data_quality_note": "snapshot_ok_prices_technicals_only"}, {"symbol": "DPLM_CFD.UK", "name": "DIPLOMA PLC", "sector": "", "last_price": 5510.0, "change_1d_pct": 0.7312614259597838, "distance_from_ma200_pct": 11.035071455048428, "distance_from_ma50_pct": 0.39717925834363843, "volatility_20d_pct": 72.46279741195445, "market_cap_usd": null, "avg_daily_volume_usd": null, "days_to_next_earnings": null, "earnings_confirmed": null, "news_sentiment_score": null, "news_headlines_last_3": [], "data_quality_note": "snapshot_ok_prices_technicals_only"}, {"symbol": "IPO_CFD.UK", "name": "IP GROUP PLC", "sector": "", "last_price": 57.6, "change_1d_pct": -1.873935264054516, "distance_from_ma200_pct": 10.233643652522883, "distance_from_ma50_pct": -2.027486732888828, "volatility_20d_pct": 89.82123635439407, "market_cap_usd": null, "avg_daily_volume_usd": null, "days_to_next_earnings": null, "earnings_confirmed": null, "news_sentiment_score": null, "news_headlines_last_3": [], "data_quality_note": "snapshot_ok_prices_technicals_only"}, {"symbol": "ATG_CFD.UK", "name": "AUCTION TECHNOLOGY GROUP", "sector": "", "last_price": 305.0, "change_1d_pct": 4.2735042735042805, "distance_from_ma200_pct": -30.344980756373573, "distance_from_ma50_pct": -1.1704016694101371, "volatility_20d_pct": 159.9931345477538, "market_cap_usd": null, "avg_daily_volume_usd": null, "days_to_next_earnings": null, "earnings_confirmed": null, "news_sentiment_score": null, "news_headlines_last_3": [], "data_quality_note": "snapshot_ok_prices_technicals_only"}, {"symbol": "GO_CFD.US", "name": "Grocery Outlet Holding Corp", "sector": "", "last_price": 6.95, "change_1d_pct": -29.726996966632967, "distance_from_ma200_pct": -47.21211614853522, "distance_from_ma50_pct": -28.605181517473753, "volatility_20d_pct": 144.92553547550253, "market_cap_usd": null, "avg_daily_volume_usd": null, "days_to_next_earnings": null, "earnings_confirmed": null, 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"snapshot_ok_prices_technicals_only"}, {"symbol": "TKA_CFD.DE", "name": "", "sector": "", "last_price": 9.666, "change_1d_pct": 2.102038660610539, "distance_from_ma200_pct": -3.4659769001453067, "distance_from_ma50_pct": -8.59539894240735, "volatility_20d_pct": 91.60155466020963, "market_cap_usd": null, "avg_daily_volume_usd": null, "days_to_next_earnings": null, "earnings_confirmed": null, "news_sentiment_score": null, "news_headlines_last_3": [], "data_quality_note": "snapshot_ok_prices_technicals_only"}, {"symbol": "ADJ_CFD.DE", "name": "ADLER GROUP SA", "sector": "", "last_price": 0.19, "change_1d_pct": -4.522613065326642, "distance_from_ma200_pct": -9.336005535275438, "distance_from_ma50_pct": -1.8493646037813782, "volatility_20d_pct": 302.6270986950585, "market_cap_usd": null, "avg_daily_volume_usd": null, "days_to_next_earnings": null, "earnings_confirmed": null, "news_sentiment_score": null, "news_headlines_last_3": [], "data_quality_note": 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{"symbol": "GXI_CFD.DE", "name": "GERRESHEIMER AG", "sector": "", "last_price": 17.966, "change_1d_pct": 14.725415070242654, "distance_from_ma200_pct": -49.1749846210904, "distance_from_ma50_pct": -24.764359931724258, "volatility_20d_pct": 234.08732547419734, "market_cap_usd": null, "avg_daily_volume_usd": null, "days_to_next_earnings": null, "earnings_confirmed": null, "news_sentiment_score": null, "news_headlines_last_3": [], "data_quality_note": "snapshot_ok_prices_technicals_only"}, {"symbol": "KBX_CFD.DE", "name": "", "sector": "", "last_price": 107.0, "change_1d_pct": 1.904761904761898, "distance_from_ma200_pct": 19.320630704320706, "distance_from_ma50_pct": 4.476638437795, "volatility_20d_pct": 49.68442531513264, "market_cap_usd": null, "avg_daily_volume_usd": null, "days_to_next_earnings": null, "earnings_confirmed": null, "news_sentiment_score": null, "news_headlines_last_3": [], "data_quality_note": "snapshot_ok_prices_technicals_only"}, {"symbol": "BESI_CFD.NL", "name": "BE 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"last_price": 3.99, "change_1d_pct": 3.475103734439844, "distance_from_ma200_pct": 15.838186537222088, "distance_from_ma50_pct": 2.856789321454545, "volatility_20d_pct": 83.02913938763913, "market_cap_usd": null, "avg_daily_volume_usd": null, "days_to_next_earnings": null, "earnings_confirmed": null, "news_sentiment_score": null, "news_headlines_last_3": [], "data_quality_note": "snapshot_ok_prices_technicals_only"}, {"symbol": "GFT_CFD.DE", "name": "", "sector": "", "last_price": 18.054, "change_1d_pct": 21.005361930294896, "distance_from_ma200_pct": -5.472950703154222, "distance_from_ma50_pct": -2.2658472891683767, "volatility_20d_pct": 91.79751049921435, "market_cap_usd": null, "avg_daily_volume_usd": null, "days_to_next_earnings": null, "earnings_confirmed": null, "news_sentiment_score": null, "news_headlines_last_3": [], "data_quality_note": "snapshot_ok_prices_technicals_only"}, {"symbol": "DCC_CFD.UK", "name": "DCC PLC", "sector": "", "last_price": 4880.0, "change_1d_pct": 12.235510579576815, "distance_from_ma200_pct": 1.3673868483688123, "distance_from_ma50_pct": 1.2134077235287588, "volatility_20d_pct": 97.80708435693202, "market_cap_usd": null, "avg_daily_volume_usd": null, "days_to_next_earnings": null, "earnings_confirmed": null, "news_sentiment_score": null, "news_headlines_last_3": [], "data_quality_note": "snapshot_ok_prices_technicals_only"}, {"symbol": "LGEN_CFD.UK", "name": "", "sector": "", "last_price": 262.78, "change_1d_pct": -4.3392792136876635, "distance_from_ma200_pct": 4.419531435333424, "distance_from_ma50_pct": -0.9270883995189272, "volatility_20d_pct": 51.67078455235858, "market_cap_usd": null, "avg_daily_volume_usd": null, "days_to_next_earnings": null, "earnings_confirmed": null, "news_sentiment_score": null, "news_headlines_last_3": [], "data_quality_note": "snapshot_ok_prices_technicals_only"}, {"symbol": "AML_CFD.UK", "name": "ASTON MARTIN LAGONDA GLOBAL", "sector": "", "last_price": 45.17, "change_1d_pct": -14.853911404335529, 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          "reasoning": "  The user wants me to perform a \"stage1_universe_scan\" task for the \"meanrev-v1\" strategy. I need to:\n1. Select exactly 5 candidates from the provided universe\n2. Focus on short-term mean reversion in liquid equities\n3. Avoid earnings within 5 trading days (if known) - but none are known\n4. Avoid highly binary/event-driven moves (if known) - but none are known\n5. Avoid sector concentration: max 1 per sector unless clearly justified (sector may be unknown) - all sectors are unknown/empty\n6. Output only valid JSON\n7. Not invent any data\n\nThe universe contains a mix of UK, US, DE, FR, and NL CFDs. Since the region is \"US\", I should focus on US symbols. Let me filter for US symbols:\n\nUS symbols in the universe:\n- GO_CFD.US (Grocery Outlet Holding Corp)\n- DKNG_CFD.US (DraftKings Inc)\n- JBLU_CFD.US (JETBLUE AIRWAYS CORP)\n- BWXT_CFD.US (BWX Technologies Inc)\n- FBIN_CFD.US (Fortune Brands Innovations Inc)\n- DELL_CFD.US (DELL TECHNOLOGIES -C)\n\nThat's only 6 US symbols. The task says \"Select exactly 5 candidates\" but the region is US. This is a bit ambiguous. Should I only select from US symbols or can I select from the entire universe? The strategy is for US region, so I should prioritize US symbols. But there are only 6 US symbols, and I need to select 5. Let me check if any of these are clearly unsuitable.\n\nFor mean reversion, I want:\n- Large moves in either direction (overextended)\n- High volatility (means opportunity for reversion)\n- Distance from moving averages (shows overextension)\n\nLet me evaluate each US symbol:\n\n1. **GO_CFD.US**: -29.73% change, -47% from MA200, -28.6% from MA50, 144.9% volatility. This is a strong candidate - huge drop, well below both MAs, high volatility.\n\n2. **DKNG_CFD.US**: +7.39% change, -30.3% from MA200, -13.7% from MA50, 123% volatility. Below MAs but positive move today. Could be a candidate for continuation or mean reversion.\n\n3. **JBLU_CFD.US**: -14.62% change, -2.4% from MA200, -10.8% from MA50, 135% volatility. Below MAs, large drop, high volatility. Good candidate.\n\n4. **BWXT_CFD.US**: -1.88% change, +15.3% from MA200, +0.67% from MA50, 92.9% volatility. Above MAs, small move. Not a strong mean reversion candidate.\n\n5. **FBIN_CFD.US**: -8.43% change, -6.9% from MA200, -10.2% from MA50, 139.3% volatility. Below MAs, decent drop, high volatility. Good candidate.\n\n6. **DELL_CFD.US**: +0.65% change, +14.4% from MA200, +20.4% from MA50, 141.2% volatility. Well above MAs, small positive move. Not ideal for mean reversion.\n\nSo from US symbols, the best candidates are: GO, JBLU, FBIN, DKNG. That's only 4. I need 5.\n\nSince all sectors are unknown/empty, the sector concentration constraint is effectively moot. I can select from the entire universe if needed. Let me look at non-US symbols that show strong mean reversion signals:\n\nStrong candidates from the full universe:\n\n- **PAGE_CFD.UK**: -13.09% change, -20.5% from MA200, -9.5% from MA50, 113% volatility. Good candidate.\n- **MCG_CFD.UK**: +21.87% change, +10.2% from MA200, +28.7% from MA50, 211% volatility. Strong upward move, extended above MAs. Good candidate for downward reversion.\n- **UTG_CFD.UK**: +3.46% change, -23.9% from MA200, -3.7% from MA50, 73.8% volatility. Below MAs but positive move.\n- **TRN_CFD.UK**: -12.93% change, -22.6% from MA200, -12.6% from MA50, 131% volatility. Good candidate.\n- **DLN_CFD.UK**: +10.40% change, +5.1% from MA200, +12.2% from MA50, 115% volatility. Extended above MAs.\n- **FUTR_CFD.UK**: -20.82% change, -37.7% from MA200, -24.3% from MA50, 153.6% volatility. Very strong candidate - huge drop, well below MAs.\n- **OCDO_CFD.UK**: -21.31% change, -14.1% from MA200, -3.2% from MA50, 241% volatility. Very strong candidate - huge drop, extremely high volatility.\n- **AML_CFD.UK**: -14.85% change, -35% from MA200, -24.2% from MA50, 125% volatility. Strong candidate.\n- **GXI_CFD.DE**: +14.73% change, -49.2% from MA200, -24.8% from MA50, 234% volatility. Interesting - big positive move but still well below MAs.\n- **PZC_CFD.UK**: -10.30% change, +8.4% from MA200, +8.1% from MA50, 91% volatility. Below MAs but still above them.\n\nGiven that I need 5 candidates and only 4 US symbols are strong candidates, I should include one non-US symbol. Since sectors are all unknown, I can justify this.\n\nLet me rank the best candidates overall:\n\n1. **GO_CFD.US**: -29.73%, -47% from MA200, 144.9% vol - extreme oversold\n2. **FUTR_CFD.UK**: -20.82%, -37.7% from MA200, 153.6% vol - extreme oversold\n3. **OCDO_CFD.UK**: -21.31%, -14.1% from MA200, 241% vol - huge drop, highest vol\n4. **JBLU_CFD.US**: -14.62%, -2.4% from MA200, 135% vol - strong drop\n5. **FBIN_CFD.US**: -8.43%, -6.9% from MA200, 139.3% vol - decent setup\n6. **AML_CFD.UK**: -14.85%, -35% from MA200, 125% vol - strong candidate\n7. **TRN_CFD.UK**: -12.93%, -22.6% from MA200, 131% vol - strong candidate\n8. **PAGE_CFD.UK**: -13.09%, -20.5% from MA200, 113% vol - strong candidate\n9. **DKNG_CFD.US**: +7.39%, -30% from MA200, 123% vol - below MAs but positive today\n10. **MCG_CFD.UK**: +21.87%, +10% from MA200, 211% vol - extended up\n\nFor mean reversion, I want the most extreme moves away from MAs. The best signals are:\n- GO_CFD.US (massive drop)\n- FUTR_CFD.UK (massive drop)\n- OCDO_CFD.UK (massive drop, highest vol)\n- AML_CFD.UK (big drop)\n- JBLU_CFD.US or FBIN_CFD.US or TRN_CFD.UK\n\nSince the region is US, I should prioritize US symbols. Let me select:\n1. GO_CFD.US (best US candidate)\n2. JBLU_CFD.US (good US candidate)\n3. FBIN_CFD.US (good US candidate)\n4. DKNG_CFD.US (US symbol, though positive today, still oversold longer term)\n5. FUTR_CFD.UK (best non-US candidate to complete the 5)\n\nWait, let me reconsider. The region is \"US\" which might mean I should ONLY consider US symbols. But there are only 6 US symbols and I need to select 5. Let me check if I can make a case for 5 US symbols:\n\nUS symbols evaluation for mean reversion:\n- GO_CFD.US: Excellent - extreme oversold\n- JBLU_CFD.US: Good - oversold, high vol\n- FBIN_CFD.US: Good - oversold, high vol\n- DKNG_CFD.US: Moderate - oversold on longer timeframe but positive today, might need more time\n- BWXT_CFD.US: Poor - above MAs, not extended\n- DELL_CFD.US: Poor - well above MAs, not extended\n\nThat's only 4 good US candidates. The instructions say \"Select exactly 5 candidates\". This is a constraint I must follow. Since there aren't 5 strong US candidates, I must include non-US symbols. The sector constraint is moot since all sectors are unknown.\n\nLet me select the 5 strongest mean reversion signals from the entire universe:\n\n1. **GO_CFD.US**: Score 95 - Extreme oversold, -29.7% day, -47% from MA200, 144.9% vol\n2. **FUTR_CFD.UK**: Score 90 - Extreme oversold, -20.8% day, -37.7% from MA200, 153.6% vol\n3. **OCDO_CFD.UK**: Score 88 - Extreme drop, -21.3% day, -14% from MA200, 241% vol (highest)\n4. **AML_CFD.UK**: Score 85 - Strong oversold, -14.9% day, -35% from MA200, 125% vol\n5. **JBLU_CFD.US**: Score 82 - Good oversold, -14.6% day, -2.4% from MA200, 135% vol\n\nAlternative: Could include FBIN_CFD.US instead of AML_CFD.UK to have more US exposure.\n\nLet me think about the strategy. It's \"Two-Stage LLM Mean-Reversion (Arena v1)\" for US region. The key is:\n- Short-term mean reversion (2-10 trading days)\n- Liquid equities\n- Avoid overtrading\n\nFor mean reversion, I want stocks that have moved excessively in one direction and are likely to snap back. The best candidates are those with:\n1. Large single-day moves\n2. Large distance from moving averages\n3. High volatility (shows movement potential)\n4. Preferably below MAs for bounce plays (or above for pullback plays)\n\nGiven the US region focus, I'll select 4 US stocks and 1 UK stock to make up the 5:\n\nFinal selection:\n1. GO_CFD.US - Best US candidate, extreme oversold\n2. JBLU_CFD.US - Good US candidate, oversold\n3. FBIN_CFD.US - Good US candidate, oversold\n4. DKNG_CFD.US - US candidate, oversold on longer timeframe\n5. FUTR_CFD.UK - Best overall non-US candidate to complete the set\n\nWait, let me recalculate scores more systematically. I should assign a mean_reversion_score (0-100) based on:\n- Magnitude of daily move (absolute value)\n- Distance from MA50 and MA200\n- Volatility level\n\nLet me create a scoring rubric:\n- Daily move >15%: 30 points\n- Daily move 10-15%: 25 points\n- Daily move 5-10%: 20 points\n- Daily move <5%: 10 points\n\n- Distance from MA200 >30%: 30 points\n- Distance 20-30%: 25 points\n- Distance 10-20%: 20 points\n- Distance <10%: 10 points\n\n- Volatility >150%: 20 points\n- Volatility 100-150%: 15 points\n- Volatility 75-100%: 10 points\n- Volatility <75%: 5 points\n\n- Distance from MA50 adds context but I'll focus on MA200 as primary trend\n\nLet me score the top candidates:\n\n**GO_CFD.US**:\n- Daily: -29.73% = 30 pts\n- Dist MA200: -47.21% = 30 pts\n- Vol: 144.93% = 15 pts\n- Total: 75 pts\n\n**FUTR_CFD.UK**:\n- Daily: -20.82% = 30 pts\n- Dist MA200: -37.68% = 30 pts\n- Vol: 153.59% = 20 pts\n- Total: 80 pts\n\n**OCDO_CFD.UK**:\n- Daily: -21.31% = 30 pts\n- Dist MA200: -14.07% = 20 pts\n- Vol: 240.96% = 20 pts\n- Total: 70 pts\n\n**AML_CFD.UK**:\n- Daily: -14.85% = 25 pts\n- Dist MA200: -34.96% = 30 pts\n- Vol: 124.96% = 15 pts\n- Total: 70 pts\n\n**JBLU_CFD.US**:\n- Daily: -14.62% = 25 pts\n- Dist MA200: -2.42% = 10 pts\n- Vol: 135.18% = 15 pts\n- Total: 50 pts\n\n**FBIN_CFD.US**:\n- Daily: -8.43% = 20 pts\n- Dist MA200: -6.94% = 10 pts\n- Vol: 139.32% = 15 pts\n- Total: 45 pts\n\n**TRN_CFD.UK**:\n- Daily: -12.93% = 25 pts\n- Dist MA200: -22.56% = 25 pts\n- Vol: 131.09% = 15 pts\n- Total: 65 pts\n\n**PAGE_CFD.UK**:\n- Daily: -13.09% = 25 pts\n- Dist MA200: -20.51% = 25 pts\n- Vol: 113.15% = 15 pts\n- Total: 65 pts\n\n**DKNG_CFD.US**:\n- Daily: +7.39% = 20 pts\n- Dist MA200: -30.32% = 30 pts\n- Vol: 122.99% = 15 pts\n- Total: 65 pts\n\n**MCG_CFD.UK**:\n- Daily: +21.87% = 30 pts\n- Dist MA200: +10.17% = 20 pts (but above MA, so mean reversion would be short)\n- Vol: 211.42% = 20 pts\n- Total: 70 pts (but direction is opposite)\n\nGiven the US region focus, I'll prioritize US symbols but need 5 total. The best US candidates are GO, JBLU, FBIN, DKNG. I need one more, and FUTR is the strongest overall.\n\nBut wait, let me check the constraint again: \"Avoid sector concentration: max 1 per sector unless clearly justified (sector may be unknown)\". Since all sectors are unknown, this constraint is effectively \"max 1 per unknown sector\" which is meaningless. So I can select any 5.\n\nHowever, the region is specified as \"US\". This likely means I should focus on US-listed equities. But there are only 6 US symbols provided. Let me check if any of the non-US symbols could be considered \"US equities\" - no, they're UK, DE, FR, NL.\n\nI think the most reasonable interpretation is: prioritize US symbols, but if there aren't enough strong candidates, supplement with non-US symbols to reach exactly 5. The alternative would be to select weak US candidates, which violates the spirit of the strategy.\n\nSo my final selection:\n1. GO_CFD.US (score 75)\n2. FUTR_CFD.UK (score 80) - best non-US\n3. OCDO_CFD.UK (score 70) - high vol\n4. AML_CFD.UK (score 70) - deep oversold\n5. DKNG_CFD.US (score 65) - US symbol, oversold\n\nWait, I should include more US symbols if possible. Let me reconsider:\n\nUS symbols scores:\n- GO: 75\n- JBLU: 50\n- FBIN: 45\n- DKNG: 65\n- BWXT: (would be low, above MAs)\n- DELL: (would be low, above MAs)\n\nSo only GO and DKNG are strong US candidates. JBLU and FBIN are moderate. I need to pick 5 total. \n\nGiven the US region, I should pick:\n1. GO_CFD.US (75)\n2. DKNG_CFD.US (65)\n3. JBLU_CFD.US (50)\n4. FBIN_CFD.US (45)\n5. FUTR_CFD.UK (80) - best non-US to complete\n\nThis gives me 4 US and 1 non-US. The scores are relative, so I can adjust them to be 0-100 scale. Let me normalize the scores of selected stocks.\n\nActually, the instruction says \"mean_reversion_score\": \"integer 0-100\". I should assign absolute scores, not relative rankings. Let me use my rubric more carefully.\n\nRevised scoring with more nuance:\n- Daily move weight: 40%\n- Distance from MA200 weight: 35%\n- Volatility weight: 25%\n\n**GO_CFD.US**:\n- Daily: -29.73% = 40 pts (max)\n- Dist MA200: -47.21% = 35 pts (max)\n- Vol: 144.93% = 20 pts (high)\n- Total: 95\n\n**FUTR_CFD.UK**:\n- Daily: -20.82% = 38 pts\n- Dist MA200: -37.68% = 35 pts",
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            {
              "text": "  The user wants me to perform a \"stage1_universe_scan\" task for the \"meanrev-v1\" strategy. I need to:\n1. Select exactly 5 candidates from the provided universe\n2. Focus on short-term mean reversion in liquid equities\n3. Avoid earnings within 5 trading days (if known) - but none are known\n4. Avoid highly binary/event-driven moves (if known) - but none are known\n5. Avoid sector concentration: max 1 per sector unless clearly justified (sector may be unknown) - all sectors are unknown/empty\n6. Output only valid JSON\n7. Not invent any data\n\nThe universe contains a mix of UK, US, DE, FR, and NL CFDs. Since the region is \"US\", I should focus on US symbols. Let me filter for US symbols:\n\nUS symbols in the universe:\n- GO_CFD.US (Grocery Outlet Holding Corp)\n- DKNG_CFD.US (DraftKings Inc)\n- JBLU_CFD.US (JETBLUE AIRWAYS CORP)\n- BWXT_CFD.US (BWX Technologies Inc)\n- FBIN_CFD.US (Fortune Brands Innovations Inc)\n- DELL_CFD.US (DELL TECHNOLOGIES -C)\n\nThat's only 6 US symbols. The task says \"Select exactly 5 candidates\" but the region is US. This is a bit ambiguous. Should I only select from US symbols or can I select from the entire universe? The strategy is for US region, so I should prioritize US symbols. But there are only 6 US symbols, and I need to select 5. Let me check if any of these are clearly unsuitable.\n\nFor mean reversion, I want:\n- Large moves in either direction (overextended)\n- High volatility (means opportunity for reversion)\n- Distance from moving averages (shows overextension)\n\nLet me evaluate each US symbol:\n\n1. **GO_CFD.US**: -29.73% change, -47% from MA200, -28.6% from MA50, 144.9% volatility. This is a strong candidate - huge drop, well below both MAs, high volatility.\n\n2. **DKNG_CFD.US**: +7.39% change, -30.3% from MA200, -13.7% from MA50, 123% volatility. Below MAs but positive move today. Could be a candidate for continuation or mean reversion.\n\n3. **JBLU_CFD.US**: -14.62% change, -2.4% from MA200, -10.8% from MA50, 135% volatility. Below MAs, large drop, high volatility. Good candidate.\n\n4. **BWXT_CFD.US**: -1.88% change, +15.3% from MA200, +0.67% from MA50, 92.9% volatility. Above MAs, small move. Not a strong mean reversion candidate.\n\n5. **FBIN_CFD.US**: -8.43% change, -6.9% from MA200, -10.2% from MA50, 139.3% volatility. Below MAs, decent drop, high volatility. Good candidate.\n\n6. **DELL_CFD.US**: +0.65% change, +14.4% from MA200, +20.4% from MA50, 141.2% volatility. Well above MAs, small positive move. Not ideal for mean reversion.\n\nSo from US symbols, the best candidates are: GO, JBLU, FBIN, DKNG. That's only 4. I need 5.\n\nSince all sectors are unknown/empty, the sector concentration constraint is effectively moot. I can select from the entire universe if needed. Let me look at non-US symbols that show strong mean reversion signals:\n\nStrong candidates from the full universe:\n\n- **PAGE_CFD.UK**: -13.09% change, -20.5% from MA200, -9.5% from MA50, 113% volatility. Good candidate.\n- **MCG_CFD.UK**: +21.87% change, +10.2% from MA200, +28.7% from MA50, 211% volatility. Strong upward move, extended above MAs. Good candidate for downward reversion.\n- **UTG_CFD.UK**: +3.46% change, -23.9% from MA200, -3.7% from MA50, 73.8% volatility. Below MAs but positive move.\n- **TRN_CFD.UK**: -12.93% change, -22.6% from MA200, -12.6% from MA50, 131% volatility. Good candidate.\n- **DLN_CFD.UK**: +10.40% change, +5.1% from MA200, +12.2% from MA50, 115% volatility. Extended above MAs.\n- **FUTR_CFD.UK**: -20.82% change, -37.7% from MA200, -24.3% from MA50, 153.6% volatility. Very strong candidate - huge drop, well below MAs.\n- **OCDO_CFD.UK**: -21.31% change, -14.1% from MA200, -3.2% from MA50, 241% volatility. Very strong candidate - huge drop, extremely high volatility.\n- **AML_CFD.UK**: -14.85% change, -35% from MA200, -24.2% from MA50, 125% volatility. Strong candidate.\n- **GXI_CFD.DE**: +14.73% change, -49.2% from MA200, -24.8% from MA50, 234% volatility. Interesting - big positive move but still well below MAs.\n- **PZC_CFD.UK**: -10.30% change, +8.4% from MA200, +8.1% from MA50, 91% volatility. Below MAs but still above them.\n\nGiven that I need 5 candidates and only 4 US symbols are strong candidates, I should include one non-US symbol. Since sectors are all unknown, I can justify this.\n\nLet me rank the best candidates overall:\n\n1. **GO_CFD.US**: -29.73%, -47% from MA200, 144.9% vol - extreme oversold\n2. **FUTR_CFD.UK**: -20.82%, -37.7% from MA200, 153.6% vol - extreme oversold\n3. **OCDO_CFD.UK**: -21.31%, -14.1% from MA200, 241% vol - huge drop, highest vol\n4. **JBLU_CFD.US**: -14.62%, -2.4% from MA200, 135% vol - strong drop\n5. **FBIN_CFD.US**: -8.43%, -6.9% from MA200, 139.3% vol - decent setup\n6. **AML_CFD.UK**: -14.85%, -35% from MA200, 125% vol - strong candidate\n7. **TRN_CFD.UK**: -12.93%, -22.6% from MA200, 131% vol - strong candidate\n8. **PAGE_CFD.UK**: -13.09%, -20.5% from MA200, 113% vol - strong candidate\n9. **DKNG_CFD.US**: +7.39%, -30% from MA200, 123% vol - below MAs but positive today\n10. **MCG_CFD.UK**: +21.87%, +10% from MA200, 211% vol - extended up\n\nFor mean reversion, I want the most extreme moves away from MAs. The best signals are:\n- GO_CFD.US (massive drop)\n- FUTR_CFD.UK (massive drop)\n- OCDO_CFD.UK (massive drop, highest vol)\n- AML_CFD.UK (big drop)\n- JBLU_CFD.US or FBIN_CFD.US or TRN_CFD.UK\n\nSince the region is US, I should prioritize US symbols. Let me select:\n1. GO_CFD.US (best US candidate)\n2. JBLU_CFD.US (good US candidate)\n3. FBIN_CFD.US (good US candidate)\n4. DKNG_CFD.US (US symbol, though positive today, still oversold longer term)\n5. FUTR_CFD.UK (best non-US candidate to complete the 5)\n\nWait, let me reconsider. The region is \"US\" which might mean I should ONLY consider US symbols. But there are only 6 US symbols and I need to select 5. Let me check if I can make a case for 5 US symbols:\n\nUS symbols evaluation for mean reversion:\n- GO_CFD.US: Excellent - extreme oversold\n- JBLU_CFD.US: Good - oversold, high vol\n- FBIN_CFD.US: Good - oversold, high vol\n- DKNG_CFD.US: Moderate - oversold on longer timeframe but positive today, might need more time\n- BWXT_CFD.US: Poor - above MAs, not extended\n- DELL_CFD.US: Poor - well above MAs, not extended\n\nThat's only 4 good US candidates. The instructions say \"Select exactly 5 candidates\". This is a constraint I must follow. Since there aren't 5 strong US candidates, I must include non-US symbols. The sector constraint is moot since all sectors are unknown.\n\nLet me select the 5 strongest mean reversion signals from the entire universe:\n\n1. **GO_CFD.US**: Score 95 - Extreme oversold, -29.7% day, -47% from MA200, 144.9% vol\n2. **FUTR_CFD.UK**: Score 90 - Extreme oversold, -20.8% day, -37.7% from MA200, 153.6% vol\n3. **OCDO_CFD.UK**: Score 88 - Extreme drop, -21.3% day, -14% from MA200, 241% vol (highest)\n4. **AML_CFD.UK**: Score 85 - Strong oversold, -14.9% day, -35% from MA200, 125% vol\n5. **JBLU_CFD.US**: Score 82 - Good oversold, -14.6% day, -2.4% from MA200, 135% vol\n\nAlternative: Could include FBIN_CFD.US instead of AML_CFD.UK to have more US exposure.\n\nLet me think about the strategy. It's \"Two-Stage LLM Mean-Reversion (Arena v1)\" for US region. The key is:\n- Short-term mean reversion (2-10 trading days)\n- Liquid equities\n- Avoid overtrading\n\nFor mean reversion, I want stocks that have moved excessively in one direction and are likely to snap back. The best candidates are those with:\n1. Large single-day moves\n2. Large distance from moving averages\n3. High volatility (shows movement potential)\n4. Preferably below MAs for bounce plays (or above for pullback plays)\n\nGiven the US region focus, I'll select 4 US stocks and 1 UK stock to make up the 5:\n\nFinal selection:\n1. GO_CFD.US - Best US candidate, extreme oversold\n2. JBLU_CFD.US - Good US candidate, oversold\n3. FBIN_CFD.US - Good US candidate, oversold\n4. DKNG_CFD.US - US candidate, oversold on longer timeframe\n5. FUTR_CFD.UK - Best overall non-US candidate to complete the set\n\nWait, let me recalculate scores more systematically. I should assign a mean_reversion_score (0-100) based on:\n- Magnitude of daily move (absolute value)\n- Distance from MA50 and MA200\n- Volatility level\n\nLet me create a scoring rubric:\n- Daily move >15%: 30 points\n- Daily move 10-15%: 25 points\n- Daily move 5-10%: 20 points\n- Daily move <5%: 10 points\n\n- Distance from MA200 >30%: 30 points\n- Distance 20-30%: 25 points\n- Distance 10-20%: 20 points\n- Distance <10%: 10 points\n\n- Volatility >150%: 20 points\n- Volatility 100-150%: 15 points\n- Volatility 75-100%: 10 points\n- Volatility <75%: 5 points\n\n- Distance from MA50 adds context but I'll focus on MA200 as primary trend\n\nLet me score the top candidates:\n\n**GO_CFD.US**:\n- Daily: -29.73% = 30 pts\n- Dist MA200: -47.21% = 30 pts\n- Vol: 144.93% = 15 pts\n- Total: 75 pts\n\n**FUTR_CFD.UK**:\n- Daily: -20.82% = 30 pts\n- Dist MA200: -37.68% = 30 pts\n- Vol: 153.59% = 20 pts\n- Total: 80 pts\n\n**OCDO_CFD.UK**:\n- Daily: -21.31% = 30 pts\n- Dist MA200: -14.07% = 20 pts\n- Vol: 240.96% = 20 pts\n- Total: 70 pts\n\n**AML_CFD.UK**:\n- Daily: -14.85% = 25 pts\n- Dist MA200: -34.96% = 30 pts\n- Vol: 124.96% = 15 pts\n- Total: 70 pts\n\n**JBLU_CFD.US**:\n- Daily: -14.62% = 25 pts\n- Dist MA200: -2.42% = 10 pts\n- Vol: 135.18% = 15 pts\n- Total: 50 pts\n\n**FBIN_CFD.US**:\n- Daily: -8.43% = 20 pts\n- Dist MA200: -6.94% = 10 pts\n- Vol: 139.32% = 15 pts\n- Total: 45 pts\n\n**TRN_CFD.UK**:\n- Daily: -12.93% = 25 pts\n- Dist MA200: -22.56% = 25 pts\n- Vol: 131.09% = 15 pts\n- Total: 65 pts\n\n**PAGE_CFD.UK**:\n- Daily: -13.09% = 25 pts\n- Dist MA200: -20.51% = 25 pts\n- Vol: 113.15% = 15 pts\n- Total: 65 pts\n\n**DKNG_CFD.US**:\n- Daily: +7.39% = 20 pts\n- Dist MA200: -30.32% = 30 pts\n- Vol: 122.99% = 15 pts\n- Total: 65 pts\n\n**MCG_CFD.UK**:\n- Daily: +21.87% = 30 pts\n- Dist MA200: +10.17% = 20 pts (but above MA, so mean reversion would be short)\n- Vol: 211.42% = 20 pts\n- Total: 70 pts (but direction is opposite)\n\nGiven the US region focus, I'll prioritize US symbols but need 5 total. The best US candidates are GO, JBLU, FBIN, DKNG. I need one more, and FUTR is the strongest overall.\n\nBut wait, let me check the constraint again: \"Avoid sector concentration: max 1 per sector unless clearly justified (sector may be unknown)\". Since all sectors are unknown, this constraint is effectively \"max 1 per unknown sector\" which is meaningless. So I can select any 5.\n\nHowever, the region is specified as \"US\". This likely means I should focus on US-listed equities. But there are only 6 US symbols provided. Let me check if any of the non-US symbols could be considered \"US equities\" - no, they're UK, DE, FR, NL.\n\nI think the most reasonable interpretation is: prioritize US symbols, but if there aren't enough strong candidates, supplement with non-US symbols to reach exactly 5. The alternative would be to select weak US candidates, which violates the spirit of the strategy.\n\nSo my final selection:\n1. GO_CFD.US (score 75)\n2. FUTR_CFD.UK (score 80) - best non-US\n3. OCDO_CFD.UK (score 70) - high vol\n4. AML_CFD.UK (score 70) - deep oversold\n5. DKNG_CFD.US (score 65) - US symbol, oversold\n\nWait, I should include more US symbols if possible. Let me reconsider:\n\nUS symbols scores:\n- GO: 75\n- JBLU: 50\n- FBIN: 45\n- DKNG: 65\n- BWXT: (would be low, above MAs)\n- DELL: (would be low, above MAs)\n\nSo only GO and DKNG are strong US candidates. JBLU and FBIN are moderate. I need to pick 5 total. \n\nGiven the US region, I should pick:\n1. GO_CFD.US (75)\n2. DKNG_CFD.US (65)\n3. JBLU_CFD.US (50)\n4. FBIN_CFD.US (45)\n5. FUTR_CFD.UK (80) - best non-US to complete\n\nThis gives me 4 US and 1 non-US. The scores are relative, so I can adjust them to be 0-100 scale. Let me normalize the scores of selected stocks.\n\nActually, the instruction says \"mean_reversion_score\": \"integer 0-100\". I should assign absolute scores, not relative rankings. Let me use my rubric more carefully.\n\nRevised scoring with more nuance:\n- Daily move weight: 40%\n- Distance from MA200 weight: 35%\n- Volatility weight: 25%\n\n**GO_CFD.US**:\n- Daily: -29.73% = 40 pts (max)\n- Dist MA200: -47.21% = 35 pts (max)\n- Vol: 144.93% = 20 pts (high)\n- Total: 95\n\n**FUTR_CFD.UK**:\n- Daily: -20.82% = 38 pts\n- Dist MA200: -37.68% = 35 pts",
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You are an Arena portfolio manager. You must follow the strategy rules strictly and output ONLY valid JSON. You are NOT allowed to invent prices/fundamentals/news/earnings. If a field is null/empty, treat it as unknown. Avoid overtrading: if changes are marginal, prefer HOLD. Do not churn.

{"task": "stage2_portfolio_management", "region": "US", "strategy": {"key": "meanrev-v1", "name": "Two-Stage LLM Mean-Reversion (Arena v1)", "rules": {"max_positions": 10, "max_buys_per_run": 2, "avoid_overtrading": true, "max_sells_per_run": 2, "max_gross_leverage": 3.0, "fixed_position_size": 3000.0, "universe_symbols_eu": [], "universe_symbols_us": []}}, "portfolio_constraints": {"initial_equity": 10000.0, "max_positions": 10, "fixed_position_size": 3000.0, "max_gross_leverage": 3.0, "overtrading_rules": ["Max 2 SELL actions per run unless risk event forces more", "Max 2 BUY actions per run", "If no clear improvement vs current holdings, output HOLD for everything"]}, "current_portfolio": [{"symbol": "BYIT_CFD.UK", "qty": 10.252904989747094, "avg_price": 292.6, "last_price": 292.6, "unrealized_pnl": 0.0, "opened_at": "2026-03-01T10:30:13.622938+00:00"}, {"symbol": "ICG_CFD.UK", "qty": 1.7647058823529411, "avg_price": 1700.0, "last_price": 1693.0, "unrealized_pnl": -12.352941176470587, "opened_at": "2026-02-16T09:30:55.514112+00:00"}, {"symbol": "LSS_CFD.FR", "qty": 0.0, "avg_price": 20.15, "last_price": 19.44, "unrealized_pnl": 0.0, "opened_at": "2026-02-16T09:30:55.514112+00:00"}, {"symbol": "PAGE_CFD.UK", "qty": 14.577259475218659, "avg_price": 205.8, "last_price": 151.91, "unrealized_pnl": -785.5685131195337, "opened_at": "2026-02-28T10:51:05.818250+00:00"}, {"symbol": "WPP_CFD.UK", "qty": 23.624431917415748, "avg_price": 253.97436099095557, "last_price": 262.8, "unrealized_pnl": 208.5007078968589, "opened_at": "2026-02-28T10:51:05.818250+00:00"}], "candidates": [], "output_schema": {"actions": {"sell": [{"symbol": "string", "reason": "string"}], "hold": [{"symbol": "string", "reason": "string"}], "buy": [{"symbol": "string", "position_size": "number (currency amount)", "reason": "string"}]}, "portfolio_rationale": "string"}}

{
  "actions": {
    "buy": [],
    "hold": [
      {
        "reason": "Position flat (0% PnL) at target size ($3,000). No clear mean-reversion signal; maintaining position.",
        "symbol": "BYIT_CFD.UK"
      },
      {
        "reason": "Minimal loss (-0.4%, -$12 PnL) at target size. No significant mean-reversion signal; avoiding overtrading.",
        "symbol": "ICG_CFD.UK"
      },
      {
        "reason": "Significant drawdown (-26.2%, -$785 PnL) but already at target position size. Mean-reversion suggests potential recovery, but no additional capital allocated due to lack of Stage 1 buy signal and risk management constraints.",
        "symbol": "PAGE_CFD.UK"
      }
    ],
    "sell": [
      {
        "reason": "Position overweight at 2x target size ($6,208 vs $3,000 target) and showing profit (+3.5%, $208 unrealized PnL), indicating potential mean reversion downward. Reducing to target size to lock in gains and rebalance portfolio.",
        "symbol": "WPP_CFD.UK"
      }
    ]
  },
  "portfolio_rationale": "Portfolio rebalancing focused on reducing overweight WPP position that has become profitable, suggesting mean-reversion downside risk. Maintaining existing positions in BYIT, ICG, and PAGE as they are at target sizes with no clear overbought signals. No new buy candidates provided by Stage 1 screening. Action respects max 2 sells/buys constraint and avoids overtrading by not making marginal changes to flat/slightly-down positions. Gross leverage remains within 3.0x limit."
}

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          "reasoning": "  The user wants me to perform a \"stage1_universe_scan\" task for the \"meanrev-v1\" strategy. I need to:\n1. Select exactly 5 candidates from the provided universe\n2. Focus on short-term mean reversion in liquid equities\n3. Avoid earnings within 5 trading days (if known) - but none are known\n4. Avoid highly binary/event-driven moves (if known) - but none are known\n5. Avoid sector concentration: max 1 per sector unless clearly justified (sector may be unknown) - all sectors are unknown/empty\n6. Output only valid JSON\n7. Not invent any data\n\nThe universe contains a mix of UK, US, DE, FR, and NL CFDs. Since the region is \"US\", I should focus on US symbols. Let me filter for US symbols:\n\nUS symbols in the universe:\n- GO_CFD.US (Grocery Outlet Holding Corp)\n- DKNG_CFD.US (DraftKings Inc)\n- JBLU_CFD.US (JETBLUE AIRWAYS CORP)\n- BWXT_CFD.US (BWX Technologies Inc)\n- FBIN_CFD.US (Fortune Brands Innovations Inc)\n- DELL_CFD.US (DELL TECHNOLOGIES -C)\n\nThat's only 6 US symbols. The task says \"Select exactly 5 candidates\" but the region is US. This is a bit ambiguous. Should I only select from US symbols or can I select from the entire universe? The strategy is for US region, so I should prioritize US symbols. But there are only 6 US symbols, and I need to select 5. Let me check if any of these are clearly unsuitable.\n\nFor mean reversion, I want:\n- Large moves in either direction (overextended)\n- High volatility (means opportunity for reversion)\n- Distance from moving averages (shows overextension)\n\nLet me evaluate each US symbol:\n\n1. **GO_CFD.US**: -29.73% change, -47% from MA200, -28.6% from MA50, 144.9% volatility. This is a strong candidate - huge drop, well below both MAs, high volatility.\n\n2. **DKNG_CFD.US**: +7.39% change, -30.3% from MA200, -13.7% from MA50, 123% volatility. Below MAs but positive move today. Could be a candidate for continuation or mean reversion.\n\n3. **JBLU_CFD.US**: -14.62% change, -2.4% from MA200, -10.8% from MA50, 135% volatility. Below MAs, large drop, high volatility. Good candidate.\n\n4. **BWXT_CFD.US**: -1.88% change, +15.3% from MA200, +0.67% from MA50, 92.9% volatility. Above MAs, small move. Not a strong mean reversion candidate.\n\n5. **FBIN_CFD.US**: -8.43% change, -6.9% from MA200, -10.2% from MA50, 139.3% volatility. Below MAs, decent drop, high volatility. Good candidate.\n\n6. **DELL_CFD.US**: +0.65% change, +14.4% from MA200, +20.4% from MA50, 141.2% volatility. Well above MAs, small positive move. Not ideal for mean reversion.\n\nSo from US symbols, the best candidates are: GO, JBLU, FBIN, DKNG. That's only 4. I need 5.\n\nSince all sectors are unknown/empty, the sector concentration constraint is effectively moot. I can select from the entire universe if needed. Let me look at non-US symbols that show strong mean reversion signals:\n\nStrong candidates from the full universe:\n\n- **PAGE_CFD.UK**: -13.09% change, -20.5% from MA200, -9.5% from MA50, 113% volatility. Good candidate.\n- **MCG_CFD.UK**: +21.87% change, +10.2% from MA200, +28.7% from MA50, 211% volatility. Strong upward move, extended above MAs. Good candidate for downward reversion.\n- **UTG_CFD.UK**: +3.46% change, -23.9% from MA200, -3.7% from MA50, 73.8% volatility. Below MAs but positive move.\n- **TRN_CFD.UK**: -12.93% change, -22.6% from MA200, -12.6% from MA50, 131% volatility. Good candidate.\n- **DLN_CFD.UK**: +10.40% change, +5.1% from MA200, +12.2% from MA50, 115% volatility. Extended above MAs.\n- **FUTR_CFD.UK**: -20.82% change, -37.7% from MA200, -24.3% from MA50, 153.6% volatility. Very strong candidate - huge drop, well below MAs.\n- **OCDO_CFD.UK**: -21.31% change, -14.1% from MA200, -3.2% from MA50, 241% volatility. Very strong candidate - huge drop, extremely high volatility.\n- **AML_CFD.UK**: -14.85% change, -35% from MA200, -24.2% from MA50, 125% volatility. Strong candidate.\n- **GXI_CFD.DE**: +14.73% change, -49.2% from MA200, -24.8% from MA50, 234% volatility. Interesting - big positive move but still well below MAs.\n- **PZC_CFD.UK**: -10.30% change, +8.4% from MA200, +8.1% from MA50, 91% volatility. Below MAs but still above them.\n\nGiven that I need 5 candidates and only 4 US symbols are strong candidates, I should include one non-US symbol. Since sectors are all unknown, I can justify this.\n\nLet me rank the best candidates overall:\n\n1. **GO_CFD.US**: -29.73%, -47% from MA200, 144.9% vol - extreme oversold\n2. **FUTR_CFD.UK**: -20.82%, -37.7% from MA200, 153.6% vol - extreme oversold\n3. **OCDO_CFD.UK**: -21.31%, -14.1% from MA200, 241% vol - huge drop, highest vol\n4. **JBLU_CFD.US**: -14.62%, -2.4% from MA200, 135% vol - strong drop\n5. **FBIN_CFD.US**: -8.43%, -6.9% from MA200, 139.3% vol - decent setup\n6. **AML_CFD.UK**: -14.85%, -35% from MA200, 125% vol - strong candidate\n7. **TRN_CFD.UK**: -12.93%, -22.6% from MA200, 131% vol - strong candidate\n8. **PAGE_CFD.UK**: -13.09%, -20.5% from MA200, 113% vol - strong candidate\n9. **DKNG_CFD.US**: +7.39%, -30% from MA200, 123% vol - below MAs but positive today\n10. **MCG_CFD.UK**: +21.87%, +10% from MA200, 211% vol - extended up\n\nFor mean reversion, I want the most extreme moves away from MAs. The best signals are:\n- GO_CFD.US (massive drop)\n- FUTR_CFD.UK (massive drop)\n- OCDO_CFD.UK (massive drop, highest vol)\n- AML_CFD.UK (big drop)\n- JBLU_CFD.US or FBIN_CFD.US or TRN_CFD.UK\n\nSince the region is US, I should prioritize US symbols. Let me select:\n1. GO_CFD.US (best US candidate)\n2. JBLU_CFD.US (good US candidate)\n3. FBIN_CFD.US (good US candidate)\n4. DKNG_CFD.US (US symbol, though positive today, still oversold longer term)\n5. FUTR_CFD.UK (best non-US candidate to complete the 5)\n\nWait, let me reconsider. The region is \"US\" which might mean I should ONLY consider US symbols. But there are only 6 US symbols and I need to select 5. Let me check if I can make a case for 5 US symbols:\n\nUS symbols evaluation for mean reversion:\n- GO_CFD.US: Excellent - extreme oversold\n- JBLU_CFD.US: Good - oversold, high vol\n- FBIN_CFD.US: Good - oversold, high vol\n- DKNG_CFD.US: Moderate - oversold on longer timeframe but positive today, might need more time\n- BWXT_CFD.US: Poor - above MAs, not extended\n- DELL_CFD.US: Poor - well above MAs, not extended\n\nThat's only 4 good US candidates. The instructions say \"Select exactly 5 candidates\". This is a constraint I must follow. Since there aren't 5 strong US candidates, I must include non-US symbols. The sector constraint is moot since all sectors are unknown.\n\nLet me select the 5 strongest mean reversion signals from the entire universe:\n\n1. **GO_CFD.US**: Score 95 - Extreme oversold, -29.7% day, -47% from MA200, 144.9% vol\n2. **FUTR_CFD.UK**: Score 90 - Extreme oversold, -20.8% day, -37.7% from MA200, 153.6% vol\n3. **OCDO_CFD.UK**: Score 88 - Extreme drop, -21.3% day, -14% from MA200, 241% vol (highest)\n4. **AML_CFD.UK**: Score 85 - Strong oversold, -14.9% day, -35% from MA200, 125% vol\n5. **JBLU_CFD.US**: Score 82 - Good oversold, -14.6% day, -2.4% from MA200, 135% vol\n\nAlternative: Could include FBIN_CFD.US instead of AML_CFD.UK to have more US exposure.\n\nLet me think about the strategy. It's \"Two-Stage LLM Mean-Reversion (Arena v1)\" for US region. The key is:\n- Short-term mean reversion (2-10 trading days)\n- Liquid equities\n- Avoid overtrading\n\nFor mean reversion, I want stocks that have moved excessively in one direction and are likely to snap back. The best candidates are those with:\n1. Large single-day moves\n2. Large distance from moving averages\n3. High volatility (shows movement potential)\n4. Preferably below MAs for bounce plays (or above for pullback plays)\n\nGiven the US region focus, I'll select 4 US stocks and 1 UK stock to make up the 5:\n\nFinal selection:\n1. GO_CFD.US - Best US candidate, extreme oversold\n2. JBLU_CFD.US - Good US candidate, oversold\n3. FBIN_CFD.US - Good US candidate, oversold\n4. DKNG_CFD.US - US candidate, oversold on longer timeframe\n5. FUTR_CFD.UK - Best overall non-US candidate to complete the set\n\nWait, let me recalculate scores more systematically. I should assign a mean_reversion_score (0-100) based on:\n- Magnitude of daily move (absolute value)\n- Distance from MA50 and MA200\n- Volatility level\n\nLet me create a scoring rubric:\n- Daily move >15%: 30 points\n- Daily move 10-15%: 25 points\n- Daily move 5-10%: 20 points\n- Daily move <5%: 10 points\n\n- Distance from MA200 >30%: 30 points\n- Distance 20-30%: 25 points\n- Distance 10-20%: 20 points\n- Distance <10%: 10 points\n\n- Volatility >150%: 20 points\n- Volatility 100-150%: 15 points\n- Volatility 75-100%: 10 points\n- Volatility <75%: 5 points\n\n- Distance from MA50 adds context but I'll focus on MA200 as primary trend\n\nLet me score the top candidates:\n\n**GO_CFD.US**:\n- Daily: -29.73% = 30 pts\n- Dist MA200: -47.21% = 30 pts\n- Vol: 144.93% = 15 pts\n- Total: 75 pts\n\n**FUTR_CFD.UK**:\n- Daily: -20.82% = 30 pts\n- Dist MA200: -37.68% = 30 pts\n- Vol: 153.59% = 20 pts\n- Total: 80 pts\n\n**OCDO_CFD.UK**:\n- Daily: -21.31% = 30 pts\n- Dist MA200: -14.07% = 20 pts\n- Vol: 240.96% = 20 pts\n- Total: 70 pts\n\n**AML_CFD.UK**:\n- Daily: -14.85% = 25 pts\n- Dist MA200: -34.96% = 30 pts\n- Vol: 124.96% = 15 pts\n- Total: 70 pts\n\n**JBLU_CFD.US**:\n- Daily: -14.62% = 25 pts\n- Dist MA200: -2.42% = 10 pts\n- Vol: 135.18% = 15 pts\n- Total: 50 pts\n\n**FBIN_CFD.US**:\n- Daily: -8.43% = 20 pts\n- Dist MA200: -6.94% = 10 pts\n- Vol: 139.32% = 15 pts\n- Total: 45 pts\n\n**TRN_CFD.UK**:\n- Daily: -12.93% = 25 pts\n- Dist MA200: -22.56% = 25 pts\n- Vol: 131.09% = 15 pts\n- Total: 65 pts\n\n**PAGE_CFD.UK**:\n- Daily: -13.09% = 25 pts\n- Dist MA200: -20.51% = 25 pts\n- Vol: 113.15% = 15 pts\n- Total: 65 pts\n\n**DKNG_CFD.US**:\n- Daily: +7.39% = 20 pts\n- Dist MA200: -30.32% = 30 pts\n- Vol: 122.99% = 15 pts\n- Total: 65 pts\n\n**MCG_CFD.UK**:\n- Daily: +21.87% = 30 pts\n- Dist MA200: +10.17% = 20 pts (but above MA, so mean reversion would be short)\n- Vol: 211.42% = 20 pts\n- Total: 70 pts (but direction is opposite)\n\nGiven the US region focus, I'll prioritize US symbols but need 5 total. The best US candidates are GO, JBLU, FBIN, DKNG. I need one more, and FUTR is the strongest overall.\n\nBut wait, let me check the constraint again: \"Avoid sector concentration: max 1 per sector unless clearly justified (sector may be unknown)\". Since all sectors are unknown, this constraint is effectively \"max 1 per unknown sector\" which is meaningless. So I can select any 5.\n\nHowever, the region is specified as \"US\". This likely means I should focus on US-listed equities. But there are only 6 US symbols provided. Let me check if any of the non-US symbols could be considered \"US equities\" - no, they're UK, DE, FR, NL.\n\nI think the most reasonable interpretation is: prioritize US symbols, but if there aren't enough strong candidates, supplement with non-US symbols to reach exactly 5. The alternative would be to select weak US candidates, which violates the spirit of the strategy.\n\nSo my final selection:\n1. GO_CFD.US (score 75)\n2. FUTR_CFD.UK (score 80) - best non-US\n3. OCDO_CFD.UK (score 70) - high vol\n4. AML_CFD.UK (score 70) - deep oversold\n5. DKNG_CFD.US (score 65) - US symbol, oversold\n\nWait, I should include more US symbols if possible. Let me reconsider:\n\nUS symbols scores:\n- GO: 75\n- JBLU: 50\n- FBIN: 45\n- DKNG: 65\n- BWXT: (would be low, above MAs)\n- DELL: (would be low, above MAs)\n\nSo only GO and DKNG are strong US candidates. JBLU and FBIN are moderate. I need to pick 5 total. \n\nGiven the US region, I should pick:\n1. GO_CFD.US (75)\n2. DKNG_CFD.US (65)\n3. JBLU_CFD.US (50)\n4. FBIN_CFD.US (45)\n5. FUTR_CFD.UK (80) - best non-US to complete\n\nThis gives me 4 US and 1 non-US. The scores are relative, so I can adjust them to be 0-100 scale. Let me normalize the scores of selected stocks.\n\nActually, the instruction says \"mean_reversion_score\": \"integer 0-100\". I should assign absolute scores, not relative rankings. Let me use my rubric more carefully.\n\nRevised scoring with more nuance:\n- Daily move weight: 40%\n- Distance from MA200 weight: 35%\n- Volatility weight: 25%\n\n**GO_CFD.US**:\n- Daily: -29.73% = 40 pts (max)\n- Dist MA200: -47.21% = 35 pts (max)\n- Vol: 144.93% = 20 pts (high)\n- Total: 95\n\n**FUTR_CFD.UK**:\n- Daily: -20.82% = 38 pts\n- Dist MA200: -37.68% = 35 pts",
          "reasoning_details": [
            {
              "text": "  The user wants me to perform a \"stage1_universe_scan\" task for the \"meanrev-v1\" strategy. I need to:\n1. Select exactly 5 candidates from the provided universe\n2. Focus on short-term mean reversion in liquid equities\n3. Avoid earnings within 5 trading days (if known) - but none are known\n4. Avoid highly binary/event-driven moves (if known) - but none are known\n5. Avoid sector concentration: max 1 per sector unless clearly justified (sector may be unknown) - all sectors are unknown/empty\n6. Output only valid JSON\n7. Not invent any data\n\nThe universe contains a mix of UK, US, DE, FR, and NL CFDs. Since the region is \"US\", I should focus on US symbols. Let me filter for US symbols:\n\nUS symbols in the universe:\n- GO_CFD.US (Grocery Outlet Holding Corp)\n- DKNG_CFD.US (DraftKings Inc)\n- JBLU_CFD.US (JETBLUE AIRWAYS CORP)\n- BWXT_CFD.US (BWX Technologies Inc)\n- FBIN_CFD.US (Fortune Brands Innovations Inc)\n- DELL_CFD.US (DELL TECHNOLOGIES -C)\n\nThat's only 6 US symbols. The task says \"Select exactly 5 candidates\" but the region is US. This is a bit ambiguous. Should I only select from US symbols or can I select from the entire universe? The strategy is for US region, so I should prioritize US symbols. But there are only 6 US symbols, and I need to select 5. Let me check if any of these are clearly unsuitable.\n\nFor mean reversion, I want:\n- Large moves in either direction (overextended)\n- High volatility (means opportunity for reversion)\n- Distance from moving averages (shows overextension)\n\nLet me evaluate each US symbol:\n\n1. **GO_CFD.US**: -29.73% change, -47% from MA200, -28.6% from MA50, 144.9% volatility. This is a strong candidate - huge drop, well below both MAs, high volatility.\n\n2. **DKNG_CFD.US**: +7.39% change, -30.3% from MA200, -13.7% from MA50, 123% volatility. Below MAs but positive move today. Could be a candidate for continuation or mean reversion.\n\n3. **JBLU_CFD.US**: -14.62% change, -2.4% from MA200, -10.8% from MA50, 135% volatility. Below MAs, large drop, high volatility. Good candidate.\n\n4. **BWXT_CFD.US**: -1.88% change, +15.3% from MA200, +0.67% from MA50, 92.9% volatility. Above MAs, small move. Not a strong mean reversion candidate.\n\n5. **FBIN_CFD.US**: -8.43% change, -6.9% from MA200, -10.2% from MA50, 139.3% volatility. Below MAs, decent drop, high volatility. Good candidate.\n\n6. **DELL_CFD.US**: +0.65% change, +14.4% from MA200, +20.4% from MA50, 141.2% volatility. Well above MAs, small positive move. Not ideal for mean reversion.\n\nSo from US symbols, the best candidates are: GO, JBLU, FBIN, DKNG. That's only 4. I need 5.\n\nSince all sectors are unknown/empty, the sector concentration constraint is effectively moot. I can select from the entire universe if needed. Let me look at non-US symbols that show strong mean reversion signals:\n\nStrong candidates from the full universe:\n\n- **PAGE_CFD.UK**: -13.09% change, -20.5% from MA200, -9.5% from MA50, 113% volatility. Good candidate.\n- **MCG_CFD.UK**: +21.87% change, +10.2% from MA200, +28.7% from MA50, 211% volatility. Strong upward move, extended above MAs. Good candidate for downward reversion.\n- **UTG_CFD.UK**: +3.46% change, -23.9% from MA200, -3.7% from MA50, 73.8% volatility. Below MAs but positive move.\n- **TRN_CFD.UK**: -12.93% change, -22.6% from MA200, -12.6% from MA50, 131% volatility. Good candidate.\n- **DLN_CFD.UK**: +10.40% change, +5.1% from MA200, +12.2% from MA50, 115% volatility. Extended above MAs.\n- **FUTR_CFD.UK**: -20.82% change, -37.7% from MA200, -24.3% from MA50, 153.6% volatility. Very strong candidate - huge drop, well below MAs.\n- **OCDO_CFD.UK**: -21.31% change, -14.1% from MA200, -3.2% from MA50, 241% volatility. Very strong candidate - huge drop, extremely high volatility.\n- **AML_CFD.UK**: -14.85% change, -35% from MA200, -24.2% from MA50, 125% volatility. Strong candidate.\n- **GXI_CFD.DE**: +14.73% change, -49.2% from MA200, -24.8% from MA50, 234% volatility. Interesting - big positive move but still well below MAs.\n- **PZC_CFD.UK**: -10.30% change, +8.4% from MA200, +8.1% from MA50, 91% volatility. Below MAs but still above them.\n\nGiven that I need 5 candidates and only 4 US symbols are strong candidates, I should include one non-US symbol. Since sectors are all unknown, I can justify this.\n\nLet me rank the best candidates overall:\n\n1. **GO_CFD.US**: -29.73%, -47% from MA200, 144.9% vol - extreme oversold\n2. **FUTR_CFD.UK**: -20.82%, -37.7% from MA200, 153.6% vol - extreme oversold\n3. **OCDO_CFD.UK**: -21.31%, -14.1% from MA200, 241% vol - huge drop, highest vol\n4. **JBLU_CFD.US**: -14.62%, -2.4% from MA200, 135% vol - strong drop\n5. **FBIN_CFD.US**: -8.43%, -6.9% from MA200, 139.3% vol - decent setup\n6. **AML_CFD.UK**: -14.85%, -35% from MA200, 125% vol - strong candidate\n7. **TRN_CFD.UK**: -12.93%, -22.6% from MA200, 131% vol - strong candidate\n8. **PAGE_CFD.UK**: -13.09%, -20.5% from MA200, 113% vol - strong candidate\n9. **DKNG_CFD.US**: +7.39%, -30% from MA200, 123% vol - below MAs but positive today\n10. **MCG_CFD.UK**: +21.87%, +10% from MA200, 211% vol - extended up\n\nFor mean reversion, I want the most extreme moves away from MAs. The best signals are:\n- GO_CFD.US (massive drop)\n- FUTR_CFD.UK (massive drop)\n- OCDO_CFD.UK (massive drop, highest vol)\n- AML_CFD.UK (big drop)\n- JBLU_CFD.US or FBIN_CFD.US or TRN_CFD.UK\n\nSince the region is US, I should prioritize US symbols. Let me select:\n1. GO_CFD.US (best US candidate)\n2. JBLU_CFD.US (good US candidate)\n3. FBIN_CFD.US (good US candidate)\n4. DKNG_CFD.US (US symbol, though positive today, still oversold longer term)\n5. FUTR_CFD.UK (best non-US candidate to complete the 5)\n\nWait, let me reconsider. The region is \"US\" which might mean I should ONLY consider US symbols. But there are only 6 US symbols and I need to select 5. Let me check if I can make a case for 5 US symbols:\n\nUS symbols evaluation for mean reversion:\n- GO_CFD.US: Excellent - extreme oversold\n- JBLU_CFD.US: Good - oversold, high vol\n- FBIN_CFD.US: Good - oversold, high vol\n- DKNG_CFD.US: Moderate - oversold on longer timeframe but positive today, might need more time\n- BWXT_CFD.US: Poor - above MAs, not extended\n- DELL_CFD.US: Poor - well above MAs, not extended\n\nThat's only 4 good US candidates. The instructions say \"Select exactly 5 candidates\". This is a constraint I must follow. Since there aren't 5 strong US candidates, I must include non-US symbols. The sector constraint is moot since all sectors are unknown.\n\nLet me select the 5 strongest mean reversion signals from the entire universe:\n\n1. **GO_CFD.US**: Score 95 - Extreme oversold, -29.7% day, -47% from MA200, 144.9% vol\n2. **FUTR_CFD.UK**: Score 90 - Extreme oversold, -20.8% day, -37.7% from MA200, 153.6% vol\n3. **OCDO_CFD.UK**: Score 88 - Extreme drop, -21.3% day, -14% from MA200, 241% vol (highest)\n4. **AML_CFD.UK**: Score 85 - Strong oversold, -14.9% day, -35% from MA200, 125% vol\n5. **JBLU_CFD.US**: Score 82 - Good oversold, -14.6% day, -2.4% from MA200, 135% vol\n\nAlternative: Could include FBIN_CFD.US instead of AML_CFD.UK to have more US exposure.\n\nLet me think about the strategy. It's \"Two-Stage LLM Mean-Reversion (Arena v1)\" for US region. The key is:\n- Short-term mean reversion (2-10 trading days)\n- Liquid equities\n- Avoid overtrading\n\nFor mean reversion, I want stocks that have moved excessively in one direction and are likely to snap back. The best candidates are those with:\n1. Large single-day moves\n2. Large distance from moving averages\n3. High volatility (shows movement potential)\n4. Preferably below MAs for bounce plays (or above for pullback plays)\n\nGiven the US region focus, I'll select 4 US stocks and 1 UK stock to make up the 5:\n\nFinal selection:\n1. GO_CFD.US - Best US candidate, extreme oversold\n2. JBLU_CFD.US - Good US candidate, oversold\n3. FBIN_CFD.US - Good US candidate, oversold\n4. DKNG_CFD.US - US candidate, oversold on longer timeframe\n5. FUTR_CFD.UK - Best overall non-US candidate to complete the set\n\nWait, let me recalculate scores more systematically. I should assign a mean_reversion_score (0-100) based on:\n- Magnitude of daily move (absolute value)\n- Distance from MA50 and MA200\n- Volatility level\n\nLet me create a scoring rubric:\n- Daily move >15%: 30 points\n- Daily move 10-15%: 25 points\n- Daily move 5-10%: 20 points\n- Daily move <5%: 10 points\n\n- Distance from MA200 >30%: 30 points\n- Distance 20-30%: 25 points\n- Distance 10-20%: 20 points\n- Distance <10%: 10 points\n\n- Volatility >150%: 20 points\n- Volatility 100-150%: 15 points\n- Volatility 75-100%: 10 points\n- Volatility <75%: 5 points\n\n- Distance from MA50 adds context but I'll focus on MA200 as primary trend\n\nLet me score the top candidates:\n\n**GO_CFD.US**:\n- Daily: -29.73% = 30 pts\n- Dist MA200: -47.21% = 30 pts\n- Vol: 144.93% = 15 pts\n- Total: 75 pts\n\n**FUTR_CFD.UK**:\n- Daily: -20.82% = 30 pts\n- Dist MA200: -37.68% = 30 pts\n- Vol: 153.59% = 20 pts\n- Total: 80 pts\n\n**OCDO_CFD.UK**:\n- Daily: -21.31% = 30 pts\n- Dist MA200: -14.07% = 20 pts\n- Vol: 240.96% = 20 pts\n- Total: 70 pts\n\n**AML_CFD.UK**:\n- Daily: -14.85% = 25 pts\n- Dist MA200: -34.96% = 30 pts\n- Vol: 124.96% = 15 pts\n- Total: 70 pts\n\n**JBLU_CFD.US**:\n- Daily: -14.62% = 25 pts\n- Dist MA200: -2.42% = 10 pts\n- Vol: 135.18% = 15 pts\n- Total: 50 pts\n\n**FBIN_CFD.US**:\n- Daily: -8.43% = 20 pts\n- Dist MA200: -6.94% = 10 pts\n- Vol: 139.32% = 15 pts\n- Total: 45 pts\n\n**TRN_CFD.UK**:\n- Daily: -12.93% = 25 pts\n- Dist MA200: -22.56% = 25 pts\n- Vol: 131.09% = 15 pts\n- Total: 65 pts\n\n**PAGE_CFD.UK**:\n- Daily: -13.09% = 25 pts\n- Dist MA200: -20.51% = 25 pts\n- Vol: 113.15% = 15 pts\n- Total: 65 pts\n\n**DKNG_CFD.US**:\n- Daily: +7.39% = 20 pts\n- Dist MA200: -30.32% = 30 pts\n- Vol: 122.99% = 15 pts\n- Total: 65 pts\n\n**MCG_CFD.UK**:\n- Daily: +21.87% = 30 pts\n- Dist MA200: +10.17% = 20 pts (but above MA, so mean reversion would be short)\n- Vol: 211.42% = 20 pts\n- Total: 70 pts (but direction is opposite)\n\nGiven the US region focus, I'll prioritize US symbols but need 5 total. The best US candidates are GO, JBLU, FBIN, DKNG. I need one more, and FUTR is the strongest overall.\n\nBut wait, let me check the constraint again: \"Avoid sector concentration: max 1 per sector unless clearly justified (sector may be unknown)\". Since all sectors are unknown, this constraint is effectively \"max 1 per unknown sector\" which is meaningless. So I can select any 5.\n\nHowever, the region is specified as \"US\". This likely means I should focus on US-listed equities. But there are only 6 US symbols provided. Let me check if any of the non-US symbols could be considered \"US equities\" - no, they're UK, DE, FR, NL.\n\nI think the most reasonable interpretation is: prioritize US symbols, but if there aren't enough strong candidates, supplement with non-US symbols to reach exactly 5. The alternative would be to select weak US candidates, which violates the spirit of the strategy.\n\nSo my final selection:\n1. GO_CFD.US (score 75)\n2. FUTR_CFD.UK (score 80) - best non-US\n3. OCDO_CFD.UK (score 70) - high vol\n4. AML_CFD.UK (score 70) - deep oversold\n5. DKNG_CFD.US (score 65) - US symbol, oversold\n\nWait, I should include more US symbols if possible. Let me reconsider:\n\nUS symbols scores:\n- GO: 75\n- JBLU: 50\n- FBIN: 45\n- DKNG: 65\n- BWXT: (would be low, above MAs)\n- DELL: (would be low, above MAs)\n\nSo only GO and DKNG are strong US candidates. JBLU and FBIN are moderate. I need to pick 5 total. \n\nGiven the US region, I should pick:\n1. GO_CFD.US (75)\n2. DKNG_CFD.US (65)\n3. JBLU_CFD.US (50)\n4. FBIN_CFD.US (45)\n5. FUTR_CFD.UK (80) - best non-US to complete\n\nThis gives me 4 US and 1 non-US. The scores are relative, so I can adjust them to be 0-100 scale. Let me normalize the scores of selected stocks.\n\nActually, the instruction says \"mean_reversion_score\": \"integer 0-100\". I should assign absolute scores, not relative rankings. Let me use my rubric more carefully.\n\nRevised scoring with more nuance:\n- Daily move weight: 40%\n- Distance from MA200 weight: 35%\n- Volatility weight: 25%\n\n**GO_CFD.US**:\n- Daily: -29.73% = 40 pts (max)\n- Dist MA200: -47.21% = 35 pts (max)\n- Vol: 144.93% = 20 pts (high)\n- Total: 95\n\n**FUTR_CFD.UK**:\n- Daily: -20.82% = 38 pts\n- Dist MA200: -37.68% = 35 pts",
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    "created": 1772735065,
    "provider": "Google"
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}