Arena run #52

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": "ATG_CFD.UK", "name": "ATG_CFD.UK", "sector": "", "last_price": 292.5, "change_1d_pct": -1.0152284263959421, "distance_from_ma200_pct": -33.84107948739843, "distance_from_ma50_pct": -5.828037166534672, "volatility_20d_pct": 158.17820784721184, "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": "BPT_CFD.UK", "name": "", "sector": "", "last_price": 274.2, "change_1d_pct": -5.912225920461179, "distance_from_ma200_pct": -11.483684525527371, "distance_from_ma50_pct": -7.545463557334964, "volatility_20d_pct": 77.69917499624198, "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": "BBOX_CFD.UK", "name": "", "sector": "", "last_price": 166.0, "change_1d_pct": 15.598885793871876, "distance_from_ma200_pct": 15.063751209988908, "distance_from_ma50_pct": 9.510960991667927, "volatility_20d_pct": 57.84262866116462, "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": "BYIT_CFD.UK", "name": "", "sector": "", "last_price": 304.8, "change_1d_pct": -9.92907801418439, "distance_from_ma200_pct": -27.18690998374248, "distance_from_ma50_pct": -13.74157791784395, "volatility_20d_pct": 86.40989379380683, "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": "", "sector": "", "last_price": 0.186, "change_1d_pct": 3.3333333333333437, "distance_from_ma200_pct": -13.132822716233882, "distance_from_ma50_pct": -6.098546042003239, "volatility_20d_pct": 289.85428872043053, "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": "BT_CFD.UK", "name": "", "sector": "", "last_price": 202.7, "change_1d_pct": 9.037116729424422, "distance_from_ma200_pct": 7.5002220805031605, "distance_from_ma50_pct": 9.900238559965292, "volatility_20d_pct": 80.0133471383762, "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": "CAR_CFD.US", "name": "", "sector": "", "last_price": 119.97, "change_1d_pct": 2.0239816310910763, "distance_from_ma200_pct": -15.465983461011612, "distance_from_ma50_pct": -5.580040925546992, "volatility_20d_pct": 75.0434760491137, "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": "ASGN_CFD.US", "name": "", "sector": "", "last_price": 50.97, "change_1d_pct": 2.2877784467188356, "distance_from_ma200_pct": 2.411605443065312, "distance_from_ma50_pct": 4.189663207986838, "volatility_20d_pct": 78.90566495955204, "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": "BDX_CFD.US", "name": "", "sector": "", "last_price": 208.67, "change_1d_pct": 1.379779429626371, "distance_from_ma200_pct": 11.477413629979605, "distance_from_ma50_pct": 4.4471762673110815, "volatility_20d_pct": 44.713843204767905, "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": "BFAM_CFD.US", "name": "", "sector": "", "last_price": 84.9, "change_1d_pct": -3.8287267784322565, "distance_from_ma200_pct": -23.001508227229895, "distance_from_ma50_pct": -13.575119406813807, "volatility_20d_pct": 50.45718157512095, "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": "BLND_CFD.UK", "name": "", "sector": "", "last_price": 419.0, "change_1d_pct": 1.305609284332676, "distance_from_ma200_pct": 12.579768072243436, "distance_from_ma50_pct": 5.858069340825067, "volatility_20d_pct": 83.6517211804937, "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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"last_price": 0.8, "change_1d_pct": -3.6144578313252906, "distance_from_ma200_pct": -28.624323046313894, "distance_from_ma50_pct": -13.358026295839021, "volatility_20d_pct": 123.9561977008674, "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": "CHT_CFD.US", "name": "", "sector": "", "last_price": 41.54, "change_1d_pct": -0.09620009620009418, "distance_from_ma200_pct": -4.015786329990223, "distance_from_ma50_pct": -0.521102745368518, "volatility_20d_pct": 24.954564057486404, "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": "CCC_CFD.UK", "name": "", "sector": "", "last_price": 3022.0, "change_1d_pct": 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"BARC_CFD.UK", "name": "", "sector": "", "last_price": 472.2, "change_1d_pct": -3.5440710856909474, "distance_from_ma200_pct": 22.127754114052635, "distance_from_ma50_pct": 0.8337899539478721, "volatility_20d_pct": 38.329163839573816, "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": "BRNK_CFD.DE", "name": "", "sector": "", "last_price": 1.99, "change_1d_pct": 0.25188916876575096, "distance_from_ma200_pct": 2.44372030290394, "distance_from_ma50_pct": 6.4091458393489065, "volatility_20d_pct": 103.1424091021338, "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": "BERY_CFD.US", "name": "", "sector": "", "last_price": 67.88, "change_1d_pct": -2.2887577371527357, "distance_from_ma200_pct": 0.1607618592304405, "distance_from_ma50_pct": -2.3899226366799975, "volatility_20d_pct": 69.71811673774233, "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": "BPOST_CFD.BE", "name": "", "sector": "", "last_price": 2.24, "change_1d_pct": -0.22271714922048602, "distance_from_ma200_pct": 8.12428500403053, "distance_from_ma50_pct": 8.528183412629975, "volatility_20d_pct": 57.61765640562978, "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": "ADP_CFD.US", "name": "", "sector": "", "last_price": 227.04, "change_1d_pct": -4.246973978322311, "distance_from_ma200_pct": -20.605390888363573, "distance_from_ma50_pct": -11.252526121167827, "volatility_20d_pct": 39.801787220025965, "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": "AZN_CFD.SE", "name": "", "sector": "", "last_price": 1703.0, "change_1d_pct": 1.2786202795123325, "distance_from_ma200_pct": 12.016370307834535, "distance_from_ma50_pct": -0.11144348642149193, "volatility_20d_pct": 38.270563233973185, "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": "AIZ_CFD.US", "name": "", "sector": "", "last_price": 243.94, "change_1d_pct": 1.0815066506443483, "distance_from_ma200_pct": 14.607418850087406, "distance_from_ma50_pct": 3.7723729135133777, "volatility_20d_pct": 35.24213160208557, "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": "BCP_CFD.PT", "name": "", "sector": "", "last_price": 0.924, "change_1d_pct": -1.2820512820512886, "distance_from_ma200_pct": 22.27397840355707, "distance_from_ma50_pct": 4.529616724738683, "volatility_20d_pct": 48.570699966330075, "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": "BMO_CFD.US", "name": "", "sector": "", "last_price": 143.19, "change_1d_pct": 2.34436423415052, "distance_from_ma200_pct": 19.3192826177079, "distance_from_ma50_pct": 7.758880192655027, "volatility_20d_pct": 37.643495462157084, "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": "CAG_CFD.US", "name": "", "sector": "", "last_price": 19.18, "change_1d_pct": 1.1070110701107083, "distance_from_ma200_pct": -0.7341429521500187, "distance_from_ma50_pct": 9.129806433992972, "volatility_20d_pct": 55.37971406673143, "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"}], "output_schema": {"selected_stocks": [{"symbol": "string", "mean_reversion_score": "integer 0-100", "selection_reason": "short, concrete, indicator-based"}], "rejected_common_reasons": ["string"]}}

{
  "raw": {
    "id": "gen-1770651881-LSoIMFuYuKszxuPnTZ6w",
    "model": "moonshotai/kimi-k2-thinking",
    "usage": {
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      "is_byok": false,
      "cost_details": {
        "upstream_inference_cost": 0.0150076,
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        "message": {
          "role": "assistant",
          "content": "{\"selected_stocks\": [{\"symbol\": \"ARW_CFD.US\", \"mean_reversion_score\": 98, \"selection_reason\": \"Extreme overextension: +32.7% from MA50, +30.4% from MA200",
          "refusal": null,
          "reasoning": "The user wants me to perform a \"stage1_universe_scan\" for the \"meanrev-v1\" strategy. Let me break down the requirements:\n\n1. **Task**: Stage 1 universe scan for mean reversion\n2. **Region**: US (but the universe includes many non-US symbols)\n3. **Strategy**: Two-Stage LLM Mean-Reversion (Arena v1)\n   - max_positions: 10\n   - max_buys_per_run: 2\n   - avoid_overtrading: true\n   - max_sells_per_run: 2\n   - max_gross_leverage: 3.0\n   - fixed_position_size: 3000.0\n4. **Selection Rules**:\n   - Horizon: 2-10 trading days\n   - Target: short-term mean reversion in liquid equities\n   - Constraints:\n     - Select exactly 5 candidates\n     - Avoid earnings within 5 trading days (if known)\n     - Avoid highly binary/event-driven moves (if known)\n     - Avoid sector concentration: max 1 per sector unless clearly justified (sector may be unknown)\n\n**Key points for mean reversion strategy**:\n- Look for stocks that have moved significantly away from their moving averages (overextended)\n- Prefer stocks that have moved sharply in one direction (up or down) and are likely to revert\n- High volatility can be good for mean reversion setups\n- Need to avoid stocks with upcoming earnings or event risk\n\n**Data limitations**:\n- Most stocks have no sector information\n- No earnings dates known (all null)\n- No news sentiment or headlines\n- No market cap or volume data\n- Only technical data available: price, distances from MA200/MA50, 20d volatility, 1d change\n\n**Approach**:\nSince I need to select exactly 5 candidates and most sector data is missing, I'll focus on:\n1. **Overextended conditions**: Large distance from moving averages (both positive and negative)\n2. **Recent sharp moves**: Large 1-day changes\n3. **Reasonable volatility**: Not too low (no opportunity) or excessively high (too risky)\n4. **Liquidity proxy**: Though not explicitly given, I'll assume the CFDs are liquid enough\n\nFor mean reversion, I want stocks that have:\n- **Oversold candidates**: Large negative distance from MAs + large negative 1-day move\n- **Overbought candidates**: Large positive distance from MAs + large positive 1-day move\n\nLet me analyze the universe:\n\n**US symbols** (since region is US, but the universe is mixed):\n- CAR_CFD.US: -15.47% from MA200, -5.58% from MA50, +2.02% today, vol 75.04%\n- ASGN_CFD.US: +2.41% from MA200, +4.19% from MA50, +2.29% today, vol 78.91%\n- BDX_CFD.US: +11.48% from MA200, +4.45% from MA50, +1.38% today, vol 44.71%\n- BFAM_CFD.US: -23.00% from MA200, -13.58% from MA50, -3.83% today, vol 50.46%\n- BRO_CFD.US: -21.51% from MA200, -6.60% from MA50, +2.81% today, vol 57.53%\n- CCK_CFD.US: +10.90% from MA200, +7.47% from MA50, -0.75% today, vol 47.16%\n- AJG_CFD.US: -18.13% from MA200, -5.80% from MA50, -2.83% today, vol 59.13%\n- AMCX_CFD.US: +2.72% from MA200, -13.62% from MA50, -1.16% today, vol 75.95%\n- BBY_CFD.US: -5.90% from MA200, -3.16% from MA50, +3.33% today, vol 68.19%\n- BERY_CFD.US: +0.16% from MA200, -2.39% from MA50, -2.29% today, vol 69.72%\n- CHT_CFD.US: -4.02% from MA200, -0.52% from MA50, -0.10% today, vol 24.95%\n- CBRE_CFD.US: +11.65% from MA200, +2.69% from MA50, +2.02% today, vol 44.59%\n- CE_CFD.US: +15.83% from MA200, +22.67% from MA50, +17.38% today, vol 112.38%\n- ARW_CFD.US: +30.42% from MA200, +32.68% from MA50, +17.46% today, vol 67.33%\n- ABBV_CFD.US: +5.26% from MA200, -1.31% from MA50, -2.62% today, vol 73.26%\n- ADP_CFD.US: -20.61% from MA200, -11.25% from MA50, -4.25% today, vol 39.80%\n- ALL_CFD.US: +2.30% from MA200, +1.42% from MA50, +2.14% today, vol 51.84%\n- BMY_CFD.US: +26.07% from MA200, +12.94% from MA50, +8.96% today, vol 60.00%\n- AIZ_CFD.US: +14.61% from MA200, +3.77% from MA50, +1.08% today, vol 35.24%\n- CAG_CFD.US: -0.73% from MA200, +9.13% from MA50, +1.11% today, vol 55.38%\n\n**Non-US symbols** (but still in universe):\n- Many UK, DE, FR, DK, PL, BE, PT, SE symbols\n\nSince the region is specified as \"US\", I should prioritize US symbols, but the strategy doesn't explicitly say to exclude non-US. The universe includes them, so I can consider them. However, the strategy name mentions \"Arena v1\" and typical mean reversion strategies focus on liquid equities. I'll prioritize US symbols as the region is US.\n\n**Selection criteria**:\n1. **Oversold bounce candidates**: Large negative distance from MAs + recent down move\n2. **Overbought fade candidates**: Large positive distance from MAs + recent up move\n3. **Volatility**: 40-120% range seems reasonable\n4. **No earnings risk**: All have null earnings dates, so this constraint is satisfied\n5. **No event risk**: No news data, so I cannot assess this; I'll have to assume it's okay\n\nLet me score candidates based on mean reversion potential:\n\n**Strong oversold candidates**:\n- BFAM_CFD.US: -23% from MA200, -13.58% from MA50, -3.83% today, vol 50.46% - **Strong**\n- ADP_CFD.US: -20.61% from MA200, -11.25% from MA50, -4.25% today, vol 39.80% - **Strong**\n- BRO_CFD.US: -21.51% from MA200, -6.60% from MA50, +2.81% today, vol 57.53% - **Good (potential early reversal)**\n- AJG_CFD.US: -18.13% from MA200, -5.80% from MA50, -2.83% today, vol 59.13% - **Good**\n- CAR_CFD.US: -15.47% from MA200, -5.58% from MA50, +2.02% today, vol 75.04% - **Good**\n\n**Strong overbought candidates**:\n- CE_CFD.US: +15.83% from MA200, +22.67% from MA50, +17.38% today, vol 112.38% - **Very Strong (huge move)**\n- ARW_CFD.US: +30.42% from MA200, +32.68% from MA50, +17.46% today, vol 67.33% - **Very Strong (huge move)**\n- BMY_CFD.US: +26.07% from MA200, +12.94% from MA50, +8.96% today, vol 60.00% - **Strong**\n- AA_CFD.US: +59.35% from MA200, +9.36% from MA50, -1.28% today, vol 113.71% - **Extreme (but might be too extended)**\n- BLDR_CFD.US: +3.22% from MA200, +9.33% from MA50, +5.37% today, vol 93.51% - **Moderate**\n\n**Mixed signals**:\n- AMCX_CFD.US: +2.72% from MA200, -13.62% from MA50, -1.16% today, vol 75.95% - **Good (short-term oversold)**\n\nI need exactly 5 candidates. I should diversify between oversold and overbought setups. Since sector data is mostly unknown, I cannot enforce the sector concentration rule strictly, but I'll try to pick different types of stocks.\n\n**My picks**:\n1. **CE_CFD.US** - Overbought fade candidate (massive +17% day, extended from MAs)\n2. **BFAM_CFD.US** - Oversold bounce candidate (deeply below MAs, down day)\n3. **ARW_CFD.US** - Overbought fade candidate (extremely extended, huge move)\n4. **ADP_CFD.US** - Oversold bounce candidate (deeply below MAs, down day)\n5. **AJG_CFD.US** - Oversold bounce candidate (extended below MAs, down day)\n\nWait, let me reconsider. I should have a better mix and consider the volatility levels. Also, I should check if some of these moves might be event-driven. Since I have no news, I have to assume they're not.\n\nLet me re-evaluate with scoring:\n\n**Scoring logic** (0-100):\n- Distance from MA50: Absolute value >10% = high score\n- Distance from MA200: Absolute value >15% = high score\n- 1-day change: Absolute value >3% = high score\n- Volatility: 40-100% = optimal range\n\n**Calculating scores**:\n\n1. **CE_CFD.US**: \n   - MA50: +22.67% (very extended)\n   - MA200: +15.83% (very extended)\n   - 1d: +17.38% (huge move)\n   - Vol: 112.38% (high but acceptable)\n   - Score: 95 (extreme overbought)\n\n2. **BFAM_CFD.US**:\n   - MA50: -13.58% (very extended)\n   - MA200: -23.00% (very extended)\n   - 1d: -3.83% (significant down)\n   - Vol: 50.46% (good)\n   - Score: 90 (deeply oversold)\n\n3. **ARW_CFD.US**:\n   - MA50: +32.68% (extremely extended)\n   - MA200: +30.42% (extremely extended)\n   - 1d: +17.46% (huge move)\n   - Vol: 67.33% (good)\n   - Score: 98 (extreme overbought)\n\n4. **ADP_CFD.US**:\n   - MA50: -11.25% (very extended)\n   - MA200: -20.61% (very extended)\n   - 1d: -4.25% (significant down)\n   - Vol: 39.80% (slightly low but ok)\n   - Score: 85 (deeply oversold)\n\n5. **AJG_CFD.US**:\n   - MA50: -5.80% (moderately extended)\n   - MA200: -18.13% (very extended)\n   - 1d: -2.83% (down)\n   - Vol: 59.13% (good)\n   - Score: 75 (oversold)\n\n6. **BRO_CFD.US**:\n   - MA50: -6.60% (moderately extended)\n   - MA200: -21.51% (very extended)\n   - 1d: +2.81% (up - potential reversal)\n   - Vol: 57.53% (good)\n   - Score: 78 (potentially reversing)\n\n7. **CAR_CFD.US**:\n   - MA50: -5.58% (moderately extended)\n   - MA200: -15.47% (very extended)\n   - 1d: +2.02% (up - potential reversal)\n   - Vol: 75.04% (good)\n   - Score: 76 (potentially reversing)\n\n8. **AMCX_CFD.US**:\n   - MA50: -13.62% (very extended)\n   - MA200: +2.72% (neutral long-term)\n   - 1d: -1.16% (slight down)\n   - Vol: 75.95% (good)\n   - Score: 72 (short-term oversold)\n\n9. **BMY_CFD.US**:\n   - MA50: +12.94% (very extended)\n   - MA200: +26.07% (very extended)\n   - 1d: +8.96% (strong up)\n   - Vol: 60.00% (good)\n   - Score: 88 (strong overbought)\n\n10. **AA_CFD.US**:\n    - MA50: +9.36% (extended)\n    - MA200: +59.35% (extremely extended)\n    - 1d: -1.28% (slight down)\n    - Vol: 113.71% (high)\n    - Score: 85 (very extended, but maybe too extreme)\n\nI need to select exactly 5. I should pick the best setups with highest scores and good diversification. Since sector data is unknown, I'll just pick the best technical setups.\n\n**Final selection**:\n1. **ARW_CFD.US** - Score 98 (overbought)\n2. **CE_CFD.US** - Score 95 (overbought)\n3. **BFAM_CFD.US** - Score 90 (oversold)\n4. **BMY_CFD.US** - Score 88 (overbought)\n5. **ADP_CFD.US** - Score 85 (oversold)\n\nThis gives me 3 overbought and 2 oversold candidates. Good mix.\n\nWait, let me double-check the constraints:\n- \"Avoid earnings within 5 trading days (if known)\" - All earnings are null, so this is satisfied\n- \"Avoid highly binary/event-driven moves (if known)\" - No news data, so I cannot assess this. I have to assume it's okay.\n- \"Avoid sector concentration: max 1 per sector unless clearly justified (sector may be unknown)\" - All sectors are unknown/empty, so this constraint is effectively not enforceable. I'll proceed with the best 5.\n\nLet me refine the selection_reason to be short, concrete, and indicator-based:\n\n1. **ARW_CFD.US**: \"Extremely overextended: +32.7% from MA50, +30.4% from MA200, +17.5% today. High volatility setup for mean reversion.\"\n2. **CE_CFD.US**: \"Sharply overbought: +22.7% from MA50, +15.8% from MA200, +17.4% today. Volatility 112% supports reversion.\"\n3. **BFAM_CFD.US**: \"Deeply oversold: -13.6% from MA50, -23.0% from MA200, -3.8% today. Volatility 50% offers reversion opportunity.\"\n4. **BMY_CFD.US**: \"Overextended rally: +12.9% from MA50, +26.1% from MA200, +9.0% today. Mature bounce candidate.\"\n5. **ADP_CFD.US**: \"Oversold breakdown: -11.3% from MA50, -20.6% from MA200, -4.3% today. Approaching support for reversion.\"\n\nActually, I should make the reasons even shorter and more concrete as per the schema requirement.\n\nLet me also consider if I should include any non-US symbols. The region is \"US\", but the universe includes others. The strategy doesn't explicitly restrict to US-only symbols. However, the \"region\" field in the task is \"US\", which suggests I should focus on US symbols. I'll stick to US symbols.\n\nOne more check: Are there any symbols that are too illiquid or have too low volatility? The volatility range is 35-113% for my selections, which is reasonable. ADP has 39.8% which is borderline but acceptable.\n\nLet me finalize my picks:\n\n1. **ARW_CFD.US** - Mean reversion score: 98\n2. **CE_CFD.US** - Mean reversion score: 95\n3. **BFAM_CFD.US** - Mean reversion score: 90\n4. **BMY_CFD.US** - Mean reversion score: 88\n5. **ADP_CFD.US** - Mean reversion score: 85\n\nThese are the top 5 scores. The reasons should be concise and mention the key indicators.\n\n**Rejection reasons**: I should also provide rejected_common_reasons. Since I don't have a explicit rejection list, I'll think about common reasons why others were rejected:\n- Not sufficiently extended from MAs\n- Volatility too low or too high\n- Mixed signals (e.g., above MA200 but below MA50 without clear overextension)\n- Recent move too small for mean reversion setup\n\nLet me create the final JSON output.",
          "reasoning_details": [
            {
              "text": "The user wants me to perform a \"stage1_universe_scan\" for the \"meanrev-v1\" strategy. Let me break down the requirements:\n\n1. **Task**: Stage 1 universe scan for mean reversion\n2. **Region**: US (but the universe includes many non-US symbols)\n3. **Strategy**: Two-Stage LLM Mean-Reversion (Arena v1)\n   - max_positions: 10\n   - max_buys_per_run: 2\n   - avoid_overtrading: true\n   - max_sells_per_run: 2\n   - max_gross_leverage: 3.0\n   - fixed_position_size: 3000.0\n4. **Selection Rules**:\n   - Horizon: 2-10 trading days\n   - Target: short-term mean reversion in liquid equities\n   - Constraints:\n     - Select exactly 5 candidates\n     - Avoid earnings within 5 trading days (if known)\n     - Avoid highly binary/event-driven moves (if known)\n     - Avoid sector concentration: max 1 per sector unless clearly justified (sector may be unknown)\n\n**Key points for mean reversion strategy**:\n- Look for stocks that have moved significantly away from their moving averages (overextended)\n- Prefer stocks that have moved sharply in one direction (up or down) and are likely to revert\n- High volatility can be good for mean reversion setups\n- Need to avoid stocks with upcoming earnings or event risk\n\n**Data limitations**:\n- Most stocks have no sector information\n- No earnings dates known (all null)\n- No news sentiment or headlines\n- No market cap or volume data\n- Only technical data available: price, distances from MA200/MA50, 20d volatility, 1d change\n\n**Approach**:\nSince I need to select exactly 5 candidates and most sector data is missing, I'll focus on:\n1. **Overextended conditions**: Large distance from moving averages (both positive and negative)\n2. **Recent sharp moves**: Large 1-day changes\n3. **Reasonable volatility**: Not too low (no opportunity) or excessively high (too risky)\n4. **Liquidity proxy**: Though not explicitly given, I'll assume the CFDs are liquid enough\n\nFor mean reversion, I want stocks that have:\n- **Oversold candidates**: Large negative distance from MAs + large negative 1-day move\n- **Overbought candidates**: Large positive distance from MAs + large positive 1-day move\n\nLet me analyze the universe:\n\n**US symbols** (since region is US, but the universe is mixed):\n- CAR_CFD.US: -15.47% from MA200, -5.58% from MA50, +2.02% today, vol 75.04%\n- ASGN_CFD.US: +2.41% from MA200, +4.19% from MA50, +2.29% today, vol 78.91%\n- BDX_CFD.US: +11.48% from MA200, +4.45% from MA50, +1.38% today, vol 44.71%\n- BFAM_CFD.US: -23.00% from MA200, -13.58% from MA50, -3.83% today, vol 50.46%\n- BRO_CFD.US: -21.51% from MA200, -6.60% from MA50, +2.81% today, vol 57.53%\n- CCK_CFD.US: +10.90% from MA200, +7.47% from MA50, -0.75% today, vol 47.16%\n- AJG_CFD.US: -18.13% from MA200, -5.80% from MA50, -2.83% today, vol 59.13%\n- AMCX_CFD.US: +2.72% from MA200, -13.62% from MA50, -1.16% today, vol 75.95%\n- BBY_CFD.US: -5.90% from MA200, -3.16% from MA50, +3.33% today, vol 68.19%\n- BERY_CFD.US: +0.16% from MA200, -2.39% from MA50, -2.29% today, vol 69.72%\n- CHT_CFD.US: -4.02% from MA200, -0.52% from MA50, -0.10% today, vol 24.95%\n- CBRE_CFD.US: +11.65% from MA200, +2.69% from MA50, +2.02% today, vol 44.59%\n- CE_CFD.US: +15.83% from MA200, +22.67% from MA50, +17.38% today, vol 112.38%\n- ARW_CFD.US: +30.42% from MA200, +32.68% from MA50, +17.46% today, vol 67.33%\n- ABBV_CFD.US: +5.26% from MA200, -1.31% from MA50, -2.62% today, vol 73.26%\n- ADP_CFD.US: -20.61% from MA200, -11.25% from MA50, -4.25% today, vol 39.80%\n- ALL_CFD.US: +2.30% from MA200, +1.42% from MA50, +2.14% today, vol 51.84%\n- BMY_CFD.US: +26.07% from MA200, +12.94% from MA50, +8.96% today, vol 60.00%\n- AIZ_CFD.US: +14.61% from MA200, +3.77% from MA50, +1.08% today, vol 35.24%\n- CAG_CFD.US: -0.73% from MA200, +9.13% from MA50, +1.11% today, vol 55.38%\n\n**Non-US symbols** (but still in universe):\n- Many UK, DE, FR, DK, PL, BE, PT, SE symbols\n\nSince the region is specified as \"US\", I should prioritize US symbols, but the strategy doesn't explicitly say to exclude non-US. The universe includes them, so I can consider them. However, the strategy name mentions \"Arena v1\" and typical mean reversion strategies focus on liquid equities. I'll prioritize US symbols as the region is US.\n\n**Selection criteria**:\n1. **Oversold bounce candidates**: Large negative distance from MAs + recent down move\n2. **Overbought fade candidates**: Large positive distance from MAs + recent up move\n3. **Volatility**: 40-120% range seems reasonable\n4. **No earnings risk**: All have null earnings dates, so this constraint is satisfied\n5. **No event risk**: No news data, so I cannot assess this; I'll have to assume it's okay\n\nLet me score candidates based on mean reversion potential:\n\n**Strong oversold candidates**:\n- BFAM_CFD.US: -23% from MA200, -13.58% from MA50, -3.83% today, vol 50.46% - **Strong**\n- ADP_CFD.US: -20.61% from MA200, -11.25% from MA50, -4.25% today, vol 39.80% - **Strong**\n- BRO_CFD.US: -21.51% from MA200, -6.60% from MA50, +2.81% today, vol 57.53% - **Good (potential early reversal)**\n- AJG_CFD.US: -18.13% from MA200, -5.80% from MA50, -2.83% today, vol 59.13% - **Good**\n- CAR_CFD.US: -15.47% from MA200, -5.58% from MA50, +2.02% today, vol 75.04% - **Good**\n\n**Strong overbought candidates**:\n- CE_CFD.US: +15.83% from MA200, +22.67% from MA50, +17.38% today, vol 112.38% - **Very Strong (huge move)**\n- ARW_CFD.US: +30.42% from MA200, +32.68% from MA50, +17.46% today, vol 67.33% - **Very Strong (huge move)**\n- BMY_CFD.US: +26.07% from MA200, +12.94% from MA50, +8.96% today, vol 60.00% - **Strong**\n- AA_CFD.US: +59.35% from MA200, +9.36% from MA50, -1.28% today, vol 113.71% - **Extreme (but might be too extended)**\n- BLDR_CFD.US: +3.22% from MA200, +9.33% from MA50, +5.37% today, vol 93.51% - **Moderate**\n\n**Mixed signals**:\n- AMCX_CFD.US: +2.72% from MA200, -13.62% from MA50, -1.16% today, vol 75.95% - **Good (short-term oversold)**\n\nI need exactly 5 candidates. I should diversify between oversold and overbought setups. Since sector data is mostly unknown, I cannot enforce the sector concentration rule strictly, but I'll try to pick different types of stocks.\n\n**My picks**:\n1. **CE_CFD.US** - Overbought fade candidate (massive +17% day, extended from MAs)\n2. **BFAM_CFD.US** - Oversold bounce candidate (deeply below MAs, down day)\n3. **ARW_CFD.US** - Overbought fade candidate (extremely extended, huge move)\n4. **ADP_CFD.US** - Oversold bounce candidate (deeply below MAs, down day)\n5. **AJG_CFD.US** - Oversold bounce candidate (extended below MAs, down day)\n\nWait, let me reconsider. I should have a better mix and consider the volatility levels. Also, I should check if some of these moves might be event-driven. Since I have no news, I have to assume they're not.\n\nLet me re-evaluate with scoring:\n\n**Scoring logic** (0-100):\n- Distance from MA50: Absolute value >10% = high score\n- Distance from MA200: Absolute value >15% = high score\n- 1-day change: Absolute value >3% = high score\n- Volatility: 40-100% = optimal range\n\n**Calculating scores**:\n\n1. **CE_CFD.US**: \n   - MA50: +22.67% (very extended)\n   - MA200: +15.83% (very extended)\n   - 1d: +17.38% (huge move)\n   - Vol: 112.38% (high but acceptable)\n   - Score: 95 (extreme overbought)\n\n2. **BFAM_CFD.US**:\n   - MA50: -13.58% (very extended)\n   - MA200: -23.00% (very extended)\n   - 1d: -3.83% (significant down)\n   - Vol: 50.46% (good)\n   - Score: 90 (deeply oversold)\n\n3. **ARW_CFD.US**:\n   - MA50: +32.68% (extremely extended)\n   - MA200: +30.42% (extremely extended)\n   - 1d: +17.46% (huge move)\n   - Vol: 67.33% (good)\n   - Score: 98 (extreme overbought)\n\n4. **ADP_CFD.US**:\n   - MA50: -11.25% (very extended)\n   - MA200: -20.61% (very extended)\n   - 1d: -4.25% (significant down)\n   - Vol: 39.80% (slightly low but ok)\n   - Score: 85 (deeply oversold)\n\n5. **AJG_CFD.US**:\n   - MA50: -5.80% (moderately extended)\n   - MA200: -18.13% (very extended)\n   - 1d: -2.83% (down)\n   - Vol: 59.13% (good)\n   - Score: 75 (oversold)\n\n6. **BRO_CFD.US**:\n   - MA50: -6.60% (moderately extended)\n   - MA200: -21.51% (very extended)\n   - 1d: +2.81% (up - potential reversal)\n   - Vol: 57.53% (good)\n   - Score: 78 (potentially reversing)\n\n7. **CAR_CFD.US**:\n   - MA50: -5.58% (moderately extended)\n   - MA200: -15.47% (very extended)\n   - 1d: +2.02% (up - potential reversal)\n   - Vol: 75.04% (good)\n   - Score: 76 (potentially reversing)\n\n8. **AMCX_CFD.US**:\n   - MA50: -13.62% (very extended)\n   - MA200: +2.72% (neutral long-term)\n   - 1d: -1.16% (slight down)\n   - Vol: 75.95% (good)\n   - Score: 72 (short-term oversold)\n\n9. **BMY_CFD.US**:\n   - MA50: +12.94% (very extended)\n   - MA200: +26.07% (very extended)\n   - 1d: +8.96% (strong up)\n   - Vol: 60.00% (good)\n   - Score: 88 (strong overbought)\n\n10. **AA_CFD.US**:\n    - MA50: +9.36% (extended)\n    - MA200: +59.35% (extremely extended)\n    - 1d: -1.28% (slight down)\n    - Vol: 113.71% (high)\n    - Score: 85 (very extended, but maybe too extreme)\n\nI need to select exactly 5. I should pick the best setups with highest scores and good diversification. Since sector data is unknown, I'll just pick the best technical setups.\n\n**Final selection**:\n1. **ARW_CFD.US** - Score 98 (overbought)\n2. **CE_CFD.US** - Score 95 (overbought)\n3. **BFAM_CFD.US** - Score 90 (oversold)\n4. **BMY_CFD.US** - Score 88 (overbought)\n5. **ADP_CFD.US** - Score 85 (oversold)\n\nThis gives me 3 overbought and 2 oversold candidates. Good mix.\n\nWait, let me double-check the constraints:\n- \"Avoid earnings within 5 trading days (if known)\" - All earnings are null, so this is satisfied\n- \"Avoid highly binary/event-driven moves (if known)\" - No news data, so I cannot assess this. I have to assume it's okay.\n- \"Avoid sector concentration: max 1 per sector unless clearly justified (sector may be unknown)\" - All sectors are unknown/empty, so this constraint is effectively not enforceable. I'll proceed with the best 5.\n\nLet me refine the selection_reason to be short, concrete, and indicator-based:\n\n1. **ARW_CFD.US**: \"Extremely overextended: +32.7% from MA50, +30.4% from MA200, +17.5% today. High volatility setup for mean reversion.\"\n2. **CE_CFD.US**: \"Sharply overbought: +22.7% from MA50, +15.8% from MA200, +17.4% today. Volatility 112% supports reversion.\"\n3. **BFAM_CFD.US**: \"Deeply oversold: -13.6% from MA50, -23.0% from MA200, -3.8% today. Volatility 50% offers reversion opportunity.\"\n4. **BMY_CFD.US**: \"Overextended rally: +12.9% from MA50, +26.1% from MA200, +9.0% today. Mature bounce candidate.\"\n5. **ADP_CFD.US**: \"Oversold breakdown: -11.3% from MA50, -20.6% from MA200, -4.3% today. Approaching support for reversion.\"\n\nActually, I should make the reasons even shorter and more concrete as per the schema requirement.\n\nLet me also consider if I should include any non-US symbols. The region is \"US\", but the universe includes others. The strategy doesn't explicitly restrict to US-only symbols. However, the \"region\" field in the task is \"US\", which suggests I should focus on US symbols. I'll stick to US symbols.\n\nOne more check: Are there any symbols that are too illiquid or have too low volatility? The volatility range is 35-113% for my selections, which is reasonable. ADP has 39.8% which is borderline but acceptable.\n\nLet me finalize my picks:\n\n1. **ARW_CFD.US** - Mean reversion score: 98\n2. **CE_CFD.US** - Mean reversion score: 95\n3. **BFAM_CFD.US** - Mean reversion score: 90\n4. **BMY_CFD.US** - Mean reversion score: 88\n5. **ADP_CFD.US** - Mean reversion score: 85\n\nThese are the top 5 scores. The reasons should be concise and mention the key indicators.\n\n**Rejection reasons**: I should also provide rejected_common_reasons. Since I don't have a explicit rejection list, I'll think about common reasons why others were rejected:\n- Not sufficiently extended from MAs\n- Volatility too low or too high\n- Mixed signals (e.g., above MA200 but below MA50 without clear overextension)\n- Recent move too small for mean reversion setup\n\nLet me create the final JSON output.",
              "type": "reasoning.text",
              "index": 0,
              "format": "unknown"
            }
          ]
        },
        "logprobs": null,
        "finish_reason": "length",
        "native_finish_reason": "length"
      }
    ],
    "created": 1770651881,
    "provider": "Moonshot AI",
    "system_fingerprint": "fpv0_acbd71c9"
  }
}

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": [], "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": [],
    "sell": []
  },
  "portfolio_rationale": "No candidate symbols provided for evaluation. Current portfolio is empty. Cannot generate BUY signals without candidates. No positions to SELL or HOLD. Awaiting candidate list to proceed with mean-reversion analysis."
}

{
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    "model": "moonshotai/kimi-k2-thinking",
    "usage": {
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      "is_byok": false,
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        "upstream_inference_prompt_cost": 0.0050076,
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      {
        "index": 0,
        "message": {
          "role": "assistant",
          "content": "{\"selected_stocks\": [{\"symbol\": \"ARW_CFD.US\", \"mean_reversion_score\": 98, \"selection_reason\": \"Extreme overextension: +32.7% from MA50, +30.4% from MA200",
          "refusal": null,
          "reasoning": "The user wants me to perform a \"stage1_universe_scan\" for the \"meanrev-v1\" strategy. Let me break down the requirements:\n\n1. **Task**: Stage 1 universe scan for mean reversion\n2. **Region**: US (but the universe includes many non-US symbols)\n3. **Strategy**: Two-Stage LLM Mean-Reversion (Arena v1)\n   - max_positions: 10\n   - max_buys_per_run: 2\n   - avoid_overtrading: true\n   - max_sells_per_run: 2\n   - max_gross_leverage: 3.0\n   - fixed_position_size: 3000.0\n4. **Selection Rules**:\n   - Horizon: 2-10 trading days\n   - Target: short-term mean reversion in liquid equities\n   - Constraints:\n     - Select exactly 5 candidates\n     - Avoid earnings within 5 trading days (if known)\n     - Avoid highly binary/event-driven moves (if known)\n     - Avoid sector concentration: max 1 per sector unless clearly justified (sector may be unknown)\n\n**Key points for mean reversion strategy**:\n- Look for stocks that have moved significantly away from their moving averages (overextended)\n- Prefer stocks that have moved sharply in one direction (up or down) and are likely to revert\n- High volatility can be good for mean reversion setups\n- Need to avoid stocks with upcoming earnings or event risk\n\n**Data limitations**:\n- Most stocks have no sector information\n- No earnings dates known (all null)\n- No news sentiment or headlines\n- No market cap or volume data\n- Only technical data available: price, distances from MA200/MA50, 20d volatility, 1d change\n\n**Approach**:\nSince I need to select exactly 5 candidates and most sector data is missing, I'll focus on:\n1. **Overextended conditions**: Large distance from moving averages (both positive and negative)\n2. **Recent sharp moves**: Large 1-day changes\n3. **Reasonable volatility**: Not too low (no opportunity) or excessively high (too risky)\n4. **Liquidity proxy**: Though not explicitly given, I'll assume the CFDs are liquid enough\n\nFor mean reversion, I want stocks that have:\n- **Oversold candidates**: Large negative distance from MAs + large negative 1-day move\n- **Overbought candidates**: Large positive distance from MAs + large positive 1-day move\n\nLet me analyze the universe:\n\n**US symbols** (since region is US, but the universe is mixed):\n- CAR_CFD.US: -15.47% from MA200, -5.58% from MA50, +2.02% today, vol 75.04%\n- ASGN_CFD.US: +2.41% from MA200, +4.19% from MA50, +2.29% today, vol 78.91%\n- BDX_CFD.US: +11.48% from MA200, +4.45% from MA50, +1.38% today, vol 44.71%\n- BFAM_CFD.US: -23.00% from MA200, -13.58% from MA50, -3.83% today, vol 50.46%\n- BRO_CFD.US: -21.51% from MA200, -6.60% from MA50, +2.81% today, vol 57.53%\n- CCK_CFD.US: +10.90% from MA200, +7.47% from MA50, -0.75% today, vol 47.16%\n- AJG_CFD.US: -18.13% from MA200, -5.80% from MA50, -2.83% today, vol 59.13%\n- AMCX_CFD.US: +2.72% from MA200, -13.62% from MA50, -1.16% today, vol 75.95%\n- BBY_CFD.US: -5.90% from MA200, -3.16% from MA50, +3.33% today, vol 68.19%\n- BERY_CFD.US: +0.16% from MA200, -2.39% from MA50, -2.29% today, vol 69.72%\n- CHT_CFD.US: -4.02% from MA200, -0.52% from MA50, -0.10% today, vol 24.95%\n- CBRE_CFD.US: +11.65% from MA200, +2.69% from MA50, +2.02% today, vol 44.59%\n- CE_CFD.US: +15.83% from MA200, +22.67% from MA50, +17.38% today, vol 112.38%\n- ARW_CFD.US: +30.42% from MA200, +32.68% from MA50, +17.46% today, vol 67.33%\n- ABBV_CFD.US: +5.26% from MA200, -1.31% from MA50, -2.62% today, vol 73.26%\n- ADP_CFD.US: -20.61% from MA200, -11.25% from MA50, -4.25% today, vol 39.80%\n- ALL_CFD.US: +2.30% from MA200, +1.42% from MA50, +2.14% today, vol 51.84%\n- BMY_CFD.US: +26.07% from MA200, +12.94% from MA50, +8.96% today, vol 60.00%\n- AIZ_CFD.US: +14.61% from MA200, +3.77% from MA50, +1.08% today, vol 35.24%\n- CAG_CFD.US: -0.73% from MA200, +9.13% from MA50, +1.11% today, vol 55.38%\n\n**Non-US symbols** (but still in universe):\n- Many UK, DE, FR, DK, PL, BE, PT, SE symbols\n\nSince the region is specified as \"US\", I should prioritize US symbols, but the strategy doesn't explicitly say to exclude non-US. The universe includes them, so I can consider them. However, the strategy name mentions \"Arena v1\" and typical mean reversion strategies focus on liquid equities. I'll prioritize US symbols as the region is US.\n\n**Selection criteria**:\n1. **Oversold bounce candidates**: Large negative distance from MAs + recent down move\n2. **Overbought fade candidates**: Large positive distance from MAs + recent up move\n3. **Volatility**: 40-120% range seems reasonable\n4. **No earnings risk**: All have null earnings dates, so this constraint is satisfied\n5. **No event risk**: No news data, so I cannot assess this; I'll have to assume it's okay\n\nLet me score candidates based on mean reversion potential:\n\n**Strong oversold candidates**:\n- BFAM_CFD.US: -23% from MA200, -13.58% from MA50, -3.83% today, vol 50.46% - **Strong**\n- ADP_CFD.US: -20.61% from MA200, -11.25% from MA50, -4.25% today, vol 39.80% - **Strong**\n- BRO_CFD.US: -21.51% from MA200, -6.60% from MA50, +2.81% today, vol 57.53% - **Good (potential early reversal)**\n- AJG_CFD.US: -18.13% from MA200, -5.80% from MA50, -2.83% today, vol 59.13% - **Good**\n- CAR_CFD.US: -15.47% from MA200, -5.58% from MA50, +2.02% today, vol 75.04% - **Good**\n\n**Strong overbought candidates**:\n- CE_CFD.US: +15.83% from MA200, +22.67% from MA50, +17.38% today, vol 112.38% - **Very Strong (huge move)**\n- ARW_CFD.US: +30.42% from MA200, +32.68% from MA50, +17.46% today, vol 67.33% - **Very Strong (huge move)**\n- BMY_CFD.US: +26.07% from MA200, +12.94% from MA50, +8.96% today, vol 60.00% - **Strong**\n- AA_CFD.US: +59.35% from MA200, +9.36% from MA50, -1.28% today, vol 113.71% - **Extreme (but might be too extended)**\n- BLDR_CFD.US: +3.22% from MA200, +9.33% from MA50, +5.37% today, vol 93.51% - **Moderate**\n\n**Mixed signals**:\n- AMCX_CFD.US: +2.72% from MA200, -13.62% from MA50, -1.16% today, vol 75.95% - **Good (short-term oversold)**\n\nI need exactly 5 candidates. I should diversify between oversold and overbought setups. Since sector data is mostly unknown, I cannot enforce the sector concentration rule strictly, but I'll try to pick different types of stocks.\n\n**My picks**:\n1. **CE_CFD.US** - Overbought fade candidate (massive +17% day, extended from MAs)\n2. **BFAM_CFD.US** - Oversold bounce candidate (deeply below MAs, down day)\n3. **ARW_CFD.US** - Overbought fade candidate (extremely extended, huge move)\n4. **ADP_CFD.US** - Oversold bounce candidate (deeply below MAs, down day)\n5. **AJG_CFD.US** - Oversold bounce candidate (extended below MAs, down day)\n\nWait, let me reconsider. I should have a better mix and consider the volatility levels. Also, I should check if some of these moves might be event-driven. Since I have no news, I have to assume they're not.\n\nLet me re-evaluate with scoring:\n\n**Scoring logic** (0-100):\n- Distance from MA50: Absolute value >10% = high score\n- Distance from MA200: Absolute value >15% = high score\n- 1-day change: Absolute value >3% = high score\n- Volatility: 40-100% = optimal range\n\n**Calculating scores**:\n\n1. **CE_CFD.US**: \n   - MA50: +22.67% (very extended)\n   - MA200: +15.83% (very extended)\n   - 1d: +17.38% (huge move)\n   - Vol: 112.38% (high but acceptable)\n   - Score: 95 (extreme overbought)\n\n2. **BFAM_CFD.US**:\n   - MA50: -13.58% (very extended)\n   - MA200: -23.00% (very extended)\n   - 1d: -3.83% (significant down)\n   - Vol: 50.46% (good)\n   - Score: 90 (deeply oversold)\n\n3. **ARW_CFD.US**:\n   - MA50: +32.68% (extremely extended)\n   - MA200: +30.42% (extremely extended)\n   - 1d: +17.46% (huge move)\n   - Vol: 67.33% (good)\n   - Score: 98 (extreme overbought)\n\n4. **ADP_CFD.US**:\n   - MA50: -11.25% (very extended)\n   - MA200: -20.61% (very extended)\n   - 1d: -4.25% (significant down)\n   - Vol: 39.80% (slightly low but ok)\n   - Score: 85 (deeply oversold)\n\n5. **AJG_CFD.US**:\n   - MA50: -5.80% (moderately extended)\n   - MA200: -18.13% (very extended)\n   - 1d: -2.83% (down)\n   - Vol: 59.13% (good)\n   - Score: 75 (oversold)\n\n6. **BRO_CFD.US**:\n   - MA50: -6.60% (moderately extended)\n   - MA200: -21.51% (very extended)\n   - 1d: +2.81% (up - potential reversal)\n   - Vol: 57.53% (good)\n   - Score: 78 (potentially reversing)\n\n7. **CAR_CFD.US**:\n   - MA50: -5.58% (moderately extended)\n   - MA200: -15.47% (very extended)\n   - 1d: +2.02% (up - potential reversal)\n   - Vol: 75.04% (good)\n   - Score: 76 (potentially reversing)\n\n8. **AMCX_CFD.US**:\n   - MA50: -13.62% (very extended)\n   - MA200: +2.72% (neutral long-term)\n   - 1d: -1.16% (slight down)\n   - Vol: 75.95% (good)\n   - Score: 72 (short-term oversold)\n\n9. **BMY_CFD.US**:\n   - MA50: +12.94% (very extended)\n   - MA200: +26.07% (very extended)\n   - 1d: +8.96% (strong up)\n   - Vol: 60.00% (good)\n   - Score: 88 (strong overbought)\n\n10. **AA_CFD.US**:\n    - MA50: +9.36% (extended)\n    - MA200: +59.35% (extremely extended)\n    - 1d: -1.28% (slight down)\n    - Vol: 113.71% (high)\n    - Score: 85 (very extended, but maybe too extreme)\n\nI need to select exactly 5. I should pick the best setups with highest scores and good diversification. Since sector data is unknown, I'll just pick the best technical setups.\n\n**Final selection**:\n1. **ARW_CFD.US** - Score 98 (overbought)\n2. **CE_CFD.US** - Score 95 (overbought)\n3. **BFAM_CFD.US** - Score 90 (oversold)\n4. **BMY_CFD.US** - Score 88 (overbought)\n5. **ADP_CFD.US** - Score 85 (oversold)\n\nThis gives me 3 overbought and 2 oversold candidates. Good mix.\n\nWait, let me double-check the constraints:\n- \"Avoid earnings within 5 trading days (if known)\" - All earnings are null, so this is satisfied\n- \"Avoid highly binary/event-driven moves (if known)\" - No news data, so I cannot assess this. I have to assume it's okay.\n- \"Avoid sector concentration: max 1 per sector unless clearly justified (sector may be unknown)\" - All sectors are unknown/empty, so this constraint is effectively not enforceable. I'll proceed with the best 5.\n\nLet me refine the selection_reason to be short, concrete, and indicator-based:\n\n1. **ARW_CFD.US**: \"Extremely overextended: +32.7% from MA50, +30.4% from MA200, +17.5% today. High volatility setup for mean reversion.\"\n2. **CE_CFD.US**: \"Sharply overbought: +22.7% from MA50, +15.8% from MA200, +17.4% today. Volatility 112% supports reversion.\"\n3. **BFAM_CFD.US**: \"Deeply oversold: -13.6% from MA50, -23.0% from MA200, -3.8% today. Volatility 50% offers reversion opportunity.\"\n4. **BMY_CFD.US**: \"Overextended rally: +12.9% from MA50, +26.1% from MA200, +9.0% today. Mature bounce candidate.\"\n5. **ADP_CFD.US**: \"Oversold breakdown: -11.3% from MA50, -20.6% from MA200, -4.3% today. Approaching support for reversion.\"\n\nActually, I should make the reasons even shorter and more concrete as per the schema requirement.\n\nLet me also consider if I should include any non-US symbols. The region is \"US\", but the universe includes others. The strategy doesn't explicitly restrict to US-only symbols. However, the \"region\" field in the task is \"US\", which suggests I should focus on US symbols. I'll stick to US symbols.\n\nOne more check: Are there any symbols that are too illiquid or have too low volatility? The volatility range is 35-113% for my selections, which is reasonable. ADP has 39.8% which is borderline but acceptable.\n\nLet me finalize my picks:\n\n1. **ARW_CFD.US** - Mean reversion score: 98\n2. **CE_CFD.US** - Mean reversion score: 95\n3. **BFAM_CFD.US** - Mean reversion score: 90\n4. **BMY_CFD.US** - Mean reversion score: 88\n5. **ADP_CFD.US** - Mean reversion score: 85\n\nThese are the top 5 scores. The reasons should be concise and mention the key indicators.\n\n**Rejection reasons**: I should also provide rejected_common_reasons. Since I don't have a explicit rejection list, I'll think about common reasons why others were rejected:\n- Not sufficiently extended from MAs\n- Volatility too low or too high\n- Mixed signals (e.g., above MA200 but below MA50 without clear overextension)\n- Recent move too small for mean reversion setup\n\nLet me create the final JSON output.",
          "reasoning_details": [
            {
              "text": "The user wants me to perform a \"stage1_universe_scan\" for the \"meanrev-v1\" strategy. Let me break down the requirements:\n\n1. **Task**: Stage 1 universe scan for mean reversion\n2. **Region**: US (but the universe includes many non-US symbols)\n3. **Strategy**: Two-Stage LLM Mean-Reversion (Arena v1)\n   - max_positions: 10\n   - max_buys_per_run: 2\n   - avoid_overtrading: true\n   - max_sells_per_run: 2\n   - max_gross_leverage: 3.0\n   - fixed_position_size: 3000.0\n4. **Selection Rules**:\n   - Horizon: 2-10 trading days\n   - Target: short-term mean reversion in liquid equities\n   - Constraints:\n     - Select exactly 5 candidates\n     - Avoid earnings within 5 trading days (if known)\n     - Avoid highly binary/event-driven moves (if known)\n     - Avoid sector concentration: max 1 per sector unless clearly justified (sector may be unknown)\n\n**Key points for mean reversion strategy**:\n- Look for stocks that have moved significantly away from their moving averages (overextended)\n- Prefer stocks that have moved sharply in one direction (up or down) and are likely to revert\n- High volatility can be good for mean reversion setups\n- Need to avoid stocks with upcoming earnings or event risk\n\n**Data limitations**:\n- Most stocks have no sector information\n- No earnings dates known (all null)\n- No news sentiment or headlines\n- No market cap or volume data\n- Only technical data available: price, distances from MA200/MA50, 20d volatility, 1d change\n\n**Approach**:\nSince I need to select exactly 5 candidates and most sector data is missing, I'll focus on:\n1. **Overextended conditions**: Large distance from moving averages (both positive and negative)\n2. **Recent sharp moves**: Large 1-day changes\n3. **Reasonable volatility**: Not too low (no opportunity) or excessively high (too risky)\n4. **Liquidity proxy**: Though not explicitly given, I'll assume the CFDs are liquid enough\n\nFor mean reversion, I want stocks that have:\n- **Oversold candidates**: Large negative distance from MAs + large negative 1-day move\n- **Overbought candidates**: Large positive distance from MAs + large positive 1-day move\n\nLet me analyze the universe:\n\n**US symbols** (since region is US, but the universe is mixed):\n- CAR_CFD.US: -15.47% from MA200, -5.58% from MA50, +2.02% today, vol 75.04%\n- ASGN_CFD.US: +2.41% from MA200, +4.19% from MA50, +2.29% today, vol 78.91%\n- BDX_CFD.US: +11.48% from MA200, +4.45% from MA50, +1.38% today, vol 44.71%\n- BFAM_CFD.US: -23.00% from MA200, -13.58% from MA50, -3.83% today, vol 50.46%\n- BRO_CFD.US: -21.51% from MA200, -6.60% from MA50, +2.81% today, vol 57.53%\n- CCK_CFD.US: +10.90% from MA200, +7.47% from MA50, -0.75% today, vol 47.16%\n- AJG_CFD.US: -18.13% from MA200, -5.80% from MA50, -2.83% today, vol 59.13%\n- AMCX_CFD.US: +2.72% from MA200, -13.62% from MA50, -1.16% today, vol 75.95%\n- BBY_CFD.US: -5.90% from MA200, -3.16% from MA50, +3.33% today, vol 68.19%\n- BERY_CFD.US: +0.16% from MA200, -2.39% from MA50, -2.29% today, vol 69.72%\n- CHT_CFD.US: -4.02% from MA200, -0.52% from MA50, -0.10% today, vol 24.95%\n- CBRE_CFD.US: +11.65% from MA200, +2.69% from MA50, +2.02% today, vol 44.59%\n- CE_CFD.US: +15.83% from MA200, +22.67% from MA50, +17.38% today, vol 112.38%\n- ARW_CFD.US: +30.42% from MA200, +32.68% from MA50, +17.46% today, vol 67.33%\n- ABBV_CFD.US: +5.26% from MA200, -1.31% from MA50, -2.62% today, vol 73.26%\n- ADP_CFD.US: -20.61% from MA200, -11.25% from MA50, -4.25% today, vol 39.80%\n- ALL_CFD.US: +2.30% from MA200, +1.42% from MA50, +2.14% today, vol 51.84%\n- BMY_CFD.US: +26.07% from MA200, +12.94% from MA50, +8.96% today, vol 60.00%\n- AIZ_CFD.US: +14.61% from MA200, +3.77% from MA50, +1.08% today, vol 35.24%\n- CAG_CFD.US: -0.73% from MA200, +9.13% from MA50, +1.11% today, vol 55.38%\n\n**Non-US symbols** (but still in universe):\n- Many UK, DE, FR, DK, PL, BE, PT, SE symbols\n\nSince the region is specified as \"US\", I should prioritize US symbols, but the strategy doesn't explicitly say to exclude non-US. The universe includes them, so I can consider them. However, the strategy name mentions \"Arena v1\" and typical mean reversion strategies focus on liquid equities. I'll prioritize US symbols as the region is US.\n\n**Selection criteria**:\n1. **Oversold bounce candidates**: Large negative distance from MAs + recent down move\n2. **Overbought fade candidates**: Large positive distance from MAs + recent up move\n3. **Volatility**: 40-120% range seems reasonable\n4. **No earnings risk**: All have null earnings dates, so this constraint is satisfied\n5. **No event risk**: No news data, so I cannot assess this; I'll have to assume it's okay\n\nLet me score candidates based on mean reversion potential:\n\n**Strong oversold candidates**:\n- BFAM_CFD.US: -23% from MA200, -13.58% from MA50, -3.83% today, vol 50.46% - **Strong**\n- ADP_CFD.US: -20.61% from MA200, -11.25% from MA50, -4.25% today, vol 39.80% - **Strong**\n- BRO_CFD.US: -21.51% from MA200, -6.60% from MA50, +2.81% today, vol 57.53% - **Good (potential early reversal)**\n- AJG_CFD.US: -18.13% from MA200, -5.80% from MA50, -2.83% today, vol 59.13% - **Good**\n- CAR_CFD.US: -15.47% from MA200, -5.58% from MA50, +2.02% today, vol 75.04% - **Good**\n\n**Strong overbought candidates**:\n- CE_CFD.US: +15.83% from MA200, +22.67% from MA50, +17.38% today, vol 112.38% - **Very Strong (huge move)**\n- ARW_CFD.US: +30.42% from MA200, +32.68% from MA50, +17.46% today, vol 67.33% - **Very Strong (huge move)**\n- BMY_CFD.US: +26.07% from MA200, +12.94% from MA50, +8.96% today, vol 60.00% - **Strong**\n- AA_CFD.US: +59.35% from MA200, +9.36% from MA50, -1.28% today, vol 113.71% - **Extreme (but might be too extended)**\n- BLDR_CFD.US: +3.22% from MA200, +9.33% from MA50, +5.37% today, vol 93.51% - **Moderate**\n\n**Mixed signals**:\n- AMCX_CFD.US: +2.72% from MA200, -13.62% from MA50, -1.16% today, vol 75.95% - **Good (short-term oversold)**\n\nI need exactly 5 candidates. I should diversify between oversold and overbought setups. Since sector data is mostly unknown, I cannot enforce the sector concentration rule strictly, but I'll try to pick different types of stocks.\n\n**My picks**:\n1. **CE_CFD.US** - Overbought fade candidate (massive +17% day, extended from MAs)\n2. **BFAM_CFD.US** - Oversold bounce candidate (deeply below MAs, down day)\n3. **ARW_CFD.US** - Overbought fade candidate (extremely extended, huge move)\n4. **ADP_CFD.US** - Oversold bounce candidate (deeply below MAs, down day)\n5. **AJG_CFD.US** - Oversold bounce candidate (extended below MAs, down day)\n\nWait, let me reconsider. I should have a better mix and consider the volatility levels. Also, I should check if some of these moves might be event-driven. Since I have no news, I have to assume they're not.\n\nLet me re-evaluate with scoring:\n\n**Scoring logic** (0-100):\n- Distance from MA50: Absolute value >10% = high score\n- Distance from MA200: Absolute value >15% = high score\n- 1-day change: Absolute value >3% = high score\n- Volatility: 40-100% = optimal range\n\n**Calculating scores**:\n\n1. **CE_CFD.US**: \n   - MA50: +22.67% (very extended)\n   - MA200: +15.83% (very extended)\n   - 1d: +17.38% (huge move)\n   - Vol: 112.38% (high but acceptable)\n   - Score: 95 (extreme overbought)\n\n2. **BFAM_CFD.US**:\n   - MA50: -13.58% (very extended)\n   - MA200: -23.00% (very extended)\n   - 1d: -3.83% (significant down)\n   - Vol: 50.46% (good)\n   - Score: 90 (deeply oversold)\n\n3. **ARW_CFD.US**:\n   - MA50: +32.68% (extremely extended)\n   - MA200: +30.42% (extremely extended)\n   - 1d: +17.46% (huge move)\n   - Vol: 67.33% (good)\n   - Score: 98 (extreme overbought)\n\n4. **ADP_CFD.US**:\n   - MA50: -11.25% (very extended)\n   - MA200: -20.61% (very extended)\n   - 1d: -4.25% (significant down)\n   - Vol: 39.80% (slightly low but ok)\n   - Score: 85 (deeply oversold)\n\n5. **AJG_CFD.US**:\n   - MA50: -5.80% (moderately extended)\n   - MA200: -18.13% (very extended)\n   - 1d: -2.83% (down)\n   - Vol: 59.13% (good)\n   - Score: 75 (oversold)\n\n6. **BRO_CFD.US**:\n   - MA50: -6.60% (moderately extended)\n   - MA200: -21.51% (very extended)\n   - 1d: +2.81% (up - potential reversal)\n   - Vol: 57.53% (good)\n   - Score: 78 (potentially reversing)\n\n7. **CAR_CFD.US**:\n   - MA50: -5.58% (moderately extended)\n   - MA200: -15.47% (very extended)\n   - 1d: +2.02% (up - potential reversal)\n   - Vol: 75.04% (good)\n   - Score: 76 (potentially reversing)\n\n8. **AMCX_CFD.US**:\n   - MA50: -13.62% (very extended)\n   - MA200: +2.72% (neutral long-term)\n   - 1d: -1.16% (slight down)\n   - Vol: 75.95% (good)\n   - Score: 72 (short-term oversold)\n\n9. **BMY_CFD.US**:\n   - MA50: +12.94% (very extended)\n   - MA200: +26.07% (very extended)\n   - 1d: +8.96% (strong up)\n   - Vol: 60.00% (good)\n   - Score: 88 (strong overbought)\n\n10. **AA_CFD.US**:\n    - MA50: +9.36% (extended)\n    - MA200: +59.35% (extremely extended)\n    - 1d: -1.28% (slight down)\n    - Vol: 113.71% (high)\n    - Score: 85 (very extended, but maybe too extreme)\n\nI need to select exactly 5. I should pick the best setups with highest scores and good diversification. Since sector data is unknown, I'll just pick the best technical setups.\n\n**Final selection**:\n1. **ARW_CFD.US** - Score 98 (overbought)\n2. **CE_CFD.US** - Score 95 (overbought)\n3. **BFAM_CFD.US** - Score 90 (oversold)\n4. **BMY_CFD.US** - Score 88 (overbought)\n5. **ADP_CFD.US** - Score 85 (oversold)\n\nThis gives me 3 overbought and 2 oversold candidates. Good mix.\n\nWait, let me double-check the constraints:\n- \"Avoid earnings within 5 trading days (if known)\" - All earnings are null, so this is satisfied\n- \"Avoid highly binary/event-driven moves (if known)\" - No news data, so I cannot assess this. I have to assume it's okay.\n- \"Avoid sector concentration: max 1 per sector unless clearly justified (sector may be unknown)\" - All sectors are unknown/empty, so this constraint is effectively not enforceable. I'll proceed with the best 5.\n\nLet me refine the selection_reason to be short, concrete, and indicator-based:\n\n1. **ARW_CFD.US**: \"Extremely overextended: +32.7% from MA50, +30.4% from MA200, +17.5% today. High volatility setup for mean reversion.\"\n2. **CE_CFD.US**: \"Sharply overbought: +22.7% from MA50, +15.8% from MA200, +17.4% today. Volatility 112% supports reversion.\"\n3. **BFAM_CFD.US**: \"Deeply oversold: -13.6% from MA50, -23.0% from MA200, -3.8% today. Volatility 50% offers reversion opportunity.\"\n4. **BMY_CFD.US**: \"Overextended rally: +12.9% from MA50, +26.1% from MA200, +9.0% today. Mature bounce candidate.\"\n5. **ADP_CFD.US**: \"Oversold breakdown: -11.3% from MA50, -20.6% from MA200, -4.3% today. Approaching support for reversion.\"\n\nActually, I should make the reasons even shorter and more concrete as per the schema requirement.\n\nLet me also consider if I should include any non-US symbols. The region is \"US\", but the universe includes others. The strategy doesn't explicitly restrict to US-only symbols. However, the \"region\" field in the task is \"US\", which suggests I should focus on US symbols. I'll stick to US symbols.\n\nOne more check: Are there any symbols that are too illiquid or have too low volatility? The volatility range is 35-113% for my selections, which is reasonable. ADP has 39.8% which is borderline but acceptable.\n\nLet me finalize my picks:\n\n1. **ARW_CFD.US** - Mean reversion score: 98\n2. **CE_CFD.US** - Mean reversion score: 95\n3. **BFAM_CFD.US** - Mean reversion score: 90\n4. **BMY_CFD.US** - Mean reversion score: 88\n5. **ADP_CFD.US** - Mean reversion score: 85\n\nThese are the top 5 scores. The reasons should be concise and mention the key indicators.\n\n**Rejection reasons**: I should also provide rejected_common_reasons. Since I don't have a explicit rejection list, I'll think about common reasons why others were rejected:\n- Not sufficiently extended from MAs\n- Volatility too low or too high\n- Mixed signals (e.g., above MA200 but below MA50 without clear overextension)\n- Recent move too small for mean reversion setup\n\nLet me create the final JSON output.",
              "type": "reasoning.text",
              "index": 0,
              "format": "unknown"
            }
          ]
        },
        "logprobs": null,
        "finish_reason": "length",
        "native_finish_reason": "length"
      }
    ],
    "created": 1770651881,
    "provider": "Moonshot AI",
    "system_fingerprint": "fpv0_acbd71c9"
  }
}