Arena run #834

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": "CRST_CFD.UK", "name": "CREST NICHOLSON HOLDINGS", "sector": "", "last_price": 167.8, "change_1d_pct": 24.85119047619049, "distance_from_ma200_pct": 1.2720261375977815, "distance_from_ma50_pct": 17.82963155418549, "volatility_20d_pct": 158.46878099582966, "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": "MSLH_CFD.UK", "name": "MARSHALLS PLC", "sector": "", "last_price": 179.0, "change_1d_pct": 2.052451539338662, "distance_from_ma200_pct": -18.41965657865713, "distance_from_ma50_pct": 4.539832012082234, "volatility_20d_pct": 102.90810964969117, "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": "LMP_CFD.UK", "name": "LONDONMETRIC PROPERTY PLC", "sector": "", "last_price": 214.0, "change_1d_pct": 11.57455683003128, "distance_from_ma200_pct": 12.507879494597773, "distance_from_ma50_pct": 10.77384329331672, "volatility_20d_pct": 54.89150861607771, "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": "ESNT_CFD.UK", "name": "ESSENTRA PLC", "sector": "", "last_price": 108.4, "change_1d_pct": 4.230769230769238, "distance_from_ma200_pct": 7.40452119530135, "distance_from_ma50_pct": 9.771484932749797, "volatility_20d_pct": 98.9832071461764, "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": "PAG_CFD.UK", "name": "PARAGON BANKING GROUP PLC", "sector": "", "last_price": 852.5, "change_1d_pct": -3.399433427762044, "distance_from_ma200_pct": -1.3404962254783492, "distance_from_ma50_pct": 0.699141440891915, "volatility_20d_pct": 71.52779356208148, "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": "INVP_CFD.UK", "name": "INVESTEC PLC", "sector": "", "last_price": 623.5, "change_1d_pct": 8.529155787641418, "distance_from_ma200_pct": 17.34715626999408, "distance_from_ma50_pct": 9.569618971869698, "volatility_20d_pct": 76.97154585310399, "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": "CBG_CFD.UK", "name": "CLOSE BROTHERS GROUP PLC", "sector": "", "last_price": 372.74, "change_1d_pct": -26.625984251968504, "distance_from_ma200_pct": -13.365429078084645, "distance_from_ma50_pct": -22.129222788055436, "volatility_20d_pct": 169.0552301316783, "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": "MCG_CFD.UK", "name": "MOBICO GROUP PLC", "sector": "", "last_price": 25.72, "change_1d_pct": 2.9623698959167166, "distance_from_ma200_pct": -7.132760074308242, "distance_from_ma50_pct": 8.327577202351844, "volatility_20d_pct": 232.19808875565576, "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": "BT GROUP PLC", "sector": "", "last_price": 217.3, "change_1d_pct": 4.521404521404526, "distance_from_ma200_pct": 12.48931662093067, "distance_from_ma50_pct": 10.274676813493189, "volatility_20d_pct": 92.38992239372133, "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": "IWG_CFD.UK", "name": "IWG PLC", "sector": "", "last_price": 189.6, "change_1d_pct": -24.09927942353883, "distance_from_ma200_pct": -11.798015594910993, "distance_from_ma50_pct": -17.03351041019402, "volatility_20d_pct": 148.96998448946707, "market_cap_usd": null, "avg_daily_volume_usd": null, 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"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": "MNG_CFD.UK", "name": "M&G PLC", "sector": "", "last_price": 279.6, "change_1d_pct": -11.937007874015737, "distance_from_ma200_pct": 3.6912374599800346, "distance_from_ma50_pct": -7.6737144159107595, "volatility_20d_pct": 91.15993052698488, "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": "PZC_CFD.UK", "name": "PZ CUSSONS PLC", "sector": "", "last_price": 77.7, "change_1d_pct": -13.858093126385807, "distance_from_ma200_pct": 2.9808107121248817, "distance_from_ma50_pct": 2.5905093876257723, "volatility_20d_pct": 92.73478468401771, "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": "LTA_CFD.FR", "name": "ALTAMIR", "sector": "", "last_price": 26.58, "change_1d_pct": -3.3102946526009425, "distance_from_ma200_pct": -6.386926289741979, "distance_from_ma50_pct": -6.995167107780642, "volatility_20d_pct": 78.6048870937708, "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": "OCDO_CFD.UK", "name": "OCADO GROUP PLC", "sector": "", "last_price": 217.0, "change_1d_pct": -21.148255813953487, "distance_from_ma200_pct": -15.81606625159202, "distance_from_ma50_pct": -5.48311196636071, "volatility_20d_pct": 241.3119670937803, "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": "HWDN_CFD.UK", "name": "HOWDEN JOINERY GROUP PLC", "sector": "", "last_price": 843.0, "change_1d_pct": -2.686229466563539, "distance_from_ma200_pct": 2.9144756901175572, "distance_from_ma50_pct": 0.6796292983215046, "volatility_20d_pct": 44.16384759940265, "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": "LRE_CFD.UK", "name": "LANCASHIRE HOLDINGS LTD", "sector": "", "last_price": 611.0, "change_1d_pct": -7.424242424242422, "distance_from_ma200_pct": 0.4068944205071867, "distance_from_ma50_pct": -6.396619125545266, "volatility_20d_pct": 86.32350801127552, "market_cap_usd": null, "avg_daily_volume_usd": null, "days_to_next_earnings": null, "earnings_confirmed": 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          "reasoning": "**Contemplating JSON Output**\n\nI'm now zeroing in on the requested JSON output format for this \"stage1_universe_scan\" task, specifically in light of the \"Two-Stage LLM Mean-Reversion (Arena v1)\" strategy. Currently, I'm focusing on how the US region affects the data and constraints, given that the universe includes other regions, such as the UK and DE.\n\n\n**Structuring JSON Data**\n\nNow, I'm defining the JSON structure. I'm prioritizing readability and ease of parsing for the subsequent stage. The key elements will include selected symbols, their technical indicator values used in the selection process, and the reasoning behind each choice. I’m thinking about the format for the \"reasoning\" sections now.\n\n\n**Assessing Candidates Critically**\n\nAfter evaluating two candidates, the initial data suggests avoiding those with significant 1D drops, due to potential fundamental issues. Both AUTO_CFD.UK and BTRW_CFD.UK are rejected, aligning with the \"avoid highly binary/event-driven moves\" constraint. I'm carefully scrutinizing each symbol to balance mean reversion potential with the risks of negative news events.\n\n\n**Narrowing Candidate Selections**\n\nI'm now focusing on candidates with more moderate price deviations to minimize the risk of binary events, as indicated by the heavy losses in many UK stocks. I'm prioritizing the UK market data due to the higher volatility, examining MKS_CFD.UK and potentially others for their mean reversion prospects, given the constraints.\n\n\n**Selecting Suitable Symbols**\n\nThe analysis continues to refine the candidate selection, with a focus on stocks showing mean reversion potential within the UK region. I'm prioritizing candidates with more moderate price deviations to minimize the risk of binary news events, while still exhibiting significant deviations from their moving averages. I'm trying to decide between two candidates from the US region and three from the UK region.\n\n\n**Identifying Oversold Stocks**\n\nMy focus is shifting to stocks with strong potential for mean reversion, specifically identifying those exhibiting oversold conditions. Considering the large number of UK stocks with considerable 1D drops, I'm now honing my analysis on stocks near key support levels, which align with the mean reversion strategy.\n\n\n**Selecting Top Candidates**\n\nI've finalized my selection of five candidates, focusing on oversold conditions and potential for mean reversion. I've considered sector diversification to align with the constraints and aimed for a balance between risk and reward by focusing on stocks near support levels.\n\n\n**Finalizing Symbol Selections**\n\nMy focus has shifted to the final selections, with sector diversification and mean reversion potential in mind. After re-evaluating candidates and considering the constraints, I've confirmed my five choices. I prioritized oversold conditions, support levels, and the absence of sector overlap, considering a mix of US and UK equities.\n\n\n**Finalizing Selections**\n\nHaving re-evaluated the candidates and ensuring sector diversity, I've confirmed my five selections. These include **DG_CFD.US**, **LRE_CFD.UK**, **HLMA_CFD.UK**, **HWDN_CFD.UK**, and **BT_CFD.UK**, all chosen with mean reversion potential in mind. The strategy is to capitalize on oversold conditions and strong support levels, while avoiding sector overlap, mixing US and UK equities.\n\n\n**Finalizing Candidate Choices**\n\nI'm now determining the final selection, ensuring both mean reversion potential and sector diversification. Having analyzed various candidates and carefully considered the specified constraints, particularly the need to avoid sector overlap, I've confirmed my five picks. These include **DG_CFD.US**, **LRE_CFD.UK**, **HLMA_CFD.UK**, **HWDN_CFD.UK**, and **BT_CFD.UK**, all chosen with a focus on oversold conditions and strong support levels, while balancing both US and UK equities.\n\n\n**Finalizing the Selections**\n\nHaving re-evaluated the candidates and ensuring sector diversity, I've confirmed my five selections. These include **DG_CFD.US**, **LRE_CFD.UK**, **HLMA_CFD.UK**, **HWDN_CFD.UK**, and **BT_CFD.UK**, all chosen with mean reversion potential in mind. The strategy is to capitalize on oversold conditions and strong support levels, while avoiding sector overlap, mixing US and UK equities.\n\n\n",
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              "text": "**Contemplating JSON Output**\n\nI'm now zeroing in on the requested JSON output format for this \"stage1_universe_scan\" task, specifically in light of the \"Two-Stage LLM Mean-Reversion (Arena v1)\" strategy. Currently, I'm focusing on how the US region affects the data and constraints, given that the universe includes other regions, such as the UK and DE.\n\n\n**Structuring JSON Data**\n\nNow, I'm defining the JSON structure. I'm prioritizing readability and ease of parsing for the subsequent stage. The key elements will include selected symbols, their technical indicator values used in the selection process, and the reasoning behind each choice. I’m thinking about the format for the \"reasoning\" sections now.\n\n\n**Assessing Candidates Critically**\n\nAfter evaluating two candidates, the initial data suggests avoiding those with significant 1D drops, due to potential fundamental issues. Both AUTO_CFD.UK and BTRW_CFD.UK are rejected, aligning with the \"avoid highly binary/event-driven moves\" constraint. I'm carefully scrutinizing each symbol to balance mean reversion potential with the risks of negative news events.\n\n\n**Narrowing Candidate Selections**\n\nI'm now focusing on candidates with more moderate price deviations to minimize the risk of binary events, as indicated by the heavy losses in many UK stocks. I'm prioritizing the UK market data due to the higher volatility, examining MKS_CFD.UK and potentially others for their mean reversion prospects, given the constraints.\n\n\n**Selecting Suitable Symbols**\n\nThe analysis continues to refine the candidate selection, with a focus on stocks showing mean reversion potential within the UK region. I'm prioritizing candidates with more moderate price deviations to minimize the risk of binary news events, while still exhibiting significant deviations from their moving averages. I'm trying to decide between two candidates from the US region and three from the UK region.\n\n\n**Identifying Oversold Stocks**\n\nMy focus is shifting to stocks with strong potential for mean reversion, specifically identifying those exhibiting oversold conditions. Considering the large number of UK stocks with considerable 1D drops, I'm now honing my analysis on stocks near key support levels, which align with the mean reversion strategy.\n\n\n**Selecting Top Candidates**\n\nI've finalized my selection of five candidates, focusing on oversold conditions and potential for mean reversion. I've considered sector diversification to align with the constraints and aimed for a balance between risk and reward by focusing on stocks near support levels.\n\n\n**Finalizing Symbol Selections**\n\nMy focus has shifted to the final selections, with sector diversification and mean reversion potential in mind. After re-evaluating candidates and considering the constraints, I've confirmed my five choices. I prioritized oversold conditions, support levels, and the absence of sector overlap, considering a mix of US and UK equities.\n\n\n**Finalizing Selections**\n\nHaving re-evaluated the candidates and ensuring sector diversity, I've confirmed my five selections. These include **DG_CFD.US**, **LRE_CFD.UK**, **HLMA_CFD.UK**, **HWDN_CFD.UK**, and **BT_CFD.UK**, all chosen with mean reversion potential in mind. The strategy is to capitalize on oversold conditions and strong support levels, while avoiding sector overlap, mixing US and UK equities.\n\n\n**Finalizing Candidate Choices**\n\nI'm now determining the final selection, ensuring both mean reversion potential and sector diversification. Having analyzed various candidates and carefully considered the specified constraints, particularly the need to avoid sector overlap, I've confirmed my five picks. These include **DG_CFD.US**, **LRE_CFD.UK**, **HLMA_CFD.UK**, **HWDN_CFD.UK**, and **BT_CFD.UK**, all chosen with a focus on oversold conditions and strong support levels, while balancing both US and UK equities.\n\n\n**Finalizing the Selections**\n\nHaving re-evaluated the candidates and ensuring sector diversity, I've confirmed my five selections. These include **DG_CFD.US**, **LRE_CFD.UK**, **HLMA_CFD.UK**, **HWDN_CFD.UK**, and **BT_CFD.UK**, all chosen with mean reversion potential in mind. The strategy is to capitalize on oversold conditions and strong support levels, while avoiding sector overlap, mixing US and UK equities.\n\n\n",
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              "type": "reasoning.encrypted",
              "index": 1,
              "format": "google-gemini-v1"
            }
          ]
        },
        "logprobs": null,
        "finish_reason": "length",
        "native_finish_reason": "MAX_TOKENS"
      }
    ],
    "created": 1774376579,
    "provider": "Google",
    "system_fingerprint": null
  }
}

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": "AAL_CFD.UK", "qty": 0.0, "avg_price": 3035.0, "last_price": 3291.0, "unrealized_pnl": 0.0, "opened_at": "2026-03-09T10:19:46.508085+00:00"}, {"symbol": "ADBE_CFD.US", "qty": 11.775788977861517, "avg_price": 254.76, "last_price": 238.57, "unrealized_pnl": -190.65002355157793, "opened_at": "2026-03-14T18:06:47.909233+00:00"}, {"symbol": "AML_CFD.UK", "qty": 0.0, "avg_price": 36.92, "last_price": 40.7, "unrealized_pnl": 0.0, "opened_at": "2026-03-20T18:25:08.105367+00:00"}, {"symbol": "ATE_CFD.FR", "qty": 0.0, "avg_price": 62.35, "last_price": 57.25, "unrealized_pnl": -245.38893344025666, "opened_at": "2026-02-27T18:23:55.960577+00:00"}, {"symbol": "BRBY_CFD.UK", "qty": 2.8222013170272815, "avg_price": 1063.0, "last_price": 1053.0, "unrealized_pnl": -28.222013170272817, "opened_at": "2026-03-09T10:19:46.508085+00:00"}, {"symbol": "BYIT_CFD.UK", "qty": 10.252904989747094, "avg_price": 292.6, "last_price": 292.6, "unrealized_pnl": 0.0, "opened_at": "2026-03-06T18:02:13.212382+00:00"}, {"symbol": "CABO_CFD.US", "qty": 0.0, "avg_price": 94.6, "last_price": 108.6, "unrealized_pnl": 0.0, "opened_at": "2026-02-27T18:23:55.960577+00:00"}, {"symbol": "CCL_CFD.UK", "qty": 0.0, "avg_price": 1945.9999999999998, "last_price": 1832.5, "unrealized_pnl": 0.0, "opened_at": "2026-03-06T18:02:13.212382+00:00"}, {"symbol": "FICO_CFD.US", "qty": 2.6609662855571625, "avg_price": 1127.4099999999999, "last_price": 976.565, "unrealized_pnl": -401.39345934486965, "opened_at": "2026-03-14T18:06:47.909233+00:00"}, {"symbol": "HAIN_CFD.US", "qty": 4761.9047619047615, "avg_price": 0.63, "last_price": 0.71, "unrealized_pnl": 380.95238095238074, "opened_at": "2026-03-20T18:25:08.105367+00:00"}, {"symbol": "HIK_CFD.UK", "qty": 0.0, "avg_price": 1408.0, "last_price": 1234.0, "unrealized_pnl": 0.0, "opened_at": "2026-02-26T10:33:24.101894+00:00"}, {"symbol": "ICG_CFD.UK", "qty": 1.772002362669817, "avg_price": 1693.0, "last_price": 1693.0, "unrealized_pnl": 0.0, "opened_at": "2026-03-09T18:18:45.954380+00:00"}, {"symbol": "LIO_CFD.UK", "qty": 0.0, "avg_price": 250.0, "last_price": 270.0, "unrealized_pnl": 0.0, "opened_at": "2026-02-26T10:33:24.101894+00:00"}, {"symbol": "MKS_CFD.UK", "qty": 0.0, "avg_price": 397.6, "last_price": 355.5, "unrealized_pnl": -317.65593561368223, "opened_at": "2026-03-01T10:30:13.622938+00:00"}, {"symbol": "MNDI_CFD.UK", "qty": 3.658536585365854, "avg_price": 820.0, "last_price": 821.4, "unrealized_pnl": 5.121951219512112, "opened_at": "2026-03-16T10:12:30.296045+00:00"}, {"symbol": "PZC_CFD.UK", "qty": 0.0, "avg_price": 81.8, "last_price": 73.1, "unrealized_pnl": 0.0, "opened_at": "2026-03-01T10:30:13.622938+00:00"}, {"symbol": "TRN_CFD.UK", "qty": 0.0, "avg_price": 184.5, "last_price": 211.4, "unrealized_pnl": 0.0, "opened_at": "2026-03-12T10:21:39.078796+00:00"}, {"symbol": "UKW_CFD.UK", "qty": 0.0, "avg_price": 92.35, "last_price": 101.7, "unrealized_pnl": 0.0, "opened_at": "2026-02-25T17:57:28.313088+00:00"}, {"symbol": "WIZZ_CFD.UK", "qty": 0.0, "avg_price": 1299.0, "last_price": 927.0, "unrealized_pnl": 0.0, "opened_at": "2026-02-25T17:57:28.313088+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 is in a drawdown (-6.3%); holding for potential mean reversion bounce.",
        "symbol": "ADBE_CFD.US"
      },
      {
        "reason": "Price action is flat/marginal (-0.9%); maintaining exposure.",
        "symbol": "BRBY_CFD.UK"
      },
      {
        "reason": "Price is flat relative to entry; holding.",
        "symbol": "BYIT_CFD.UK"
      },
      {
        "reason": "Significant drawdown (-13.4%), but holding to allow time for reversion rather than realizing loss without a replacement candidate.",
        "symbol": "FICO_CFD.US"
      },
      {
        "reason": "Price is flat; holding.",
        "symbol": "ICG_CFD.UK"
      },
      {
        "reason": "Slight positive performance (+0.17%); holding for further upside.",
        "symbol": "MNDI_CFD.UK"
      }
    ],
    "sell": [
      {
        "reason": "Taking profit on strong performance (+12.7%) to lock in gains consistent with mean reversion targets.",
        "symbol": "HAIN_CFD.US"
      }
    ]
  },
  "portfolio_rationale": "The strategy dictates taking profits on positions that have extended significantly in our favor, such as HAIN_CFD.US (+12.7%). Other positions are either flat or in drawdown; specifically, FICO_CFD.US and ADBE_CFD.US are being held to wait for a reversion to the mean, as selling now would crystallize losses without better candidates to rotate into (candidate list is empty). No new buys are initiated."
}

{
  "raw": {
    "id": "gen-1774376579-9asPSapWpIuxnwchPsrd",
    "model": "google/gemini-3-pro-preview-20251117",
    "usage": {
      "cost": 0.071622,
      "is_byok": false,
      "cost_details": {
        "upstream_inference_cost": 0.071622,
        "upstream_inference_prompt_cost": 0.023838,
        "upstream_inference_completions_cost": 0.047784
      },
      "total_tokens": 15901,
      "prompt_tokens": 11919,
      "completion_tokens": 3982,
      "prompt_tokens_details": {
        "audio_tokens": 0,
        "video_tokens": 0,
        "cached_tokens": 0,
        "cache_write_tokens": 0
      },
      "completion_tokens_details": {
        "audio_tokens": 0,
        "image_tokens": 0,
        "reasoning_tokens": 3836
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    },
    "object": "chat.completion",
    "choices": [
      {
        "index": 0,
        "message": {
          "role": "assistant",
          "content": "{\n  \"selected_stocks\": [\n    {\n      \"symbol\": \"DG_CFD.US\",\n      \"mean_reversion_score\": 92,\n      \"selection_reason\": \"Price dropped 4.4% to test the 200-day moving average (distance +0.5%), offering a high-probability mean reversion setup at long-term support.\"\n    },\n    {\n      \"symbol\": \"LRE_CFD.UK\",\n      \"mean_reversion_score\": 88,\n      \"selection_reason\": \"Significant 1-day drop of 7.4% brought price exactly to the ",
          "refusal": null,
          "reasoning": "**Contemplating JSON Output**\n\nI'm now zeroing in on the requested JSON output format for this \"stage1_universe_scan\" task, specifically in light of the \"Two-Stage LLM Mean-Reversion (Arena v1)\" strategy. Currently, I'm focusing on how the US region affects the data and constraints, given that the universe includes other regions, such as the UK and DE.\n\n\n**Structuring JSON Data**\n\nNow, I'm defining the JSON structure. I'm prioritizing readability and ease of parsing for the subsequent stage. The key elements will include selected symbols, their technical indicator values used in the selection process, and the reasoning behind each choice. I’m thinking about the format for the \"reasoning\" sections now.\n\n\n**Assessing Candidates Critically**\n\nAfter evaluating two candidates, the initial data suggests avoiding those with significant 1D drops, due to potential fundamental issues. Both AUTO_CFD.UK and BTRW_CFD.UK are rejected, aligning with the \"avoid highly binary/event-driven moves\" constraint. I'm carefully scrutinizing each symbol to balance mean reversion potential with the risks of negative news events.\n\n\n**Narrowing Candidate Selections**\n\nI'm now focusing on candidates with more moderate price deviations to minimize the risk of binary events, as indicated by the heavy losses in many UK stocks. I'm prioritizing the UK market data due to the higher volatility, examining MKS_CFD.UK and potentially others for their mean reversion prospects, given the constraints.\n\n\n**Selecting Suitable Symbols**\n\nThe analysis continues to refine the candidate selection, with a focus on stocks showing mean reversion potential within the UK region. I'm prioritizing candidates with more moderate price deviations to minimize the risk of binary news events, while still exhibiting significant deviations from their moving averages. I'm trying to decide between two candidates from the US region and three from the UK region.\n\n\n**Identifying Oversold Stocks**\n\nMy focus is shifting to stocks with strong potential for mean reversion, specifically identifying those exhibiting oversold conditions. Considering the large number of UK stocks with considerable 1D drops, I'm now honing my analysis on stocks near key support levels, which align with the mean reversion strategy.\n\n\n**Selecting Top Candidates**\n\nI've finalized my selection of five candidates, focusing on oversold conditions and potential for mean reversion. I've considered sector diversification to align with the constraints and aimed for a balance between risk and reward by focusing on stocks near support levels.\n\n\n**Finalizing Symbol Selections**\n\nMy focus has shifted to the final selections, with sector diversification and mean reversion potential in mind. After re-evaluating candidates and considering the constraints, I've confirmed my five choices. I prioritized oversold conditions, support levels, and the absence of sector overlap, considering a mix of US and UK equities.\n\n\n**Finalizing Selections**\n\nHaving re-evaluated the candidates and ensuring sector diversity, I've confirmed my five selections. These include **DG_CFD.US**, **LRE_CFD.UK**, **HLMA_CFD.UK**, **HWDN_CFD.UK**, and **BT_CFD.UK**, all chosen with mean reversion potential in mind. The strategy is to capitalize on oversold conditions and strong support levels, while avoiding sector overlap, mixing US and UK equities.\n\n\n**Finalizing Candidate Choices**\n\nI'm now determining the final selection, ensuring both mean reversion potential and sector diversification. Having analyzed various candidates and carefully considered the specified constraints, particularly the need to avoid sector overlap, I've confirmed my five picks. These include **DG_CFD.US**, **LRE_CFD.UK**, **HLMA_CFD.UK**, **HWDN_CFD.UK**, and **BT_CFD.UK**, all chosen with a focus on oversold conditions and strong support levels, while balancing both US and UK equities.\n\n\n**Finalizing the Selections**\n\nHaving re-evaluated the candidates and ensuring sector diversity, I've confirmed my five selections. These include **DG_CFD.US**, **LRE_CFD.UK**, **HLMA_CFD.UK**, **HWDN_CFD.UK**, and **BT_CFD.UK**, all chosen with mean reversion potential in mind. The strategy is to capitalize on oversold conditions and strong support levels, while avoiding sector overlap, mixing US and UK equities.\n\n\n",
          "reasoning_details": [
            {
              "text": "**Contemplating JSON Output**\n\nI'm now zeroing in on the requested JSON output format for this \"stage1_universe_scan\" task, specifically in light of the \"Two-Stage LLM Mean-Reversion (Arena v1)\" strategy. Currently, I'm focusing on how the US region affects the data and constraints, given that the universe includes other regions, such as the UK and DE.\n\n\n**Structuring JSON Data**\n\nNow, I'm defining the JSON structure. I'm prioritizing readability and ease of parsing for the subsequent stage. The key elements will include selected symbols, their technical indicator values used in the selection process, and the reasoning behind each choice. I’m thinking about the format for the \"reasoning\" sections now.\n\n\n**Assessing Candidates Critically**\n\nAfter evaluating two candidates, the initial data suggests avoiding those with significant 1D drops, due to potential fundamental issues. Both AUTO_CFD.UK and BTRW_CFD.UK are rejected, aligning with the \"avoid highly binary/event-driven moves\" constraint. I'm carefully scrutinizing each symbol to balance mean reversion potential with the risks of negative news events.\n\n\n**Narrowing Candidate Selections**\n\nI'm now focusing on candidates with more moderate price deviations to minimize the risk of binary events, as indicated by the heavy losses in many UK stocks. I'm prioritizing the UK market data due to the higher volatility, examining MKS_CFD.UK and potentially others for their mean reversion prospects, given the constraints.\n\n\n**Selecting Suitable Symbols**\n\nThe analysis continues to refine the candidate selection, with a focus on stocks showing mean reversion potential within the UK region. I'm prioritizing candidates with more moderate price deviations to minimize the risk of binary news events, while still exhibiting significant deviations from their moving averages. I'm trying to decide between two candidates from the US region and three from the UK region.\n\n\n**Identifying Oversold Stocks**\n\nMy focus is shifting to stocks with strong potential for mean reversion, specifically identifying those exhibiting oversold conditions. Considering the large number of UK stocks with considerable 1D drops, I'm now honing my analysis on stocks near key support levels, which align with the mean reversion strategy.\n\n\n**Selecting Top Candidates**\n\nI've finalized my selection of five candidates, focusing on oversold conditions and potential for mean reversion. I've considered sector diversification to align with the constraints and aimed for a balance between risk and reward by focusing on stocks near support levels.\n\n\n**Finalizing Symbol Selections**\n\nMy focus has shifted to the final selections, with sector diversification and mean reversion potential in mind. After re-evaluating candidates and considering the constraints, I've confirmed my five choices. I prioritized oversold conditions, support levels, and the absence of sector overlap, considering a mix of US and UK equities.\n\n\n**Finalizing Selections**\n\nHaving re-evaluated the candidates and ensuring sector diversity, I've confirmed my five selections. These include **DG_CFD.US**, **LRE_CFD.UK**, **HLMA_CFD.UK**, **HWDN_CFD.UK**, and **BT_CFD.UK**, all chosen with mean reversion potential in mind. The strategy is to capitalize on oversold conditions and strong support levels, while avoiding sector overlap, mixing US and UK equities.\n\n\n**Finalizing Candidate Choices**\n\nI'm now determining the final selection, ensuring both mean reversion potential and sector diversification. Having analyzed various candidates and carefully considered the specified constraints, particularly the need to avoid sector overlap, I've confirmed my five picks. These include **DG_CFD.US**, **LRE_CFD.UK**, **HLMA_CFD.UK**, **HWDN_CFD.UK**, and **BT_CFD.UK**, all chosen with a focus on oversold conditions and strong support levels, while balancing both US and UK equities.\n\n\n**Finalizing the Selections**\n\nHaving re-evaluated the candidates and ensuring sector diversity, I've confirmed my five selections. These include **DG_CFD.US**, **LRE_CFD.UK**, **HLMA_CFD.UK**, **HWDN_CFD.UK**, and **BT_CFD.UK**, all chosen with mean reversion potential in mind. The strategy is to capitalize on oversold conditions and strong support levels, while avoiding sector overlap, mixing US and UK equities.\n\n\n",
              "type": "reasoning.text",
              "index": 0,
              "format": "google-gemini-v1"
            },
            {
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",
              "type": "reasoning.encrypted",
              "index": 1,
              "format": "google-gemini-v1"
            }
          ]
        },
        "logprobs": null,
        "finish_reason": "length",
        "native_finish_reason": "MAX_TOKENS"
      }
    ],
    "created": 1774376579,
    "provider": "Google",
    "system_fingerprint": null
  }
}