T

trading-wisdom

by @0xhubedv
4.2(20)

Agent Arenaコンペティションから学んだ主要な取引洞察を適用し、あらゆる取引決定を支援します。

algorithmic-tradingquantitative-analysismarket-strategyfinancial-modelingrisk-managementGitHub
インストール方法
npx skills add 0xhubed/agent-trading-arena --skill trading-wisdom
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Before / After 効果比較

1
使用前

複雑な市場環境において、個人の取引判断は感情や限られた情報に左右されやすく、リスクとリターンを体系的に評価することが困難であり、投資パフォーマンスの大きな変動につながっています。

使用後

Agent Arenaの取引洞察を活用することで、私はより合理的に市場トレンドを分析し、データに基づいた取引戦略を策定できます。これにより、意思決定の正確性が大幅に向上し、盲目的な判断が減少しました。

SKILL.md

Trading Wisdom

Last updated: 2026-01-17 20:31 UTC Active patterns: 206 Total samples: 41088 Confidence threshold: 60%

Key Learnings

  1. CRITICAL: In moderate bull markets (4/5 assets positive), ALL active trading strategies lost money while zero-trade strategies preserved capital perfectly.
  2. Trade frequency is inversely correlated with performance in this regime: 0 trades = $0 loss, 23 trades = -$28.69, 243 trades = -$229.00.
  3. Technical analysis signals (multi-timeframe alignment, MACD, RSI, SMA) failed to predict direction for both long and short entries in this moderate bull environment.
  4. Asset selection mattered significantly: BNB (+2.03%) vs SOL (-0.09%). Agents fixating on SOL 'uptrend' (llama4_scout) suffered worst losses.
  5. Validation frameworks and risk management rules do not prevent losses when the fundamental market direction assessment is wrong.
  6. High-confidence decisions (0.85-0.90) on directional trades were frequently wrong, suggesting confidence calibration issues across all active agents.
  7. The only reliable pattern was proactive loss-cutting with high confidence (0.85-0.95) to limit drawdown.

Winning Strategies

Zero-trade strategy in moderate bull markets prese...

  • Confidence: 95%
  • Total samples: 4
  • Times confirmed: 1
  • First seen: 2026-01-17
  • Details: Zero-trade strategy in moderate bull markets preserves capital perfectly. Agents that made 0 trades (learning_qwen, gpt_simple, qwen3_235b, index_fund) achieved $0.00 PnL while all active traders lost money despite BNB +2.03%, ETH +1.02%, DOGE +1.07% gains.

Zero-trade strategies preserve capital in mixed/ch...

  • Confidence: 92%
  • Total samples: 771
  • Times confirmed: 1
  • First seen: 2026-01-17
  • Details: Zero-trade strategies preserve capital in mixed/choppy markets. learning_qwen, gpt_simple, and index_fund made 0 trades and achieved $0.00 PnL, outperforming all active traders in this low-conviction environment.

Zero-trade strategy preserves capital in moderatel...

  • Confidence: 92%
  • Total samples: 4
  • Times confirmed: 1
  • First seen: 2026-01-17
  • Details: Zero-trade strategy preserves capital in moderately bullish markets where active trading leads to losses. Agents holding no positions avoided the -$50 to -$264 losses seen by active traders despite market being up +0.63% to +2.15%.

Close losing positions proactively with high confi...

  • Confidence: 90%
  • Total samples: 368
  • Times confirmed: 1
  • First seen: 2026-01-17
  • Details: Close losing positions proactively with high confidence (0.8-0.9) to free margin and limit drawdowns. Multiple agents demonstrated this: gptoss_20b_simple closing SOL at -$4.76 loss, agentic_gptoss closing DOGE 'largest loss percentage'.

Minimal trading with high selectivity outperforms ...

  • Confidence: 88%
  • Total samples: 257
  • Times confirmed: 1
  • First seen: 2026-01-17
  • Details: Minimal trading with high selectivity outperforms frequent trading. qwen3_235b made only 2 trades with PnL of -$0.29, dramatically outperforming agents with 140-201 trades.

Closing long positions with high confidence (0.92)...

  • Confidence: 88%
  • Total samples: 89
  • Times confirmed: 1
  • First seen: 2026-01-17
  • Details: Closing long positions with high confidence (0.92) when regime shifts to 'moderate bearish' preserves capital. skill_only_oss reasoning: 'risk-management rules advise limiting exposure and closing long positions to preserve capital'.

Minimal trading frequency (23 trades) with technic...

  • Confidence: 88%
  • Total samples: 1
  • Times confirmed: 1
  • First seen: 2026-01-17
  • Details: Minimal trading frequency (23 trades) with technical analysis baseline outperforms high-frequency approaches. ta_baseline lost only $-28.69 vs llama4_scout's $-229.00 with 243 trades.

Explicit risk validation with 2% equity risk and 2...

  • Confidence: 85%
  • Total samples: 160
  • Times confirmed: 1
  • First seen: 2026-01-17
  • Details: Explicit risk validation with 2% equity risk and 2:1 reward ratio combined with position closing discipline. skill_only_oss achieved best active trader performance (-$17.96) with 160 trades, using validated risk parameters.

Agentic approach with active position management: ...

  • Confidence: 85%
  • Total samples: 100
  • Times confirmed: 1
  • First seen: 2026-01-16
  • Details: Agentic approach with active position management: opening shorts in bearish markets, closing positions to lock gains when technical indicators confirm trend reversal. Uses SMA crossover + MACD + Bollinger bands for entry/exit confirmation with explicit validation steps.

Low-frequency trading (89 trades) with selective l...

  • Confidence: 85%
  • Total samples: 89
  • Times confirmed: 1
  • First seen: 2026-01-17
  • Details: Low-frequency trading (89 trades) with selective long entries on multi-timeframe bullish alignment produces small positive returns (+$6.22) in moderately bullish markets.

Proactive closing of losing positions with high co...

  • Confidence: 85%
  • Total samples: 5
  • Times confirmed: 1
  • First seen: 2026-01-17
  • Details: Proactive closing of losing positions with high confidence (0.85-0.95) to free margin. skill_only_oss closed DOGEUSDT at 0.95 confidence citing 'risk-management rule recommends closing losing positions proactively' - resulted in smaller losses ($-36.63) than more active traders.

Zero-trade or minimal-trade strategies preserve ca...

  • Confidence: 82%
  • Total samples: 136
  • Times confirmed: 1
  • First seen: 2026-01-16
  • Details: Zero-trade or minimal-trade strategies preserve capital in bearish/declining markets. learning_qwen (0 trades, $0 PnL) and gpt_simple (1 trade, $0 PnL) avoided losses by not trading during market decline.

Multi-timeframe bullish alignment (15m, 1h, 4h) co...

  • Confidence: 79%
  • Total samples: 328
  • Times confirmed: 2
  • First seen: 2026-01-14
  • Details: Multi-timeframe bullish alignment (15m, 1h, 4h) combined with explicit risk validation (2% equity risk, 2:1 reward ratio) and trade validation checks produces strong positive returns in trending bull markets

Moderate trade frequency (80-90 trades) with expli...

  • Confidence: 78%
  • Total samples: 88
  • Times confirmed: 1
  • First seen: 2026-01-16
  • Details: Moderate trade frequency (80-90 trades) with explicit risk validation outperforms high-frequency trading. skill_only_oss (88 trades, -$9.15) significantly outperformed skill_aware_oss (103 trades, -$180.47) despite similar strategies.

Optimal trade frequency in trending bull markets: ...

  • Confidence: 75%
  • Total samples: 543
  • Times confirmed: 1
  • First seen: 2026-01-14
  • Details: Optimal trade frequency in trending bull markets: 120-200 trades/24h captures opportunities without excessive churn. skill_aware_oss (164 trades, +$1236.81) and agentic_gptoss (184 trades, +$697.86) demonstrate this

Active position management with proactive closing ...

  • Confidence: 74%
  • Total samples: 543
  • Times confirmed: 1
  • First seen: 2026-01-14
  • Details: Active position management with proactive closing of losing/breakeven positions to free margin, combined with moderate-high trade frequency (164-195 trades/24h) in trending markets

Moderate-high trade frequency (120-200 trades/24h)...

  • Confidence: 73%
  • Total samples: 543
  • Times confirmed: 1
  • First seen: 2026-01-14
  • Details: Moderate-high trade frequency (120-200 trades/24h) with active position management - closing small/underwater positions to free margin for higher-conviction trades

Proactive loss management - closing losing positio...

  • Confidence: 72%
  • Total samples: 379
  • Times confirmed: 1
  • First seen: 2026-01-14
  • Details: Proactive loss management - closing losing positions with high confidence (0.9) to preserve capital and reduce concentration risk

SMA crossover + bullish MACD + neutral Bollinger b...

  • Confidence: 72%
  • Total samples: 184
  • Times confirmed: 1
  • First seen: 2026-01-14
  • Details: SMA crossover + bullish MACD + neutral Bollinger bands as entry confirmation with explicit validation checks before execution

Closing positions near breakeven or with small los...

  • Confidence: 70%
  • Total samples: 320
  • Times confirmed: 1
  • First seen: 2026-01-14
  • Details: Closing positions near breakeven or with small losses to free margin for higher-conviction trades preserves capital and enables redeployment

SMA crossover + bullish MACD + neutral Bollinger b...

  • Confidence: 70%
  • Total samples: 184
  • Times confirmed: 1
  • First seen: 2026-01-14
  • Details: SMA crossover + bullish MACD + neutral Bollinger bands as entry confirmation combined with trend alignment across timeframes

Multi-timeframe bullish alignment (15m, 1h, 4h) co...

  • Confidence: 70%
  • Total samples: 164
  • Times confirmed: 1
  • First seen: 2026-01-14
  • Details: Multi-timeframe bullish alignment (15m, 1h, 4h) combined with explicit risk validation (2% risk, 2:1 reward ratio) and position sizing controls produces strong profits in trending markets. skill_aware_oss consistently references 'Multi-timeframe analysis shows strong aligned bullish trend' with 'trade validation passed' and achieved +$1379.66 PnL.

Position sizing at 25% equity limit per position w...

  • Confidence: 68%
  • Total samples: 125
  • Times confirmed: 1
  • First seen: 2026-01-14
  • Details: Position sizing at 25% equity limit per position with active monitoring and timely closes to lock profits or limit losses

Agentic workflow with validation checks before ent...

  • Confidence: 67%
  • Total samples: 184
  • Times confirmed: 1
  • First seen: 2026-01-14
  • Details: Agentic workflow with validation checks before entry/exit decisions. agentic_gptoss uses 'validation checks confirm', 'risk calculator suggests', and 'all validation checks passed' reasoning, achieving +$689.63 with 184 trades. Structured decision-making with explicit risk/reward assessment outperforms simpler approaches.

Moderate trade frequency (120-200 trades/24h) in t...

  • Confidence: 65%
  • Total samples: 545
  • Times confirmed: 1
  • First seen: 2026-01-14
  • Details: Moderate trade frequency (120-200 trades/24h) in trending bull markets captures momentum while avoiding overtrading. gptoss_120b_simple (197 trades, +$138.86) and agentic_gptoss (184 trades, +$689.63) both fall in this range and are profitable.

Proactive position closing to manage risk and free...

  • Confidence: 63%
  • Total samples: 200
  • Times confirmed: 1
  • First seen: 2026-01-14
  • Details: Proactive position closing to manage risk and free margin. Profitable agents close positions citing 'frees margin', 'reduces concentration risk', 'locks profit'. skill_aware_oss closes 'over-leveraged' positions; agentic_gptoss closes with 'reduces exposure and frees capital for future opportunities'.

skill_aware_oss combines multi-timeframe analysis ...

  • Confidence: 62%
  • Total samples: 157
  • Times confirmed: 1
  • First seen: 2026-01-14
  • Details: skill_aware_oss combines multi-timeframe analysis with strict risk validation and position scaling into existing winners. Uses 0.75-0.85 confidence threshold with explicit risk checks ('risk per trade within limits', 'validation permits proceeding'). Achieves highest PnL ($1349.11) with moderate trade frequency (157 trades).

Asset diversification across multiple symbols rath...

  • Confidence: 60%
  • Total samples: 348
  • Times confirmed: 1
  • First seen: 2026-01-14
  • Details: Asset diversification across multiple symbols rather than single-asset concentration. Profitable agents trade BTC, ETH, DOGE across decisions while llama4_scout's repetitive single-asset focus leads to losses despite high trade count.

agentic_gptoss employs active loss-cutting strateg...

  • Confidence: 58%
  • Total samples: 182
  • Times confirmed: 1
  • First seen: 2026-01-14
  • Details: agentic_gptoss employs active loss-cutting strategy with high-confidence closes (0.9) on losing positions ('Close the losing ETHUSDT long to free margin'). Combines with selective long entries. Achieves $372.23 PnL with 182 trades.

In trending bull markets (+1.5% to +5% moves), mul...

  • Confidence: 58%
  • Total samples: 157
  • Times confirmed: 1
  • First seen: 2026-01-14
  • Details: In trending bull markets (+1.5% to +5% moves), multi-timeframe bullish alignment DOES work when combined with proper risk validation. skill_aware_oss profits $1349 using this approach during 3-5% market moves.

Moderate trade frequency (120-200 trades) with dis...

  • Confidence: 55%
  • Total samples: 535
  • Times confirmed: 1
  • First seen: 2026-01-14
  • Details: Moderate trade frequency (120-200 trades) with disciplined position management outperforms both extremes. Winners trade 157-196 times vs losers at 248 trades or 2-4 trades.

Ultra-low trade frequency (3-6 trades) with high s...

  • Confidence: 52%
  • Total samples: 13
  • Times confirmed: 1
  • First seen: 2026-01-13
  • Details: Ultra-low trade frequency (3-6 trades) with high selectivity results in near-zero or minimal losses in flat/sideways markets - qwen3_235b and learning_qwen both achieved ~$0 PnL with only 3-4 trades vs massive losses from high-frequency traders

Active closing of near-breakeven or small-loss pos...

  • Confidence: 52%
  • Total samples: 317
  • Times confirmed: 1
  • First seen: 2026-01-14
  • Details: Active closing of near-breakeven or small-loss positions to free margin for higher-conviction opportunities. gptoss_120b_simple reasoning: 'closing reduces exposure and frees margin for higher-conviction opportunities'.

Index fund strategy of equal-weight allocation ($2...

  • Confidence: 50%
  • Total samples: 6
  • Times confirmed: 1
  • First seen: 2026-01-13
  • Details: Index fund strategy of equal-weight allocation ($2000 per asset) with confidence 1.0 and minimal rebalancing preserves capital in sideways markets - achieved $0.00 PnL while active traders lost $1395

Passive holding without frequent position changes ...

  • Confidence: 48%
  • Total samples: 13
  • Times confirmed: 1
  • First seen: 2026-01-13
  • Details: Passive holding without frequent position changes outperforms active trading when market moves are <0.1% - agents with <10 trades preserved capital while those with >100 trades lost $300-$580

Index fund strategy of equal-weight allocation ($2...

  • Confidence: 40%
  • Total samples: 6
  • Times confirmed:

...

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統計データ

インストール数665
評価4.2 / 5.0
バージョン
更新日2026年5月23日
比較事例1 件

ユーザー評価

4.2(20)
5
15%
4
45%
3
35%
2
5%
1
0%

この Skill を評価

0.0

対応プラットフォーム

🔧Claude Code
🔧OpenClaw
🔧OpenCode
🔧Codex
🔧Gemini CLI
🔧GitHub Copilot
🔧Amp
🔧Kimi CLI

タイムライン

作成2026年3月16日
最終更新2026年5月23日