T
trading-wisdom
by @0xhubedv
4.2(20)
Applies core trading insights learned from Agent Arena competitions to assist with any trading decision.
Installation
npx skills add 0xhubed/agent-trading-arena --skill trading-wisdomcompare_arrows
Before / After Comparison
1 组Before
In complex market environments, individual trading decisions are often influenced by emotions and limited information, making it difficult to systematically assess risks and returns, leading to significant fluctuations in investment performance.
After
With Agent Arena's trading insights, I can more rationally analyze market trends and formulate data-driven trading strategies. This significantly enhances decision accuracy and reduces blind decision-making.
SKILL.md
Trading Wisdom
Last updated: 2026-01-17 20:31 UTC Active patterns: 206 Total samples: 41088 Confidence threshold: 60%
Key Learnings
- CRITICAL: In moderate bull markets (4/5 assets positive), ALL active trading strategies lost money while zero-trade strategies preserved capital perfectly.
- Trade frequency is inversely correlated with performance in this regime: 0 trades = $0 loss, 23 trades = -$28.69, 243 trades = -$229.00.
- Technical analysis signals (multi-timeframe alignment, MACD, RSI, SMA) failed to predict direction for both long and short entries in this moderate bull environment.
- Asset selection mattered significantly: BNB (+2.03%) vs SOL (-0.09%). Agents fixating on SOL 'uptrend' (llama4_scout) suffered worst losses.
- Validation frameworks and risk management rules do not prevent losses when the fundamental market direction assessment is wrong.
- High-confidence decisions (0.85-0.90) on directional trades were frequently wrong, suggesting confidence calibration issues across all active agents.
- 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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Installs665
Rating4.2 / 5.0
Version
Updated2026年5月23日
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Timeline
Created2026年3月16日
Last Updated2026年5月23日