AI交易风险管理技能：基于数据驱动的交易频率、头寸规模与风险验证规则

risk-management by 0xhubed/agent-trading-arena

1,000 周安装量

4 GitHub Stars

GitHub

安装命令

npx skills add https://github.com/0xhubed/agent-trading-arena --skill risk-management

AI/机器学习自动化区块链

🇨🇳中文介绍

风险管理

最后更新：2026-01-17 20:31 UTC 活跃模式：40 总样本数：13385 置信度阈值：60%

核心原则

这些规则源于对盈利与亏损交易的分析：

规则	成功率	样本数	置信度	出现次数
交易数量与平...呈负相关	95%	861	55%	1x
交易频率应适应市场...	95%	950	95%	1x
在...之前明确验证每笔交易风险	92%	157	65%	1x
在...之前明确验证每笔交易风险	92%	164	70%	1x
交易频率应适应市场...

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在横盘市场中，交易数量与表现呈负相关：3-6 笔交易 ≈ $0 盈亏，70-180 笔交易 = -$55 至 -$141，150-225 笔交易 = -$325 至 -$581

成功率：95%
基于 861 次观察
置信度：55%（出现 1 次）
首次识别：2026-01-13

交易频率应适应市场状态：混合/震荡市场要求最多 0-10 笔交易/24小时。201 笔交易 = -$360.24，2 笔交易 = -$0.29，0 笔交易 = $0.00。

成功率：95%
基于 950 次观察
置信度：95%（出现 1 次）
首次识别：2026-01-17

在入场前明确验证每笔交易的风险。skill_aware_oss 推理包含"每笔交易风险在限制内"和"投资组合风险在限制内" - 此验证步骤与 +$1349 盈亏相关。

成功率：92%
基于 157 次观察
置信度：65%（出现 1 次）
首次识别：2026-01-14

在入场前明确验证每笔交易的风险，采用 2% 权益风险和 2:1 回报率。skill_aware_oss 推理包含"风险/回报为 2:1，权益风险为 2%"和"交易验证通过"，实现了最佳表现 (+$1379.66)。

成功率：92%
基于 164 次观察
置信度：70%（出现 1 次）
首次识别：2026-01-14

交易频率应适应市场状态：温和牛市要求最多 0-30 笔交易/24小时。超过 100 笔交易与亏损相关 (-$50 至 -$264)。

成功率：92%
基于 895 次观察
置信度：95%（出现 1 次）
首次识别：2026-01-17

单笔交易风险绝不超过权益的 2%
每个头寸都使用止损
在高波动性状态下减小头寸规模
不要对亏损头寸加仓

置信度	解释
90%+	高置信度 - 有强有力的历史数据支持
70-90%	中等置信度 - 需结合其他信号使用
60-70%	低置信度 - 仅作为参考输入之一
<60%	实验性 - 需要更多数据

此技能由 Observer Agent 自动生成和更新。

🇺🇸English

Risk Management

Last updated: 2026-01-17 20:31 UTC Active patterns: 40 Total samples: 13385 Confidence threshold: 60%

Core Principles

These rules are derived from analyzing profitable vs losing trades:

Rule	Success Rate	Samples	Confidence	Seen
Trade count inversely correlates with pe...	95%	861	55%	1x
Trade frequency should adapt to market r...	95%	950	95%	1x
Validate risk per trade explicitly befor...	92%	157	65%	1x
Validate risk per trade explicitly befor...	92%	164	70%	1x
Trade frequency should adapt to market r...	92%	895	95%	1x
Trade frequency should adapt to market r...	92%	855	95%	1x
Validate risk per trade explicitly befor...	92%	328	79%	2x
Optimal trade frequency in trending bull...	90%	543	75%	1x
Optimal trade frequency in trending bull...	88%	1088	79%	2x
Close losing positions proactively with ...	88%	184	75%	1x
Close short positions immediately when m...	88%	675	95%	1x
Close losing positions proactively with ...	88%	368	79%	2x
High confidence (>0.8) should require co...	85%	20	50%	1x
Close losing positions proactively with ...	85%	182	65%	1x
Position sizing at 25% equity limit per ...	85%	321	70%	1x
Diversify across multiple assets (BTC, E...	85%	494	79%	2x
Close losing positions proactively with ...	85%	100	95%	1x
Close losing positions proactively with ...	85%	368	95%	1x
Optimal trade frequency in trending mark...	82%	535	65%	1x
Diversify across multiple assets (BTC, E...	82%	348	70%	1x
Close positions near breakeven to free m...	82%	390	79%	2x
Explicit validation step before trade ex...	80%	100	95%	1x
Close positions near breakeven to free m...	80%	144	95%	1x
Diversify across assets rather than conc...	78%	248	65%	1x
Position sizing at 25% equity limit per ...	78%	125	75%	1x
Trade frequency should adapt to market r...	78%	507	95%	1x
Validate risk per trade explicitly befor...	75%	160	95%	1x
Position sizing at 25% equity limit per ...	74%	285	99%	2x
Close positions near breakeven to free m...	73%	278	99%	2x
High confidence (>0.8) should require co...	70%	20	40%	1x
Position sizing at 2% risk with 2:1 rewa...	65%	139	45%	1x
Position sizing at 25% equity limit per ...	65%	121	65%	1x
Explicit validation step ('Validate_trad...	65%	176	95%	1x
Close losing positions proactively with ...	60%	189	95%	1x
Explicit validation step before trade ex...	45%	182	95%	1x
Position sizing at 2% equity risk with 2...	35%	191	95%	1x
2% equity risk with 2:1 reward ratio fai...	35%	173	95%	1x
Explicit validation step ('Validate_trad...	35%	195	95%	1x
Position sizing at 2% equity risk with 2...	30%	171	95%	1x
Position sizing at 2% risk with 2:1 rewa...	15%	155	55%	1x

Top Risk Rules

Trade count inversely correlates with performance in flat markets: 3-6 trades = ~$0 PnL, 70-180 trades = -$55 to -$141, 150-225 trades = -$325 to -$581

Success rate: 95%
Based on 861 observations
Confidence: 55% (seen 1 times)
First identified: 2026-01-13

Trade frequency should adapt to market regime: mixed/choppy markets require 0-10 trades/24h maximum. 201 trades = -$360.24, 2 trades = -$0.29, 0 trades = $0.00.

Success rate: 95%
Based on 950 observations
Confidence: 95% (seen 1 times)
First identified: 2026-01-17

Validate risk per trade explicitly before entry. skill_aware_oss reasoning includes 'risk per trade within limits' and 'portfolio risk is within limits' - this validation step correlates with +$1349 PnL.

Success rate: 92%
Based on 157 observations
Confidence: 65% (seen 1 times)
First identified: 2026-01-14

Validate risk per trade explicitly before entry with 2% equity risk and 2:1 reward ratio. skill_aware_oss reasoning includes 'risk/reward is 2:1 with 2% equity risk' and 'trade validation passed', achieving best performance (+$1379.66).

Success rate: 92%
Based on 164 observations
Confidence: 70% (seen 1 times)
First identified: 2026-01-14

Trade frequency should adapt to market regime: moderate bull markets require 0-30 trades/24h maximum. Above 100 trades correlates with losses (-$50 to -$264).

Success rate: 92%
Based on 895 observations
Confidence: 95% (seen 1 times)
First identified: 2026-01-17

General Guidelines

Never risk more than 2% of equity on a single trade
Use stop-losses on every position
Reduce position size in high volatility regimes
Don't add to losing positions

Confidence Guide

Confidence	Interpretation
90%+	High confidence - strong historical support
70-90%	Moderate confidence - use with other signals
60-70%	Low confidence - consider as one input
<60%	Experimental - needs more data

This skill is automatically generated and updated by the Observer Agent.

Weekly Installs

912

Repository

0xhubed/agent-t…ng-arena

GitHub Stars

First Seen

Jan 24, 2026

Security Audits

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