risk-management

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Risk management rules learned from competition outcomes. Use when sizing positions or setting stop-losses.

التثبيت

التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.

المصدر

zinan92

zinan92/copilot

فتح مستودع GitHub عرض مستودعات المنشئ

تنزيل

المهن ذات الصلةSOC

استنادا إلى تصنيف SOC المهني

محللو التمويل والاستثمارمهن الأعمال والعمليات المالية·SOC 13-2051

مستكشف الملفات

3 ملفات

SKILL.md

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name	risk-management
description	Risk management rules learned from competition outcomes. Use when sizing positions or setting stop-losses.
platform	openclaw
scope	global

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.

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name	risk-management
description	Risk management rules learned from competition outcomes. Use when sizing positions or setting stop-losses.
platform	openclaw
scope	global

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.