risk-reward-ratio SKILL.md skillA
risk-reward-ratio from shubhamkumartrichy/claude-trading-skills-india is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add shubhamkumartrichy/claude-trading-skills-india/risk-reward-ratio@git:20261031.0348258Pins git:20261031.0348258 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- shubhamkumartrichy/claude-trading-skills-india
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skills/risk-reward-ratio/SKILL.md- Versions recorded
- 1
- Latest version
- git:20261031.0348258, committed Oct 31, 2026
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- 3
- License
- MIT
Risk-reward evaluation for Indian trades after real costs: R multiples per target, weighted R for scale-outs, breakeven win rate, expectancy, trade-filter thresholds, and option-specific R:R (theta, IV, premium). risk.py rr computes everything including Indian round-trip charges. Use when the user asks: "is this trade worth it", "risk reward for entry X stop Y target Z", "R:R", "expected value", "what win rate do I need", "should I take this setup", or compares multiple trade ideas.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Risk-Reward Ratio
If the maths doesn't work after costs, skip the trade. R:R is the cheapest filter there is.
## Calculator
```bash
python3 ../position-sizing/scripts/risk.py rr --entry 1800 --stop 1700 --target 2100
python3 ../position-sizing/scripts/risk.py rr --entry 1800 --stop 1700 \
--target 1900:50 --target 2000:30 --target 2200:20 --win-rate 45 --cost-pct 0.25
python3 ../position-sizing/scripts/risk.py rr --entry 450 --stop 470 --target 410 --cost-pct 0.05 # short
```
Weights after `:` are the % of the position exited at each target. `--cost-pct` is the round-trip
cost (delivery ≈0.25, intraday ≈0.05, futures ≈0.06, or exact from `trading-costs`).
## Core maths
```
R per target = (Target − Entry) ÷ (Entry − Stop) long; mirror for shorts
R after costs = (Reward − cost) ÷ (Risk + cost)
Weighted R = Σ weight × R
Breakeven win% = 1 ÷ (1 + R_after_costs)
Expectancy (R) = W × R_after_costs − (1 − W)
```
Example: entry ₹1,800, stop ₹1,700, scale out 50/30/20 at ₹1,900/₹2,000/₹2,200 gives a weighted
1.90R. With 0.25% delivery costs it is 1.78R, so the breakeven win rate is 36%. At a 45% win rate,
expectancy is +0.25R per trade.
…Read the whole file at its exact version.
How to install
mdr add shubhamkumartrichy/claude-trading-skills-india/risk-reward-ratio@sha256:5cf0b788f1324138The line at the top of this page pins the label git:20261031.0348258, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_ud472w2syfijiusd)
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Versions
The registry has recorded 1 version of this file, committed on Oct 31, 2026.
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Source
shubhamkumartrichy/claude-trading-skills-india · 3 stars · license MIT · pushed 2026-10-31 · branch main
API
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