Before you size the trade: compute the loss distribution, run the stress tests, name the binding cap, and get a blunt verdict — Kelly / vol-targeting, VaR / ES, Sharpe / Sortino / Calmar / UPI, concentration and leverage caps, and risk-of-ruin asymmetry included.
Works with: Claude Code · OpenAI Codex · Cursor · GitHub Copilot · Gemini CLI · 26+ tools that support portable agent skills.
Clone the skill into your agent's skills directory:
# Claude Code
git clone https://github.com/Viprasol-Tech/risk-management-review \
~/.claude/skills/risk-management-review
# OpenAI Codex
git clone https://github.com/Viprasol-Tech/risk-management-review \
~/.codex/skills/risk-management-review
# Cursor / Gemini CLI / other tools — clone anywhere your tool loads skills from, e.g.
git clone https://github.com/Viprasol-Tech/risk-management-review \
~/.config/skills/risk-management-reviewThe skill is a single self-contained skill.md (plus examples) — no
dependencies, no install step, nothing to build.
Paste your inputs and ask:
Vet this position size — long XYZ, μ=12% annualised, σ=35%, R_f=5%,
NAV=$100k, leverage 1.5×. Is it too big?
The skill will scope the review, apply Kelly (f* = (μ − r) / σ²) and
half-Kelly, run the vol-target sizing, check it against the single-name cap,
flag risk-of-ruin if relevant, and return a verdict banner
(✅ / 🟡 / 🟠 / ⛔) with concrete sizing recommendations.
Most trading losses aren't a bad call on direction — they're a bad call on size, on leverage, or on how a "diversified" book behaves when correlations go to 1. A 50% drawdown requires +100% to recover; 80% needs +400%; asymmetry kills compounders. Pure Kelly is almost always over-sized in practice; parametric-normal VaR systematically understates fat tails; Sharpe above 3 on a non-HFT strategy is usually over-fit, not edge. The defense is a consistent, formulas-on-the-table risk review — compute the loss distribution, size with half-Kelly or a vol target, cap single-name and factor exposure, and stress-test what could actually kill the book. This skill encodes that review so your agent runs it the same way every time.
- Scopes the review — single position, strategy, or multi-asset portfolio — and pins down which inputs (returns series, weights, leverage, correlations, scenarios) are available.
- Computes the loss distribution — σ, σ_d, MDD + duration, Ulcer Index, VaR_95, ES_97.5 — with explicit formulas and the fat-tail caveat.
- Picks the right risk-adjusted return metric — Sharpe vs Sortino vs Calmar vs UPI vs Information Ratio — and flags gameable patterns (Sharpe > 3, autocorrelation, Sortino << Sharpe).
- Reviews position sizing — applies Kelly
f* = (μ − r) / σ²and the half-Kelly default, vol-targetingnotional_i = target_vol × NAV / σ_i, and Optimal f; flags missing or gut-feel sizing. - Checks concentration, correlation & leverage — single-name cap, top-3 share, factor/sector caps, pairwise ρ → 1 stress, gross/net leverage, and % of ADV.
- Runs the stress catalog — 1987, 2008, 2020-Mar, 2022 bond rout, 2023-Mar SVB, plus +1σ vol shock, -10% equity / +200bp rates, correlation → 1, liquidity haircut, and a reverse stress test ("what move kills the book?").
- Calls out risk-of-ruin with the recovery-asymmetry math when sizing or leverage make a fatal drawdown a plausible path.
- Outputs a verdict (✅ Within risk policy / 🟡 Caution / 🟠 Over-risk / ⛔ Likely-ruin path), a risk dashboard, a position dashboard, a sizing review, a stress-test table, and a concrete recommendations list.
- Full risk dashboard — σ, σ_d, MDD, MDD duration, Ulcer Index, Sharpe, Sortino, Calmar, UPI, VaR_95, ES_97.5 — one table the user can re-run.
- Sizing engine — Kelly, half-Kelly default, vol-targeting, Optimal f, with the binding-cap rule (lower of half-Kelly, vol-target, and single-name cap).
- Concentration + leverage caps — 10% single-name, 40% top-3, gross > 3× without stops = flag.
- Stress-test catalog — three historical replays + two hypotheticals + a reverse stress test, mandatory.
- Risk-of-ruin asymmetry baked in —
-50% → +100%,-80% → +400%, with the recovery formula on the table. - Red-flag scan — Sharpe > 3, single-name > 15%, MDD < 5% over 6+ months (hidden tail), parametric-normal VaR on fat tails, no drawdown duration.
| Metric | Formula | Best for |
|---|---|---|
| Sharpe | (R − R_f) / σ |
Roughly symmetric returns; broad comparability |
| Sortino | (R − MAR) / σ_d |
Asymmetric payoffs (options, trend following) |
| Calmar | `annualised return / | MDD |
| UPI | (R − R_f) / UI |
"Did I sleep at night?" — penalises underwater time |
| Information Ratio | active return / tracking error |
Benchmark-relative strategies |
Pick the metric that matches the strategy's payoff shape — never quote raw return alone.
See full worked reports in examples/:
- Single-position sizing — long XYZ μ=12% σ=35%, full Kelly ≈ 57%, half-Kelly ≈ 29%, single-name cap binds at 10% → 🟠 OVER-RISK.
- Multi-asset portfolio review — 35% TQQQ / 25% BTC / 20% NVDA / 15% SVXY / 5% cash; top-3 = 80%, embedded 3× leverage, short-vol tail, reverse stress fails at SPY -8% → ⛔ LIKELY-RUIN PATH.
This skill provides educational risk-management guidance only — not financial, legal, or investment advice, and not a guarantee of safety. It reasons only over the information you provide; without numbers, output is qualitative. Risk metrics describe history and assumed distributions; they do not predict the next regime shift. Markets do things that have never happened before — size below your pain threshold, and consult a qualified risk or investment professional for live decisions. Not affiliated with or endorsed by Anthropic.
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