ClawHub

Risk Metrics Calculation

v1.0.0

Calculate portfolio risk metrics including VaR, CVaR, Sharpe, Sortino, and drawdown analysis. Use when measuring portfolio risk, implementing risk limits, or...

⭐ 0· 271·3 current·3 all-time
by@zhengxinjipai
MIT-0
Download zip
LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
VirusTotalVirusTotal
Benign
View report →
OpenClawOpenClaw
Benign
high confidence
✓
Purpose & Capability
Name/description match the included content: SKILL.md contains detailed implementations and explanations for VaR, CVaR, Sharpe, Sortino, drawdown, and related metrics. No unrelated binaries, env vars, or config paths are requested.
✓
Instruction Scope
SKILL.md is implementation-oriented (Python examples and formulas) but does not instruct the agent to read system files, collect environment secrets, or transmit data to external endpoints. The instructions focus on local computation of risk metrics given return series.
✓
Install Mechanism
There is no install spec (instruction-only). That minimizes risk because nothing is written to disk or downloaded by the skill itself.
ℹ
Credentials
The skill requires no credentials or config paths, which is proportionate. Note: the provided Python examples depend on numpy/pandas/scipy, but the skill declares no install — ensure the execution environment has these libraries before running code.
✓
Persistence & Privilege
always is false and the skill does not request persistent privileges or modify other skills or system-wide settings. Autonomous invocation is permitted (platform default) and not a concern by itself.
Assessment
This is an instruction-only skill that provides Python implementations for portfolio risk metrics and asks for no credentials. Before installing/use: (1) verify your execution environment has numpy, pandas, and scipy if you intend to run the examples; (2) treat the code as illustrative — test and validate the calculations on known datasets before using for trading/regulatory decisions; (3) confirm how your agent/platform handles data — the skill will process any return series you supply, so avoid feeding sensitive or production data until you’re comfortable; (4) note the skill source/homepage is unknown and the author is unaffiliated in metadata — that is not proof of maliciousness but double-check provenance if you require vendor support or provenance guarantees.

Like a lobster shell, security has layers — review code before you run it.

latestvk976bfkaa41nd9jcddpgf4q4hx82ctxn

License

MIT-0
Free to use, modify, and redistribute. No attribution required.
Termshttps://spdx.org/licenses/MIT-0.html

Comments