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Portfolio risk and optimization: mean-variance, risk parity, CVaR, CDaR, worst-case, and robust optimization. Factor models, Black-Litterman, NCO. Supports plotting and interactive dashboards.
Passed 20 of 22 test cases with the skill, and 18 of 22 without it.
2 fixed18 passed either way2 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 2 test cases the skill fixed. Same model, same prompt, with and without the skill.
In Riskfolio-Lib, what parameter value is passed to obj in port.optimization to perform risk parity minimum risk optimization?
| Checked | Without skill | With skill |
|---|---|---|
| The obj parameter value is "MinRisk" | Missed | Passed |
The instructions your model reads when the skill loads.
Riskfolio-Lib provides portfolio optimization beyond mean-variance: risk parity, CVaR, CDaR, worst-case, robust optimization, NCO (Network Clustering), and hierarchical methods. Includes factor models, Black-Litterman, and built-in plotting for efficient frontiers.
uv pip install riskfolio-lib
import riskfolio as rp
import yfinance as yf
prices = yf.download(["AAPL", "MSFT", "GOOGL", "AMZN", "NVDA"], start="2022-01-01")["Close"]
returns = prices.pct_change().dropna()
port = rp.Portfolio(returns=returns)
port.assets_stats(method_mu="hist", method_cov="hist")
# Max Sharpe
w = port.optimization(model="Classic", rm="MV", obj="Sharpe", hist=True)
print("Optimal weights:", w.to_dict())
# Risk parity
w_rp = port.optimization(model="Classic", rm="MV", obj="MinRisk", hist=True)
test cases passed, vs 18 / 22 without
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