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Optimise a portfolio with conjugate gradient v1.0.0
Use this resource to solve a portfolio optimisation with a fast method
New
- 582 downloads
- 171 likes
- 157 saves
Free
Install with the CLI
In a terminal, from the folder you want:
npx --yes palatekit@latest install portfolio-optimization-conjugate-gradientWith no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.
First time: connect the CLI with
npx --yes palatekit@latest loginThe agent solves the mean-variance system Σx = μ with conjugate gradient instead of the Neumann series. Because the covariance matrix is symmetric positive-definite, the method converges without preconditioning. The stated speed-up is forty to sixty times, with parity within 1e-4 on a fixed seed.
Mostly picked by
Updated November 2, 2026
Previews
Details
- Install guides
- Generates with
- Your agent's model
- Licence
- MIT
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What you get
- SKILL.md: solver method and rationale
- SKILL.md: stated speed and parity measurements
Good fit for
- You optimise a large portfolio
- You are comparing the speed of two solvers
Not for
Tags
- portfolio
- conjugate gradient
- optimisation
- performance
About
You say
“Solve this portfolio's mean-variance allocation with conjugate gradient and compare with the standard version.”
Skill published by ruvnet under the MIT license, delivered in its original version.
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How to use it
- Install the skill in your agent's skills folder
- Ask your agent to solve a portfolio optimisation with a fast method
- Review and adjust the result
Content preview
Files
- LICENSE1.1 KB
- NOTICE-PALATEKIT.md0.5 KB
- SKILL.md6.7 KB
Origin and licence
Listed unmodified
- Author
- ruvnet
- Source
- github.com/ruvnet/ruflo/tree/89b0cd02dd99ea1f63437fde6c05992ec53cc22b/plugins/ruflo-neural-trader/skills/trader-portfolio-cg
- Licence
- MIT
Notice
« trader-portfolio-cg » (ruvnet, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.
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