zenith-execution

Runs Monte Carlo risk assessment and optimizes position sizing for trading portfolios.

558|75|Updated Dec 18, 2025
One-click install
npx skills add https://github.com/winstonkoh87/Athena-Public --skill zenith-execution
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: zenith-execution
Source: https://github.com/winstonkoh87/Athena-Public/tree/main/examples/skills/decision/zenith-execution
Command: npx skills add https://github.com/winstonkoh87/Athena-Public --skill zenith-execution

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

High-variance trading decisions are hard to size and manage; Zenith Execution provides a deterministic framework for position sizing, stop-loss determination, Monte Carlo risk assessment, and portfolio rebalancing.

Core Features & Use Cases

  • Position Sizing (Half-Kelly): calculates optimal Kelly fraction, halves it for practical execution, with a hard cap to limit risk.
  • Stop-Loss (Structural Invalidation): identifies a validation point distance and maps risk to position size to protect capital.
  • Monte Carlo Simulation: runs many synthetic paths to estimate median outcomes, drawdowns, and ruin probabilities.
  • Portfolio Rebalance: evaluates drift from targets and outputs actions to restore allocation parity.

Quick Start

Execute a Monte Carlo simulation with a 60% win rate, 1:1 reward-to-risk, 1% risk per trade, a fixed number of trades, and starting capital, then report the median final equity and maximum drawdown.

Frequently Asked Questions about zenith-execution

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I calculate position sizing using Half-Kelly for trading execution?▼

Position sizing using Half-Kelly calculates the optimal Kelly fraction for a trade, halves it for practical execution to reduce variance, and applies a hard cap to limit total risk exposure.

What is Monte Carlo risk assessment and how does it estimate trading drawdowns?▼

Monte Carlo risk assessment runs many synthetic price paths to estimate median outcomes, maximum drawdowns, and ruin probabilities for a portfolio under parameterized trading scenarios.

How do I calibrate a stop-loss based on structural invalidation points?▼

Stop-loss calibration identifies the distance to a structural validation point and maps that risk distance directly to the position size to protect trading capital from adverse moves.

Can I use this framework for portfolio rebalancing and allocation drift correction?▼

Yes, portfolio rebalancing evaluates current allocation drift from target weights and outputs specific actions needed to restore allocation parity across the portfolio.

What inputs do I need to run a Monte Carlo simulation for trading risk management?▼

You need to parameterize win rate, reward-to-risk ratio, risk per trade percentage, number of trades, and starting capital to execute a Monte Carlo simulation and report median equity and drawdown.

Does this trade execution framework require any external dependencies or libraries?▼

No, the trade execution framework operates independently with no external dependencies, providing deterministic outputs for position sizing and risk controls directly within the environment.