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.