What problem does the Empirical Config Builder solve?

It eliminates 'magic numbers' or hardcoded thresholds in trading strategies that may be too restrictive or too loose for current market conditions by using actual data percentiles.

How does it calculate volume thresholds?

It uses statistical percentiles, such as the Median (P50), from actual market data in your SymbolDatabase to find representative values for the current trading universe.

Does it require real-time API calls?

It is designed to work primarily with a local SymbolDatabase to reduce redundant API calls, though it can fetch historical data for advanced correlation estimations.

Can I still keep some values fixed?

Yes, the skill distinguishes between data-driven parameters and theory-based parameters, such as Hurst exponents or regime durations, which should remain hardcoded based on financial literature.

Empirical Config Builder

Name: Empirical Config Builder
Author: smith6jt-cop

bysmith6jt-cop

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데이터 과학 및 ML

Derives trading selection thresholds from market data to replace hardcoded parameters with dynamic, data-driven values.

The Empirical Config Builder optimizes universe selection in trading systems by moving away from arbitrary constants. It analyzes market data within a SymbolDatabase to calculate dynamic thresholds for volume, price, and sector distribution based on statistical percentiles. This ensures that trading strategies adapt to current market conditions, preventing the under-filtering or over-filtering of candidates that often occurs with static, guessed parameters like fixed dollar amounts or percentage guesses.

주요 기능

01Statistical percentile derivation for volume and price thresholds

02Smart separation of theory-based fixed parameters from data-driven dynamics

03Automatic sector filtering calculation based on target candidate counts

04Advanced pairwise correlation estimation for refined risk management

05Integration with SymbolDatabase for efficient local data processing

060 GitHub stars

사용 사례

01Optimizing universe selection for stock or crypto trading algorithms

02Adapting strategy filters automatically as market volatility or liquidity shifts

03Validating and replacing arbitrary 'magic numbers' in financial models

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add smith6jt-cop/skills_registry empirical-config-builder

For use in Claude.ai and ChatGPT

Download Skill