backtest-expert

Validates trading strategies on Indian markets with JSON/Markdown reports and red-flag detection.

Updated Mar 19, 2026

Search Tags:#backtesting #cost-modeling #walk-forward #nse #bse #indian-markets #edge-analysis

Ready to run

npx skills add https://github.com/sujaynsv/Agentic-Skills --skill backtest-expert-sujaynsv

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: backtest-expert
Source: https://github.com/sujaynsv/Agentic-Skills/tree/main/skills/trading/indian-trading-skills/skills/backtest-expert
Command: npx skills add https://github.com/sujaynsv/Agentic-Skills --skill backtest-expert-sujaynsv

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Backtesting guidance to validate and stress-test trading strategies on Indian markets (NSE/BSE), incorporating realistic costs and scenario analysis to prevent overfitting.

Core Features & Use Cases

Stepwise framework: 6-step backtesting process covering hypothesis, rules, data, and evaluation
Indian market cost modeling: includes brokerage, STT, exchange charges, GST, stamp duty, SEBI charges, and slippage
Walk-forward and out-of-sample validation: ensures generalization across regime changes
Red-flag detection and deployment criteria: objective scoring and decision framework
Reference methodologies and failed-tests: access to methodology and failure pattern resources

Quick Start

Follow the six-step backtesting workflow to evaluate your trading idea on NSE/BSE and generate an objective report.

Frequently Asked Questions about backtest-expert

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

FAQPage Schema

How do I backtest trading strategies for NSE and BSE with realistic Indian market costs?▼

Backtesting NSE and BSE strategies requires modeling brokerage, STT, exchange charges, GST, stamp duty, SEBI charges, and slippage to generate cost-aware performance assessments and prevent overfitting.

What is walk-forward validation and why is it needed for Indian market backtesting?▼

Walk-forward validation ensures trading strategies generalize across regime changes by testing out-of-sample data, preventing overfitting and confirming robustness for deployment in dynamic Indian market conditions.

How do I run parameter sensitivity analysis and detect red flags in a trading strategy?▼

Parameter sensitivity analysis evaluates strategy robustness while red-flag detection applies objective scoring across sample size, expectancy, risk management, robustness, and execution realism to output deployment criteria.

What is the best way to stress-test an NSE edge analysis hypothesis before deployment?▼

Stress-test NSE edge analysis by applying a six-step framework covering hypothesis, rules, data, and evaluation, concluding with an objective JSON or Markdown report containing deployment decisions.

Does this backtesting framework generate reports in JSON or Markdown format?▼

The framework outputs both JSON and Markdown reports containing cost-aware performance metrics, five-dimension evaluation scores, and red-flag detection for objective strategy deployment decisions.