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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
One-click install
npx skills add https://github.com/sujaynsv/Agentic-Skills --skill backtest-expert-sujaynsv
Or copy as Structured Prompt for Agent▼
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.

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