algo_scalper_api

Validate the correctness, realism, and statistical validity of options backtests. Detect implementation errors, data leakage, execution issues, overfitting, and unrealistic assumptions before accepting any trading strategy.

Comprehensive broker integration for market research, backtesting, paper trading, and live execution using DhanHQ APIs.

Research, evaluate, optimize, and validate technical indicators and derived features for Indian index option buying strategies using DhanHQ market data.

Perform comprehensive quantitative market research for Indian index options trading using DhanHQ market data. Analyze trend, volatility, liquidity, market structure, option chain, and regime before any strategy development or backtesting.

Perform institutional-grade market structure analysis on Indian index prices. Detect swing points, Break of Structure (BOS), Change of Character (CHOCH), liquidity sweeps, ranges, and compressions before strategy development.

Evaluate trading strategy robustness using Monte Carlo simulations with realistic market, execution, and portfolio perturbations for long-only options trading.

Perform institutional-grade option chain analysis for Indian index options using DhanHQ APIs. Analyze liquidity, open interest, implied volatility, Greeks, dealer positioning, strike quality, and directional opportunities for long-only CE/PE strategies.

Execute strategies in a production-identical environment using a virtual broker that accurately models Dhan order execution, option chain behaviour, slippage, commissions, latency and portfolio management.

Perform institutional-grade quantitative analysis of completed backtests, paper trading sessions, and live trading performance for long-only index options.

Institutional-grade risk engine for long-only index options. Validate every trade, portfolio, and strategy before execution using quantitative risk models and configurable limits.

Generate, evolve, validate and rank institutional-grade long-only index option trading strategies using objective quantitative research.

Manage open option positions from entry until final exit using adaptive stop losses, trailing logic, volatility analysis, market structure and risk management.

Research, compare, optimize and validate trailing stop methodologies for long-only options trading using historical market data, option chain data and completed trades.

Validate trading strategies using rolling in-sample and out-of-sample optimization to measure robustness, parameter stability, and generalization for long-only options trading.

Rails Style Guide (rails.rubystyle.guide) conventions for configuration, routing, controllers, models, Active Record, migrations, views, mailers, and testing. Use when writing or reviewing Rails/Ruby on Rails code.

RSpec best practices from the RSpec Style Guide and Better Specs. Use when writing or reviewing RSpec specs, request specs, model specs, or integration tests in Ruby/Rails projects.

Ruby skills bundle. Contains Ruby-oriented SOLID, TDD, clean code, Ruby Style Guide, Rails Style Guide, RSpec/Better Specs, and design-pattern guidance. Use when working with Ruby or Rails code.

Ruby-focused. Transforms junior-level code into senior-engineer quality software through SOLID, TDD, and clean code. Examples and references use Ruby/RSpec. Use when writing or refactoring Ruby code, planning architecture, reviewing code, or creating tests.

Ruby Style Guide (rubystyle.guide) conventions. Use when writing, formatting, or reviewing Ruby code for layout, naming, flow of control, methods, classes, and idioms. Complements RuboCop.