The Intraday Trading Simulator Engine is a modular, research-friendly platform for testing algorithmic trading strategies on historical intraday stock data, powered by Python. Its mission: to give users ultimate control and flexibility with minimal effort—while staying clean, scalable, and expandable as new features (and wild trading ideas) emerge.
This simulator aims to democratize trading strategy development. Whether you're a financial prodigy, a machine learning explorer, or a Dunning-Kruger hero ("How hard can trading be, right?"), this engine lets you:
- Write simple Python trading algorithms, subscribe to as many metrics as your heart desires, and backtest instantly.
- Add your own custom metrics or use built-ins like EMA, RSI, and MACD—no setup headaches.
- Clean, abstracted Python code, so you can focus on innovation—not boilerplate or copy-paste debugging sessions.
- Experiment, iterate, and compare trading strategies and machine learning models, all under one flexible, friendly framework.
Already Shipped 🚀
- Plug-and-Play Algorithm System: Drop in your Python algorithm, hit play, and watch it run on real intraday data.
- Metric Subscriptions: Import classic or custom signals in your algo—zero effort.
- Extensible Design: Clean code and modular architecture make future expansions easy.
Coming Soon
- Real-time UI Dashboards: Live visualization of algorithm magic on charted data.
- In-Browser Code Editor: Write, debug, and run algorithms right where you see them—no more terminal tab-hopping.
- Easy Metric Builder: Create and subscribe to any metric, as easily as changing your Twitter bio.
- Machine Learning Integration: Plug in predictor and decider models, combine them for higher confidence, and toggle between training/evaluation modes with a click.
- Automated Data Cleaning & Preprocessing: Load data → Click button → Magic happens.
- Simulation Storage & Research Tools: Save every simulation run (and embarrassing misfire) to revisit and compare.
- Algorithm & Model Comparison Tools: Who wins: Your "SuperSimpleRSI" bot or the latest LSTM ensemble? Let science (and dashboards) decide!
- UI so good, you'll want to trade in it just for fun: The real-time chart dashboard that makes even boring stocks look exciting.
- Editor for lazy geniuses: In-browser Python playground for writing trading algorithms, because copy-pasting from Stack Overflow is so 2022.
- Metric buffet: all you can eat: Easy metric subscription—prebuilt or custom. Want a new indicator? Toss it in, watch it work, panic later.
- ML Model Mashups: Mix, match, and combine predictor/decider models until your signals sound smarter than your stockbroker uncle.
- Training process so easy even your pet can overfit: Select ML model, pick dataset, hit train, sip coffee, achieve trading nirvana.
- Data cleaning, but make it sparkle: Automated cleaning and preprocessing that makes your data cleaner than your kitchen after Diwali.
- Simulation time-travel: Save, revisit, and compare every simulated regret (a.k.a. trading decision combo) for research or memes.
- Documentation for actual humans: Clear guides, GIFs, and explanation memes for onboarding new users (and for future-me, who will forget all this by next month).
- Bug fixes, the eternal battle: Squash bugs, banish glitches, and never admit you missed an edge case.
- Tests: Conduct systematic tests to see if we can create an algorithm which can make profit out of given market day. Does any algorithm even give profit at all?
MIT. Use, extend, remix, and have fun—just don't sue if your "Moonshot" strategy ends up in the Mariana Trench.