TL;DR: The MDL Asia Quant Trading Simulator is a simulation-only backtesting platform covering China A-shares, Hong Kong, US, and Malaysia markets. You write strategies in Python or indicator-style syntax (MyTT / funcat), use an AI Strategy Compiler to turn plain-language ideas into runnable code, and validate them against historical data — with zero real-money risk.
Most retail traders never test an idea before risking capital on it. Backtesting closes that gap: it replays a strategy against historical price data so you can measure how it would have performed. The MDL Asia Quant Trading Simulator was built to make that workflow accessible to quantitative researchers, algorithmic traders, and financial professionals across Asia and beyond.
What the Quant Trading Simulator is
It is a professional-grade quantitative simulation and backtesting platform — not a brokerage and not a real-money trading venue. Every order, fill, and position is simulated, which makes it a safe environment for research, education, and strategy development. Its defining feature is breadth of market coverage in a single tool:
- China A-shares (Shanghai / Shenzhen)
- Hong Kong equities
- US equities
- Malaysia (Bursa Malaysia) equities
This CN/HK/US/MY coverage matters because most simulators are single-market. A researcher comparing a momentum strategy across Greater China and US sessions can stay in one platform instead of stitching together three data sources.
Write strategies your way: Python, MyTT, or funcat
The platform offers what we call a Seamless Syntax Pool — you are not locked into one dialect:
- Python for full programmatic control, custom indicators, and complex logic.
- MyTT syntax, familiar to anyone who has used TongDaXin (通达信) indicator scripting.
- funcat syntax, modeled on TongHuaShun (同花顺) style formulas.
If you already think in indicator formulas, you can express a strategy in a few lines instead of rewriting it in Python from scratch.
The AI Strategy Compiler
The AI Strategy Compiler turns a natural-language description — "buy when the 5-day crosses above the 20-day moving average and RSI is below 70" — into runnable strategy code. It is a drafting accelerator: it gets you to a testable first version quickly, which you then refine and validate yourself.
Risk analysis and a developer API
Beyond raw backtests, the simulator surfaces risk analysis metrics so you can judge a strategy on more than headline returns — drawdown, exposure, and trade statistics that separate a robust edge from an over-fit curve. For programmatic users, a Developer API and Python SDK support automated strategy deployment and data access; contact [email protected] for API details.
Who it is for
The Quant Trading Simulator is aimed at:
- Quantitative researchers prototyping and stress-testing ideas
- Algorithmic traders validating logic before any live deployment
- Students and finance professionals learning systematic trading safely
Frequently Asked Questions
Which markets does the Quant Trading Simulator support? It supports China A-shares, Hong Kong, US, and Malaysia equity markets with historical data for backtesting and strategy validation.
Do I need to know Python? No. You can write strategies in MyTT or funcat indicator syntax, or describe them in plain language and let the AI Strategy Compiler draft the code. Python is available when you want full control.
Is this real-money trading? No. The platform is for simulation and education only. It does not execute real trades and does not constitute financial advice.
Can I automate strategies through an API? Yes. A RESTful API and Python SDK are available for programmatic backtesting and data access. Contact [email protected] for access and enterprise plans.
Get started
Explore the Quant Trading Simulator on MDL Asia, or contact our team to discuss API access and enterprise use. Build, test, and learn — without risking a cent.
Disclaimer: The Quant Trading Simulator is for simulation and educational purposes only and does not constitute investment advice.