Masquant SDK
Masquant SDK
Quantitative trading strategy developer dedicated
Frame-free setting and cumbersome data sources, you can complete the complete policy backtesting process within 10 minutes with just a few lines of Python code.
core function
Masquant SDK function
Eliminating the tedious framework and environment settings, just install a single set, you can load data, verify policies and output results through a simple API.
Built-in Sharpe Ratio, maximum retracement, annual rate of return and other performance indicators, and automatically generate visual reports to quickly grasp the strategy performance and risk structure.
Automatically output backtest reports and charts, including each transaction record, daily net value curve and statistical abstract, so that the strategy performance is clear at a glance, and it is convenient to compare and optimize.
Lightweight one-click tool
Modular performance analysis
Full and transparent data presentation
Masquant SDK
Examples of online files and programs
backtesting tool
Masquant backtest report tool
MasQuant Backtesting Report Tool is specially created for quantitative traders. Free installation of Python or additional kits can be used to quickly execute policy backtesting, view complete performance reports, and support data export, so as to easily complete policy verification.
Verify each set of trading strategies in a way closer to the real market
Masquant backtest engine
Closer to the real market, verify each set of trading strategies
Masquant backtest engine
MasQuant has a built-in professional backtesting engine, which integrates historical data, real-time market conditions and simulated transactions, allowing you to complete the complete verification of the strategy through the process of approaching the real market before the strategy is deployed.
Masquant backtest engine
core function
Data source and security management
With compliance, information security and transparency as the core, Masquant creates an international quantitative trading platform that allows investors, strategy developers and trading teams and B2B partners to use it with peace of mind.
Support major major brokerages
European and Global Exchange Data Support
Masquant currently integrates financial market data with the MT5 environment.
Support major global brokerages
Support Brokerage
MASQUANT platform — support 90% of the world’s brokers
MasQuant platform —
Support 90% of brokers in the world
Support 90% of the world’s securities companies, and there are more lists that cannot be listed in all
support market
Masquant platform support market type
The MasQuant SDK can directly connect to the brokerage environment that supports MT5, and access all the transaction products provided by the broker.
Enterprise-level security mechanism
Adopt a high-standard enterprise-level information security mechanism, do not operate on behalf of, do not transmit sensitive data, do not access customer accounts, all transactions and operations are completed in your control.
System Compatibility Description
Currently only supported for Windows computers:MasQuant transaction-related functions currently mainly support Windows computers, including policy execution file download, MT5 connection, automatic transaction setting and policy execution and other functions.
If you need to use the following functions, use the Windows PC
Currently not supported
The MasQuant team will continue to evaluate support for more platforms
In order to ensure the function of policy execution, MT5 connection and automatic transaction function, it is recommended to use a Windows computer for installation, setup and operation. The Masquant team will continue to evaluate the possibility of more platforms support, and will be announced separately if macOS or other systems are supported in the future.
faq
Frequently Asked Questions
Masquant SDK FAQ
What is the Masquant SDK?
The MASQUANT SDK is MASQuant's Python quantitative trading SDK.
It provides strategy backtesting, performance analysis, trading signal generation, report export, and MT5 integration — helping developers and trading teams follow a standardized workflow for strategy development, validation, and pre-deployment analysis, the same rigor institutional quant desks rely on.
It provides strategy backtesting, performance analysis, trading signal generation, report export, and MT5 integration — helping developers and trading teams follow a standardized workflow for strategy development, validation, and pre-deployment analysis, the same rigor institutional quant desks rely on.
Are the MasQuant SDK and Masquant the same product?
No. MASQuant is the complete platform brand, providing the AI Trading Assistant, strategy backtesting, strategy management, subscription plans, and strategy deployment services.
The MASQUANT SDK is MASQuant's underlying Python SDK, responsible for strategy logic execution, backtest calculation, performance analysis, data processing, and MT5 integration.
MASQuant is the platform; the MASQUANT SDK is the underlying technology toolkit.
The MASQUANT SDK is MASQuant's underlying Python SDK, responsible for strategy logic execution, backtest calculation, performance analysis, data processing, and MT5 integration.
MASQuant is the platform; the MASQUANT SDK is the underlying technology toolkit.
Can I use the Masquant SDK without writing a program?
Yes, though we recommend starting with the official documentation to learn the basics first.
The MASQUANT SDK is a Python SDK aimed primarily at developers and strategy researchers with basic Python skills. That said, it comes with complete documentation that walks you through everything from environment setup and data loading to writing strategies, running backtests, and generating reports.
You can learn the fundamentals and see example applications on the official documentation site. Even if you're not comfortable with code at first, you can follow the examples step by step to build your own strategy-backtesting workflow.
If you'd prefer a more intuitive way to work, you can also pair the MASQuant platform or MASQuant.Soft with the graphical interface and AI Trading Assistant to generate, backtest, and deploy strategies.
The MASQUANT SDK is a Python SDK aimed primarily at developers and strategy researchers with basic Python skills. That said, it comes with complete documentation that walks you through everything from environment setup and data loading to writing strategies, running backtests, and generating reports.
You can learn the fundamentals and see example applications on the official documentation site. Even if you're not comfortable with code at first, you can follow the examples step by step to build your own strategy-backtesting workflow.
If you'd prefer a more intuitive way to work, you can also pair the MASQuant platform or MASQuant.Soft with the graphical interface and AI Trading Assistant to generate, backtest, and deploy strategies.
Can the Masquant SDK integrate with MT5 or place an order directly?
Yes. The MASQUANT SDK can read MT5 instrument data, pull historical candlesticks, generate trading signals, run simulated trading tests, and help validate strategies before live deployment.
Using the MASQUANT SDK does not mean the platform trades on your behalf, and it does not constitute discretionary trading, asset management, or investment advisory services.
Using the MASQUANT SDK does not mean the platform trades on your behalf, and it does not constitute discretionary trading, asset management, or investment advisory services.
Which products and sources support the Masquant SDK?
Primarily supports forex, precious metals, index CFDs, energy CFDs, commodity CFDs, and select stock CFDs within the MT5 broker environment.
Common instruments include EURUSD, GBPUSD, USDJPY, XAUUSD, XAGUSD, US30, NAS100, SPX500, GER40, USOIL, and UKOIL.
Actual instrument coverage and available data history depend on your broker's instrument list, data source, and account permissions.
Common instruments include EURUSD, GBPUSD, USDJPY, XAUUSD, XAGUSD, US30, NAS100, SPX500, GER40, USOIL, and UKOIL.
Actual instrument coverage and available data history depend on your broker's instrument list, data source, and account permissions.
Will the backtest result of the Masquant SDK be equal to the real transaction result?
It won't be identical to live trading results, but the MASQUANT SDK is built to minimize the gap between backtested and real-world outcomes.
Differences between backtest and live results can arise from spread changes, slippage, execution delay, broker quote variance, insufficient liquidity, trading-session restrictions, fees, overnight interest, historical data quality, and differences in the strategy's execution environment.
The MASQUANT SDK is a tool for strategy development, backtesting, and analysis — it does not provide individualized investment advice and does not guarantee any strategy's future performance. All strategies, signals, backtest reports, and KPI results are provided solely as reference for the user's own judgment and technical analysis.
Differences between backtest and live results can arise from spread changes, slippage, execution delay, broker quote variance, insufficient liquidity, trading-session restrictions, fees, overnight interest, historical data quality, and differences in the strategy's execution environment.
The MASQUANT SDK is a tool for strategy development, backtesting, and analysis — it does not provide individualized investment advice and does not guarantee any strategy's future performance. All strategies, signals, backtest reports, and KPI results are provided solely as reference for the user's own judgment and technical analysis.
Will the Masquant SDK save my transaction funds, account password or policy information?
Neither the MASQUANT SDK nor MASQuant provide custodial fund services, and neither handles deposits, withdrawals, or fund transfers. All funds remain in the user's own broker account at all times.
Trading account passwords are never stored in plain text.
When connecting to MT5 or a broker environment, login credentials are managed by the user; if the system needs to store related information, it does so under encryption.
Whether strategy data is stored depends on how you use the platform.
When used locally, strategy data stays on your own computer; if you use MASQuant's cloud features, strategy data may be stored on the platform as needed to support strategy management, backtest records, and license verification.
Trading account passwords are never stored in plain text.
When connecting to MT5 or a broker environment, login credentials are managed by the user; if the system needs to store related information, it does so under encryption.
Whether strategy data is stored depends on how you use the platform.
When used locally, strategy data stays on your own computer; if you use MASQuant's cloud features, strategy data may be stored on the platform as needed to support strategy management, backtest records, and license verification.
About the backtest engine
What is the Masquant backtest engine?
The MASQuant Backtest Engine validates strategy performance under near-real market conditions before deployment, using historical data, live-market logic, and simulated trading flows.
It's not just a historical performance readout — it gives you a consistent workflow to manage strategies all the way from generation and backtesting through simulation, deployment, and performance tracking.
It's not just a historical performance readout — it gives you a consistent workflow to manage strategies all the way from generation and backtesting through simulation, deployment, and performance tracking.
What is the difference between Masquant backtesting and general only looking at historical performance?
Standard historical performance is mostly a backward-looking snapshot; the MASQuant Backtest Engine instead brings data integration, format conversion, technical-indicator calculation, the trading model, simulated order execution, and simulated fills together in a single framework.
This lets a strategy be validated, before deployment, in a way that more closely mirrors the real trading process.
This lets a strategy be validated, before deployment, in a way that more closely mirrors the real trading process.
Why do backtesting and real trading use a consistent transaction architecture?
When backtesting and live trading use different data-processing methods or different execution pipelines, a strategy can show a performance gap once it goes live.
MASQuant routes both historical data and live market data through the same data-integration pipeline before format conversion and indicator calculation, narrowing the technical gap between backtest and live trading.
MASQuant routes both historical data and live market data through the same data-integration pipeline before format conversion and indicator calculation, narrowing the technical gap between backtest and live trading.
Will the backtest engine simulate trading behavior?
MASQuant's backtest architecture doesn't just simulate price — it also incorporates simulated order execution and fill flows, helping strategy tests more closely mirror real trading execution.
For the exact fill logic, latency, slippage, and market-friction factors supported, please refer to the product version and official technical documentation.
For the exact fill logic, latency, slippage, and market-friction factors supported, please refer to the product version and official technical documentation.
What performance indicators can you see in the backtest?
Backtest performance data currently available includes number of trades, profit/loss ratio, win rate, maximum drawdown, total return, annualized cumulative return, and Sharpe ratio.
For the exact fields displayed, please refer to the current version's page.
For the exact fields displayed, please refer to the current version's page.
What does the backtest report contain?
A backtest report typically includes backtest data, performance metrics, risk metrics, charts, trade history, and a strategy summary.
This information helps you judge whether a strategy has long-term viability, rather than looking only at a single win or loss.
This information helps you judge whether a strategy has long-term viability, rather than looking only at a single win or loss.
How long is the backtest of historical data supported?
Backtesting currently supports up to five years of historical data.
The available historical data range depends on the current product version, instrument support, and data source. For the exact backtestable period, please refer to what's shown in the product.
The available historical data range depends on the current product version, instrument support, and data source. For the exact backtestable period, please refer to what's shown in the product.
Can the strategy be retested and optimized repeatedly?
Yes. Once a strategy is built, you can backtest it with historical data, then move into simulated trading for validation, and only then evaluate whether to deploy it to a live trading environment.
This creates an iterative strategy-development workflow, letting you repeatedly test, adjust, and compare different strategy versions.
This creates an iterative strategy-development workflow, letting you repeatedly test, adjust, and compare different strategy versions.
Do I need to rewrite the transaction program from back-test to real deployment?
MASQuant designs backtesting, simulation, and live trading within a single unified framework, specifically to reduce the rewrite cost and process gaps as a strategy moves from testing to deployment.
The exact deployment method still depends on the product version, broker environment, and MT5 configuration.
The exact deployment method still depends on the product version, broker environment, and MT5 configuration.
How can I tell if a strategy is worth deploying?
At minimum, we recommend evaluating together: whether the backtest results are stable, whether the risk falls within an acceptable range, whether the instrument and market conditions match your expectations, whether your capital and risk tolerance are a good fit, and whether you're satisfied with the simulated-account test results.
If any of these remain unclear, we recommend holding off on live trading.
If any of these remain unclear, we recommend holding off on live trading.
How long is the backtest of historical data supported?
Backtesting currently supports up to five years of historical data.
The available historical data range depends on the current product version, instrument support, and data source. For the exact backtestable period, please refer to what's shown in the product.
The available historical data range depends on the current product version, instrument support, and data source. For the exact backtestable period, please refer to what's shown in the product.
Can the strategy be retested and optimized repeatedly?
Yes. Once a strategy is built, you can backtest it with historical data, then move into simulated trading for validation, and only then evaluate whether to deploy it to a live trading environment.
This creates an iterative strategy-development workflow, letting you repeatedly test, adjust, and compare different strategy versions.
This creates an iterative strategy-development workflow, letting you repeatedly test, adjust, and compare different strategy versions.
Do I need to rewrite the transaction program from back-test to real deployment?
MASQuant designs backtesting, simulation, and live trading within a single unified framework, specifically to reduce the rewrite cost and process gaps as a strategy moves from testing to deployment.
The exact deployment method still depends on the product version, broker environment, and MT5 configuration.
The exact deployment method still depends on the product version, broker environment, and MT5 configuration.
How can I tell if a strategy is worth deploying?
At minimum, we recommend evaluating together: whether the backtest results are stable, whether the risk falls within an acceptable range, whether the instrument and market conditions match your expectations, whether your capital and risk tolerance are a good fit, and whether you're satisfied with the simulated-account test results.
If any of these remain unclear, we recommend holding off on live trading.
If any of these remain unclear, we recommend holding off on live trading.
Does the backtest results mean that the future will definitely make money?
No, it does not. Historical performance, backtest data, and illustrative results are provided only to help you understand a strategy's logic and risk characteristics — they should not be taken as a guarantee of future performance.
Real markets remain subject to volatility, liquidity, slippage, broker execution conditions, and other factors beyond anyone's control.
Real markets remain subject to volatility, liquidity, slippage, broker execution conditions, and other factors beyond anyone's control.
What is the difference between backtesting and simulated trading?
Backtesting uses historical data to examine how a strategy would have performed under specific past conditions; simulated trading, by contrast, lets you get familiar with strategy execution and trading operations in an environment close to live markets.
The recommended order is: backtest first, then simulate, and only then evaluate whether to move into live trading.
The recommended order is: backtest first, then simulate, and only then evaluate whether to move into live trading.
What should I do when I can't run the result in the backtest?
Please first check that your strategy conditions are complete, that the instrument and data range are supported, and that your parameter settings are reasonable.
If the product interface offers a clear or reset function, you can also reset your strategy conditions and try again. Contact support if needed.
If the product interface offers a clear or reset function, you can also reset your strategy conditions and try again. Contact support if needed.