MasQuant supports simulated transaction function
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masquant
AI Smart Trading Tool
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
Before entering the real market, build your trading rhythm first
masquant simulates ordering
The demo account provides a trading environment, market data and operation process close to the real market, so that you can be familiar with strategy execution and transaction operations under zero capital risk.
Simulate the order software
Masquan supports a variety of mainstream simulation trading platforms, which can quickly connect to strategy testing and simulate ordering.
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 products
Masquant platform supports CFD mainstream products
EURUSD
GBPUSD
audusd
usdcad
usdchf
nzdusd
EURGBP
xauusd
More products are expanding…
support market
Masquant platform
Support market type
Forex Market Data
The foreign exchange margin market is not a single centralized exchange market, but a decentralized market composed of global banks, securities companies, liquidity providers and electronic trading networks. Therefore, the foreign quotation used by Masquant is mainly based on the MT5 brokerage environment and platform data sources connected by users.
| Item | Description |
|---|---|
| FX Quotes | Provided by the MT5 broker or data source you connect |
| Historical Candlesticks | Provided by the broker, database, or licensed data source |
| Live Prices | Determined by the broker's server quotes |
| Spread | Determined by the broker, instrument, account type, and market conditions |
| Slippage | Affected by liquidity, market volatility, server latency, and execution conditions |
| Backtestable Instruments | Supported based on the MASQuant database and your broker's instrument list |
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.
faq
Frequently Asked Questions
Strategic Wizard FAQ
Who is the strategy wizard suitable for?
Strategy Genie is built for traders just starting out with quantitative trading, who aren't yet familiar with technical indicators, or who'd rather not write trading logic from scratch.
Simply answer a questionnaire about your return goals, risk tolerance, and trading needs, and the system will help generate a strategy direction you can backtest and evaluate further.
Simply answer a questionnaire about your return goals, risk tolerance, and trading needs, and the system will help generate a strategy direction you can backtest and evaluate further.
After filling out the questionnaire, how will the strategy wizard generate the strategy?
Strategy Genie generates a candidate strategy based on the investment goals, risk tolerance, market conditions, and instrument characteristics you provide.
Once generated, we recommend running a backtest first to review win rate, returns, maximum drawdown, and risk performance before deciding whether to move on to simulation or deployment.
Once generated, we recommend running a backtest first to review win rate, returns, maximum drawdown, and risk performance before deciding whether to move on to simulation or deployment.
I don't understand technical indicators, can I also use the strategy wizard?
Yes. Strategy Genie is specifically designed so that users without a programming background or familiarity with technical indicators can still start building a strategy direction, simply from a needs questionnaire.
Before going live, though, we still recommend reviewing the backtest report and risk metrics to confirm the strategy's performance matches your own risk tolerance.
Before going live, though, we still recommend reviewing the backtest report and risk metrics to confirm the strategy's performance matches your own risk tolerance.
What is Strategic Health Monitoring?
Strategy Health Monitoring helps you observe whether a strategy remains relevant as market conditions change.
It serves as a prompt for adjusting and reassessing your strategy — it does not guarantee that the strategy will maintain the same performance in future markets.
It serves as a prompt for adjusting and reassessing your strategy — it does not guarantee that the strategy will maintain the same performance in future markets.
Can the strategy generated by the strategy wizard be connected to the simulation or real disk from the backtest?
Yes — following the platform's supported workflow, you can complete strategy creation and backtesting first, then move into simulated trading; only once the results meet your needs would you evaluate deploying to a live trading environment.
This workflow reduces the gap between testing and deployment, though it does not eliminate market risk.
This workflow reduces the gap between testing and deployment, though it does not eliminate market risk.
Can I manage multiple groups of policies at the same time?
Strategy Genie supports cloud-based management of multiple strategies, making it easy to compare backtest results, risk profiles, and ongoing status across strategies.
For the exact number manageable, execution quotas, and feature limits, please refer to your current plan and product version.
For the exact number manageable, execution quotas, and feature limits, please refer to your current plan and product version.
How does the strategy wizard reduce the problem that the backtest looks good, but the real disk fails?
Strategy Genie uses backtesting, simulated trading, and Strategy Health Monitoring to help you check, before deployment, whether a strategy is overly dependent on specific historical data.
However, no backtest can guarantee future performance, so it still needs to be evaluated alongside risk-control settings and simulated testing.
However, no backtest can guarantee future performance, so it still needs to be evaluated alongside risk-control settings and simulated testing.
It is the first time to use the strategy wizard, how to start?
We recommend completing three steps first:
1. Register for a MASQuant account and choose a plan
2. Fill out the Strategy Genie questionnaire to get an evaluable strategy direction
3. Run backtests and simulated tests before deciding whether to connect an MT5 account for deployment
1. Register for a MASQuant account and choose a plan
2. Fill out the Strategy Genie questionnaire to get an evaluable strategy direction
3. Run backtests and simulated tests before deciding whether to connect an MT5 account for deployment
Do I have to have an MT5 account before using the policy wizard?
Not necessarily. If you're just building and backtesting strategies, you can start with a MASQuant account alone.
An available MT5 account is only needed once you're ready to deploy to a simulated or live trading environment, following the platform's setup process.
An available MT5 account is only needed once you're ready to deploy to a simulated or live trading environment, following the platform's setup process.
AI Policy Assistant Frequently Asked Questions
Who is the AI strategy assistant suitable for?
The AI Trading Assistant is built for traders who already have a trading idea, entry/exit conditions, or a technical-indicator concept in mind, but don't want to write the code themselves.
Just describe your strategy logic in plain language, and the system will help organize, refine, and turn it into backtestable strategy content.
Just describe your strategy logic in plain language, and the system will help organize, refine, and turn it into backtestable strategy content.
Can I describe the transaction logic directly in the vernacular?
Yes. You can enter your strategy idea in plain language, such as "enter when RSI is below 30, exit when price breaks above MA20."
The AI Trading Assistant will parse the meaning and organize it into strategy logic you can review and backtest.
The AI Trading Assistant will parse the meaning and organize it into strategy logic you can review and backtest.
Will the AI Policy Assistant help me check if the policy logic is complete?
Based on what you enter, the AI Trading Assistant flags key conditions you may have missed — such as entry, exit, stop-loss, take-profit, or timeframe — and helps produce a logic summary.
You'll still need to confirm for yourself that the finished strategy matches what you intended.
You'll still need to confirm for yourself that the finished strategy matches what you intended.
Will the AI Strategic Assistant automatically make up for risk control?
The AI Trading Assistant can help remind you of stop-loss, take-profit, timeframe, and other risk-control conditions to make your strategy logic more complete.
Which risk-control settings to actually use is still something you need to confirm based on your own capital size, risk tolerance, and trading environment.
Which risk-control settings to actually use is still something you need to confirm based on your own capital size, risk tolerance, and trading environment.
Can the policies generated by AI directly place an order?
Once an AI-generated strategy has been confirmed, backtested, and deployed, it can be used for simulated or live trading in the ways the platform supports.
Before actual use, please review the strategy content, backtest results, risk performance, and trading environment, and decide for yourself whether to adopt it.
Before actual use, please review the strategy content, backtest results, risk performance, and trading environment, and decide for yourself whether to adopt it.
Can the strategy after AI generation be modified?
If you need to adjust the conditions after a strategy has been generated, we recommend re-entering the updated description and regenerating it.
Before going live, please refer to the editing and saving functions shown in the current product interface.
Before going live, please refer to the editing and saving functions shown in the current product interface.
What risk information can be seen after the back test?
After backtesting, you can review win rate, returns, maximum drawdown, trade history, and other performance metrics; if the page offers risk visualization, charts can also show the equity curve, maximum gain, and maximum loss.
For the exact fields displayed, please refer to your product version.
For the exact fields displayed, please refer to your product version.
Do I need to be able to write programs when using AI Policy Assistant?
No coding required. The AI Trading Assistant works primarily through natural language and a web interface, so users without a programming background can build strategies, run backtests, and view results.
If you need more advanced development integration, check out our API & Developer Tools separately.
If you need more advanced development integration, check out our API & Developer Tools separately.
The first time to use AI Strategy Assistant, how to start?
We recommend starting with a simple, clearly describable strategy idea — for example, entry conditions, exit conditions, and risk-control conditions.
The workflow is: enter your strategy idea → review the logic organized by AI → run a backtest → save the strategy → deploy to a simulated or live trading environment as needed.
The workflow is: enter your strategy idea → review the logic organized by AI → run a backtest → save the strategy → deploy to a simulated or live trading environment as needed.
Does the content generated by the AI strategy assistant count as investment advice?
No. The AI Trading Assistant provides strategy-building and analysis assistance — it is not investment advice, advisory services, discretionary management, or a profit guarantee.
Whether to adopt a strategy, how to set parameters, and whether to trade with real funds remain the user's own decisions and responsibility, carrying the associated trading risk.
Whether to adopt a strategy, how to set parameters, and whether to trade with real funds remain the user's own decisions and responsibility, carrying the associated trading risk.
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.