Professional and stable API services
Covers all MT4 / MT5 interface types with stable, reliable 99.99% availability.
Trading Strategy Customization
Customize cross-platform trading strategies based on MT4 / MT5 Client APIs, account data, order data, and risk-control rules.
- Rule-based execution
- Risk-control conditions
- Multi-account strategy management
Professional Quant Strategy Customization
Build trading strategies with professional quant code beyond traditional script limits
Based on professional languages such as Python, C++, and Java, we build modular and scalable quant trading strategy frameworks, support centralized multi-account execution, integrate with MT4 / MT5 APIs, and deliver low-latency, highly stable trade execution. From strategy research and risk-control execution to business-system integration, we deliver long-term iterable strategy solutions for quant teams, signal providers, IB teams, and asset-management institutions.
strategy_engine.pyrisk_manager.cppexecution.java
def on_tick(self, data):
signal = self.strategy.generate(data)
for sig in signal:
if self.risk.check(sig):
order = self.execution.send(sig)
self.logger.info("order sent", order)
Strategy backtest performance
Strategy equityBenchmark curve
Strategy engineStrategy Engine
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Risk engineRisk Engine
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Execution gatewayExecution Gateway
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MT4APIMT5API
Why choose professional quant strategy customization?
Professional Quant Strategy Customization vs Traditional EA
| Item | QC-Copy Quant Strategy Customization | Traditional EA | Description |
|---|---|---|---|
| Development approach | Professional languages such as Python, C++, and Java | Traditional trading scripts | Professional language ecosystems are more complete and powerful |
| Scalability | Strong; can integrate external systems, data, and APIs | Weaker; limited by the EA environment | Easier to integrate with enterprise systems |
| Multi-account execution | Supports centralized multi-account execution | Usually depends on one terminal and one account | Centralized management with higher efficiency |
| Data capabilities | Can connect databases, factors, and third-party data | Limited data sources and complex integration | More complete data and more precise strategies |
| Risk-control system | Modular, centralized risk control and unified management | Mostly built-in risk control for a single strategy | Stricter risk control with manageable risk |
| Deployment method | Service-based, server, or cloud deployment | Depends on terminals and the EA runtime environment | Higher stability with 24/7 operation |
| Maintenance collaboration | Suitable for team collaboration and version management | Fragmented maintenance and high collaboration cost | Team collaboration with more efficient iteration |
| Future expansion | Can extend to community, CRM, API, and reporting systems | Limited expansion capability | Build a complete trading business ecosystem |
Strategy development platform and technology stack
PythonC++JavaGolangRust.NETNode.js
strategy.py
import pandas as pd
from qccopy.engine import StrategyBase, DataFeed, Order
class TrendStrategy(StrategyBase):
def __init__(self, config):
super().__init__(config)
self.fast_ma = config.get("fast_ma", 20)
self.slow_ma = config.get("slow_ma", 60)
def on_bar(self, data: DataFeed):
df = data.get_klines(symbol=self.symbol, n=200)
df["ma_fast"] = df["close"].rolling(self.fast_ma).mean()
df["ma_slow"] = df["close"].rolling(self.slow_ma).mean()
if self.cross_up(df):
self.buy(Order(symbol=self.symbol, risk=0.02))
if self.cross_down(df):
self.close()
Data engineMulti-source data access and management
Backtesting engineStrategy backtesting and parameter optimization
Risk enginePortfolio risk control and risk management
Task schedulingScheduled jobs and strategy orchestration
API executionMT4 / MT5 API integration
Log monitoringLogging and real-time monitoring
Backtest performance example
2021-2024Stable upward growth
Annualized return28.57%
Max drawdown-12.34%
Sharpe ratio1.68
Win rate56.21%
Strategy customization process
01 Requirement discussionUnderstand business needs and strategy objectives in depth
02 Strategy designDefine strategy logic and the technical plan
03 Data preparationPrepare historical and factor data
04 Backtest validationHistorical backtesting and parameter optimization validation
05 Simulation runDemo-account testing and risk-control validation
06 Deployment launchLive deployment and multi-account execution configuration
07 Continuous optimizationMonitor strategy performance and continue iterative optimization
Customizable strategy types
Related extension capabilities
Create more stable execution capability for your trading business with professional quant strategies
Move beyond traditional EA files and use a professional strategy-development architecture to support long-term business growth.
API Strategy Customization
Strategy Customization
Cross-platform execution without relying on EA
Based on MT4/MT5 Client API, account data, order data, quote data, and risk-control rules, we customize cross-platform trading strategies, copy-trading strategies, risk-control strategies, and automated execution logic without relying on MT4/MT5 EA plugins.
Custom Rules
Customizable strategy and execution rules
Instead of writing an EA, we turn trading rules into API-driven software modules or services that can connect to copy-trading software, website backends, risk-control systems, and data interfaces.
Rule Library
Turn manual trading rules into API services
The focus is to split business rules into verifiable, traceable, and runnable execution modules instead of depending on an EA file inside a terminal.
- Signal filtering: filter by account, symbol, time, order type, floating profit/loss, and risk conditions.
- Lot calculation: fixed lots, balance ratio, equity ratio, tiered lots, loss-based copying, and multipliers.
- Risk-control closeout: equity protection, margin protection, loss thresholds, forced closeout, and no-copy rules.
- Batch execution: batch closeout, batch order repair, batch password changes, mobile notifications, and backend linkage.
- Symbol mapping: map and convert symbols across platforms, brokers, and suffixes.
- Martingale grid: high-frequency position adding, closing, risk boundaries, and batch order-processing rules.
- Reporting statistics: customize by yearly reports, daily reports, symbols, accounts, and customer business metrics.
- System linkage: connect CRM, membership systems, website backends, data dashboards, and risk-control systems.
Strategy Architecture
Strategy execution architecture without relying on EA
Strategies run on the server or customer VPS, obtain account, order, quote, and risk-control data through APIs, and then execute trading actions in a unified way.
Data inputAccounts, positions, history, quotes, risk thresholds, and customer business rules.
AccountQuote
Rule calculationStrategy filtering, lot calculation, symbol mapping, time windows, and risk boundaries.
RuleRisk
Execution engineOpen, close, repair orders, modify SL/TP, and run batch operations.
TradeBatch
Monitoring writebackLogs, reports, notifications, exception alerts, and backend status synchronization.
LogNotify
Scenarios
Use cases
- Multi-account risk-control executionTrigger no-copy, forced closeout, pause, or notification based on equity, margin, and floating-loss thresholds.
- Cross-platform trading rulesBring MT4 and MT5 accounts into one rule engine to handle symbol mapping, lot calculation, and order comments.
- Batch operation toolsBatch close positions, repair orders, change passwords, and check account status.
- Reporting and performance systemGenerate statistical reports by account, symbol, date, and strategy dimensions based on customer business definitions.
- Backend-linked strategiesConnect with membership systems, website backends, CRM, and authorization systems to form a complete business workflow.
Delivery Flow
Custom development flow
- 01Requirement discussionClarify trading rules, account scenarios, risk boundaries, deployment methods, and acceptance criteria.
- 02Rule confirmationSplit manual processes into executable API rules, exception-handling rules, and log fields.
- 03Technical evaluationEvaluate API capability, latency, account volume, server network, and risk limits.
- 04Development and testingComplete module development, simulation validation, small live-account traffic validation, and log tracing.
- 05VPS deploymentDeploy to the customer environment and configure networking, account permissions, notification channels, and backend monitoring.
- 06Operations and maintenanceContinuously optimize rules, reports, alerts, and API stability as the business evolves.