Automate Your Alpha.
Deploy with Matrix SaaS.
Market Matrix LLC provides professional strategy automation software, low-latency cloud backtesting infrastructure, and clean SDK wrappers engineered for systematic quant traders.
Cloud Infrastructure Built For Execution
Develop, validate, and launch sophisticated trading systems on standard managed servers.
High-Speed Cloud Backtester
Run complex multi-factor simulations over 10 years of tick-by-tick historic market data in minutes. Access vectorized matrix engines to parse parallel calculations without crashing your browser environments.
Direct Broker Gateways
Seamlessly deploy live signals directly through unified APIs connecting to leading trading brokerages, clearers, and digital asset portals with strict error-handling configurations.
Sandboxed Strategy Nodes
Every algorithm runs inside secure, containerized cloud runtime execution spaces. Private client keys and workspace variables are protected via full envelope encryption standards.
Unified Dashboard Interface
Monitor open strategies, execution statuses, equity growth curves, Drawdown caps, and real-time Sharpe metrics in an intuitive interface containing customizable grid metrics.
Multi-Broker Feed Consolidation
Direct view inside unified level-2 books tracking aggregated price structures across connected partners.
Asks (Consolidated Sellers)
Bids (Consolidated Buyers)
Clean SDK Integration Guides
Deploy your custom logic, quantitative scripts, and machine learning models straight into the execution cloud via modern APIs.
- Python Client SDK: Easy-to-use functions to backtest and place live orders programmatically with a few lines of code.
- Streaming WebSockets: Access instant updates on level-2 books, current strategy statuses, and overall account equity balances.
- REST Gateway: Simple endpoints to review historical backtest logs, tweak active configurations, and verify platform settings.
import market_matrix_saas as mms
client = mms.TradingEngine(
api_key="mm_live_7x92f...",
workspace_id="workspace_83j21..."
)
# Define a trend-following logic class
def on_tick(data):
if data.close > data.sma_50:
client.buy("XAU_USD", qty=10.0)
# Initialize backtester over 5 years of historical data
backtest = client.run_backtest(
strategy=on_tick,
pair="XAU_USD",
timeframe="1h",
period_years=5
)
# Deploy the live strategy agent on active nodes
agent = client.deploy_live(strategy=on_tick)Flexible Software Tier Options
Select the subscription model that scales with your strategy complexity and testing bandwidth.
- Simultaneous Runs: 3 Engines
- Backtesting: 1 Year History
- API Limit: 100 req/min
- Simultaneous Runs: 20 Engines
- Backtesting: Full Historic Tick
- API Limit: 1000 req/min
- Simultaneous Runs: Unlimited
- Backtesting: Custom Datasets
- API Limit: Custom Broker Channels
High-Speed Server Cloud Nodes
Run your strategies adjacent to major financial and cloud hosting exchanges.
AWS West (Oregon)
Equinix NY4
AWS London
Google Tokyo
Supported Broker Integrations
Connect your strategy directly to your chosen clearing channels and prime broker platforms.
| Broker/Exchange | Asset Classes Supported | API Style | Avg Routing Latency | Integration Method |
|---|---|---|---|---|
| Interactive Brokers | Equities, Options, Futures, FX | REST / WebSockets | 12ms - 25ms | OAuth Gateway Connection |
| Binance / Coinbase | Spot & Perpetuals (Crypto) | REST / Native WebSockets | 8ms - 15ms | Secure Custom API Keys |
| Match-Trader / cTrader | CFDs, Spot Precious Metals, FX | FIX Protocol | 3ms - 8ms | Direct FIX Credentials |
| Tradier | US Equities, Stock Options | REST API | 18ms - 30ms | OAuth Token Exchange |