Introduction to Algo Trading Architecture

Algo trading uses computers to automate trades, but it’s more than just code—it runs on a robust architecture that handles live market data, trade execution, risk management, and compliance. This system ensures trades are fast, accurate, and efficient.  

Another important piece of this puzzle is smart order routing, or smart routing. A key component, which scans multiple exchanges in real-time to get the best price and execution for your trades. Understanding this infrastructure is crucial for anyone entering the world of algorithmic trading. In this chapter, we’ll explore the core tools behind algo trading and how smart routing gives your strategies a competitive edge in the market. 

What Is Algorithmic Trading Architecture? 

Algo trading architecture is the foundational structure used to design and operate automated trading systems. It includes various elements and workflows that enable the automation of trading strategies, covering everything from gathering and analysing market data to executing orders and managing trading risks. 

Key Components of Algorithmic Trading Architecture 

1. Market data feed handlers: Market data feeds are the lifeblood of any algorithmic trading infrastructure. Feed handlers collect real-time pricing data from exchanges and deliver it to internal systems in a structured format. These handlers also filter and normalise incoming data so it can be processed efficiently by other components. 

1. Strategy engine: At the heart of any algo trading architecture is the strategy engine. This component runs trading algorithms that analyse data and trigger buy or sell decisions. Strategies can be as simple as moving average crossovers or as complex as machine-learning models. 

1. Order Management System (OMS): The OMS manages the entire lifecycle of an order—from creation and modification to execution and cancellation. It tracks order status in real-time and ensures accurate reporting, which is critical for compliance and performance analysis. 

1. Execution Management System (EMS): While the OMS focuses on managing orders, the EMS ensures those orders are executed in the most efficient manner. It chooses the best execution venue based on market conditions, liquidity, and fees. 

1. Risk management layer: This component continuously monitors trades to ensure they fall within predefined risk thresholds. If a trading strategy starts showing abnormal behaviour or losses exceed a set limit, the risk system can halt the strategy automatically. 

1. Backtesting and simulation module: Before deploying any strategy live, traders use backtesting tools to simulate performance using historical market data. This helps to identify potential issues and validate the effectiveness of the strategy. 

1. Low-latency infrastructure: In high-frequency environments, milliseconds matter. Traders invest in low-latency infrastructure, including direct market access (DMA), co-location with exchanges, and ultra-fast networking equipment. 

1. Compliance and reporting systems: Given the regulatory scrutiny surrounding automated trading, systems must have built-in compliance checks. Automated reports ensure that all trades meet legal requirements and are transparent to regulators. 

The Role of Quants in Building Algo Trading Strategies 

Quantitative analysts, often called quants, are essential to the success of any algorithmic trading operation. Their responsibilities include: 

1. Data analysis: Quants analyse massive volumes of data, from price trends and market volumes to economic indicators, to find actionable insights. 

1. Model development: They build predictive models using statistical techniques, machine learning, and econometric methods. 

1. Strategy implementation: Once a model is validated, quants code it into a trading algorithm and integrate it into the broader trading infrastructure. 

1. Risk Assessment:  Quants also analyse the potential risks associated with a strategy, including drawdowns, volatility, and tail risks. 

Smart Routing in Algorithmic Trading 

Smart order routing (SOR) is a critical feature of modern algorithmic trading infrastructure. It helps traders execute orders at the best possible price by analysing multiple trading venues in real-time. 

What Is Smart Routing? 

Smart routing refers to an automated process that directs a trade to the most suitable venue based on criteria like price, liquidity, speed, and execution cost. As markets become more fragmented, with multiple exchanges offering the same instruments, SOR ensures traders get optimal execution without manually monitoring each venue. 

Why Smart Routing Matters? 

With trading spread across venues such as NSE, BSE, LSE, and SGX, a single order could be filled in multiple parts across different exchanges. Smart routing technology makes this seamless. It’s especially useful for institutional traders dealing with large orders, where minimising slippage and market impact is crucial. 

Types of Smart Order Routes 

1. Cost-based routes: These routes prioritise venues with the lowest transaction fees. By calculating the total cost of execution, the system chooses the most cost-effective venue. 

1. Time-based routes: When speed is vital, time-based smart order routes prioritise the fastest execution options. This is useful in high-volatility conditions. 

1. Liquidity-based routes: These routes target venues with higher liquidity to ensure that large orders are filled efficiently without significant price impact. 

1. VWAP-based routes: Volume-Weighted Average Price (VWAP) routes aim to execute trades close to the average market price, which is ideal for institutional orders. 

1. Dark pool routes: Dark pools are private exchanges where orders aren’t publicly visible. These routes reduce market impact and are useful when discretion is important. 

Customising Smart Order Routes for Optimal Execution 

• Order slicing: Large orders can be divided into smaller ones to minimise market disruption. These smaller orders are then routed across venues over time. 

• Venue prioritisation: Traders can set preferences for which venues to use first, based on past performance, speed, or fees. 

• Order type selection: Depending on market conditions, traders can choose between market orders, limit orders, or stop orders. 

• Time weighting: This configuration spreads trades across a chosen time frame, reducing the risk of adverse price movement. 

• Risk tolerance settings: Traders can define acceptable levels for bid-ask spreads, execution time, and slippage. The system won’t execute trades outside these limits. 

Managing Intraday Smart Order Routing (SOR) Trades 

When placing intraday orders using SOR, traders must track where each part of the order was executed. For example, if a trade for 500 shares of ABC Corporation executes 300 on the NSE and 200 on the BSE, closing the trade involves selling the same number of shares on each respective exchange. 

Steps to Manage Intraday SOR Positions: 

• Check the order book and trade history to see how shares were split across exchanges 

• Place sell orders on each respective exchange accordingly 

• Ensure the positions are closed before the end of the trading session 

General Restrictions on Smart Routing Systems 

1. Order type limitations: Some brokers only allow market orders through SOR, while others may support limit or stop orders. 

1. Liquidity constraints: Not all stocks may be eligible for smart routing due to low trading volumes or regulatory issues. 

1. Exchange rules: Different exchanges have specific rules that may affect how and where orders can be routed. 

Mean Reversion Strategy Implementation 

Step 1: Collect data: Download historical stock prices for a selected asset. 

Step 2: Calculate mean and standard deviation: Compute rolling averages and standard deviations to identify deviations from the mean. 

Step 3: Define entry and exit rules: Buy when the price is two standard deviations below the mean and sell when it reverts. 

Step 4: Backtest the strategy: Run the strategy on past data using your trading system’s backtesting module. 

Step 5: Deploy with smart routing: Use smart order routing to ensure the strategy’s orders are executed at the best price with minimal impact. 

Conclusion 

Understanding the core components of algorithmic trading architecture and smart routing is essential for any beginner entering the world of algo trading. From handling real-time market data and executing trades efficiently to customising smart order routes for better outcomes, each component plays a critical role. As financial markets continue to evolve, understanding these foundational elements will help algo traders navigate the system better and carry out strategies accurately.