Algorithmic Trading System Architecture refers to the technical infrastructure and components that enable the execution of algorithmic trading strategies using software development kits (SDK). SDKs provide pre-built modules and tools that facilitate the development and deployment of trading algorithms.

At its core, an algorithmic trading system is designed to automate the buying and selling of financial instruments, such as stocks, bonds, or derivatives, based on predefined rules and algorithms. These algorithms utilize mathematical models, statistical analysis, and historical data to make trading decisions.

The architecture of an algorithmic trading system typically consists of the following components:

1. Market Data Providers: These sources collect real-time market data, including prices, volume, and other relevant information, from various financial exchanges or data vendors. This data is crucial for generating trading signals and making informed decisions.
2. Data Storage and Management: Once the market data is received, it needs to be stored and managed efficiently. This component includes databases and storage systems that handle large volumes of data and allow for quick retrieval and analysis.
3. Trading Algorithms: These are the core components of the system that perform calculations and analysis based on the available market data. These algorithms are responsible for generating trading signals and determining when to buy or sell specific assets.
4. Order Management System (OMS): The OMS is responsible for managing the entire order flow, including order routing, execution, and monitoring. It connects to multiple exchanges or brokers to send trade orders and receive trade confirmations.
5. Risk Management: A crucial part of algorithmic trading is managing various risks associated with the strategy, market conditions, and execution. Risk management tools and algorithms help ensure that the trading system operates within predefined risk parameters.
6. Execution Platforms: These platforms provide connectivity with financial exchanges or brokers for executing trades. SDKs play a significant role in integrating the trading algorithms with these execution platforms.
7. Performance Monitoring and Reporting: The system should have mechanisms to track the performance of trading strategies, monitor real-time market conditions, and generate comprehensive reports for analysis and compliance purposes.

Overall, Algorithmic Trading System Architecture based on SDK trading includes these essential components to automate and streamline the trading process, leveraging data analysis, mathematical models, and algorithms to make informed trading decisions.