Trading-Engine

KO | EN

gitlite — search

#python #ai #typescript #android #rust #deep-learning #macos #nodejs #cli #vue #pytorch #security #ios #openai

(★ 15)

A fast, and efficient trade matching engine built in C++ utilizing Chrono, BOOST, and STL libraries

Trading-Engine 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# Multithreaded Limit Orderbook and Trading Engine

A fast, multithreaded and efficient trade matching engine built in C++ utilizing Chrono, BOOST, and STL libraries. A demo can be found [here.](https://www.youtube.com/watch?v=-k_1Zz8bcX8&ab_channel=HamzaRashid)

- **FIFO** (First in first out) approach is used to store orders'.

- **Price Priority** algorithm is used for matching orders - where oldest buy order at the highest buying price is matched with the oldest sell order at the lowest selling price.

## Performance

Two simulations were conducted using the same seed, involving the random generation of 100,000 "ETH" and "BTC" orders.

- **Single-threaded trading simulation**: The processing of 100,000 orders was accomplished within 6.51089 seconds, resulting in an average of 15,000 executions per second.
- **Multi-threaded trading simulation**: The processing of 100,000 orders was accomplished within 4.23649 seconds, resulting in an average of 23,000 executions per second.

## Architecture

Code is developed using efficient data structures (Binary Trees, Unordered Set and Unordered Map) keeping in mind High Frequency Trading (**HFT**) objectives.

Time complexity for key order operations are as follows:

- Add: O(log M) for the first order at a limit price, O(1) for all others
    - Cancel: O(1)
    - Execute: O(1)

Where M is the number of price limits and N is the number of orders (generally M << N).

## Input Data Format

Order scripts expect the following input format (.csv or .txt file)

- Buy, Sell or Cancel: BUY or SELL or CANCEL
    - Order ID: Unique or autoincrementing Integer (0,1,2...)
    - Price: Positive float (1.00, 2.5...) 
    - Quantity: Positive float (100.00, 200.00...)

Sample orders are as follows:

- SELL,1,31502,7500
    - BUY,2,31601,20000
    - CANCEL,1,31502,7500

## Next Steps

- Integrate the proof of concept with an API that provides real-time order book data, transitioning from the current CSV-based approach to a dynamic and automated data source.
- Explore other data structure variations by utilizing a sparse array to store the Limits instead of a tree. This leads to distinctive time complexity trade-offs that impact performance considerations.
- Establish a synchronization mechanism for the output_data variable across multiple threads using primitives such as conditional variables, locks, mutexes, or atomic operations to ensure consistent and orderly access.

## References

1. [Limit Order Book](https://web.archive.org/web/20110410160306/http://howtohft.wordpress.com:80/2011/02/15/how-to-build-a-fast-limit-order-book)
2. [How to Build a Fast Limit Order Book](https://web.archive.org/web/20110410160306/http://howtohft.wordpress.com:80/2011/02/15/how-to-build-a-fast-limit-order-book)

Trading-Engine

Trading-Engine 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

Trading-Engine

Trading-Engine 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

Download README