What Role Does Matching Engine Software Play in Your Exchange's Functionality?

Markets digitalisation is a fact many people overlook. Matching engine software is the essence of any trading platform, whether a traditional exchange or a crypto trading venue. 

These engines assist in linking purchasers with sellers and promote trades by comparing their orders to find ideal matches. Match engines’ significance cannot be overrated, and a thorough comprehension of their function is crucial for everyone involved in trading.

The article will outline matching engines' functionality advantages and downsides.

Exchanges and marketplaces provide a venue for market players to swap stocks, digital currencies, commodities, and other investment options. They aim to create an equal and structured trading experience for everyone involved.

Finance exchanges typically place orders through a member broker for execution at the best price.

Marketplaces utilise matching engine software to offer transparent price discovery, timely order execution, fairness, and efficient asset exchange through fair and orderly transactions.

An order matching engine (OME) is a trading software that uses algorithms to analyse trade information and match suitable buy and sell orders from market participants, facilitating trade execution. Advances in exchange matching engine software have transformed trading across multiple asset classes, eliminating the need for face-to-face trading. Intelligent OMEs now fully enable exchange trading.

An OME creates efficient global markets with vast liquidity changes daily. A trade matching engine is the core software and hardware component of any electronic exchange, and all other exchange systems are peripheral to the match engine since no market can exist without it.

Matching software is necessary for trading venues to execute incoming market orders with liquidity from limit orders in the order book.

The trading engine is a complex, sophisticated piece of software that collects and instantly synchronises data from different currencies being traded. 

The performance of the engine determines its efficiency and reliability.

Exchanges use various OMEs, with the centralised engine being the most common. It matches real-time orders from multiple users, mostly using the first-come, first-serve algorithm, though some exchanges may use different methods.

The decentralised match system is a system that matches orders from multiple users in real time without a central server, using a peer-to-peer network. This eliminates a single point of failure and increases security against attacks. Smart contracts are used to accomplish trades within this system.

OMEs vary in their key features, but core features are similar for most of them.

A trade matching mechanism compares buyers' and sellers' orders by considering their willingness to pay and the number of shares or financial instruments they are willing to trade. The engine searches for matches between orders and arranges trades based on these results.

An order-matching engine architecture uses various criteria to match orders, including price and time, order type, and trading venue.

The trade is completed once two orders match, and all parties involved are notified.

Let’s take a look at the simplified example of an OME work: suppose you want to purchase 1 BTC at 10,000 USD and place a purchasing order on the exchange. Then, another trader wants to sell 1 BTC at the same price and places a sell order on the exchange.  The engine, with the help of specialised algorithms, matches these two orders and executes the trade. As a result of the matched orders, you get 1 BTC, and the BTC’s seller gets their money.

The match engine employs algorithms to fulfil orders based on parameters like price, volume, and time of order entry.

The algorithms OMEs use to analyse trade data collect information about all open orders, and if two opposite orders are equal, they are executed, and the transaction is completed. These methods also allow you to place market, limit and stop limit orders.

The OME employs various algorithms; the FIFO and Pro-Rata are the most common. 

The First-In-First-Out (FIFO) algorithm, also known as the Price-Time algorithm, gives priority to buy orders based on price and time. The method ensures that the earliest active purchase order at the highest price is prioritised over any subsequent order at that price, which in turn takes priority over any active buy order at a lower price.

Let’s look at the example: a purchase order for 100 shares of stock at $200 per share entered an order book, and an order for 50 shares of the same stock at the same price joined the order book later. Following the FIFO algorithm, the system will match the 100-share order to a sell order prior to matching any portion of the 50-share order.

The Pro-Rata algorithm prioritises the highest-priced buy order but matches buy orders with the same price proportionally to each order size. This method ignores the time the orders were placed and prioritises a price for active orders proportionally to their size.

Let’s look at the example: two buy orders, a 200-share one and a 50-share one, entered an order book at the same price and are active. Then, a 200-share sell order arrives and is compatible with both buy orders. According to the Pro-Rata algorithm, the system must match 160 shares to the 200-share buy order and 40 shares to the 50-share purchase order.

The following factors can influence the performance of an exchange match engine:

OMEs are crucial for efficient and accurate order matching, enabling buyers and sellers to trade without intermediaries and ensuring all trades are accomplished at the best possible price. Without them, human manual matching would be time-consuming and subject to human error.

The order matching system is paramount in every exchange for its efficient execution of trades and ensuring that all transactions are fulfilled at the best price.

Moreover, an OME is crucial for providing liquidity, enabling traders to buy or sell assets without constantly looking for a buyer or seller. It ensures there is always someone to buy or sell an asset, even at unfavourable prices, making trading easier and promoting market stability.

Any market is a dynamic yet unpredictable landscape. A reliable order-matching algorithm can solve many issues arising in exchanges due to its numerous benefits. However, there are also some challenges that trading platforms might encounter when using OMEs. Let’s discuss some of the advantages and drawbacks of using match engines.

OMEs are crucial in electronic trading systems, enabling market participants to trade without human assistance and offering numerous advantages.

Providing market liquidity - OMEs can enhance liquidity in a finance market by simplifying transactions between buyers and sellers, resulting in more trade closures.

Accessibility - Matching algorithms allow market players to connect from any location, which enhances finance market accessibility and potentially leads to a more open and effective market.

Increased trade efficiency - A match engine enhances capital market efficiency by automating the pairing of purchase and sell orders, reducing transaction time and manual order matching costs, thus enhancing the market's overall efficiency.

Reduced risks - Automating order matching can reduce human error, inaccuracies, and incorrect prices that may result in funds loss.

Transparency of trading - A match system improves transparency in the financial market by providing equal access to buy and sell order data, leading to more accurate price determination.

Cost-efficiency - Matching systems can reduce trading costs by eliminating the need for mediation from brokers or exchanges.

Despite the numerous benefits, OMEs also have some drawbacks.

Latency - This issue can occur in swiftly changing markets. The engine is constantly managing many orders, especially during peak market activity. Possible failure to do so, or delays or cancellations of trade execution, can result in incorrect border matching and funds loss.

Price discovery - The exchange typically sets prices independently, but utilising an OME by some market participants makes asset price determination more challenging.

Regulations - This is especially challenging for a cryptocurrency market since, in many areas, digital currency is still uncontrolled. As a result, there is no formal organisation overseeing the match algorithms and no assurance that they will work fairly and transparently.

The primary component of the trading software is the OME, which is essential for its operation. It is crucial to make a careful decision when it comes to picking the right pairing engine, requiring careful deliberation on numerous aspects.

Asset class - Understanding the asset classes your trading venue will offer is crucial, as not all OMEs are compatible with every class. However, multi-asset engines are independent of underlying assets, making them suitable for most markets.

Latency - This factor is crucial for businesses, especially those deploying high-frequency trading strategies. 

Order management - A trading match engine aids in order management by providing various tools, processes, and algorithms for efficient order management.

API integration - Pick a match engine that aids in API integration, platform integration, price and quote contributions, and algorithm coding.

Security - Select a secure match engine with a built-in remote password protocol to protect your software from attacks.

Memory - Memory aids in order recovery in case of a crash, so ensure your match engine software has memory and an inbuilt recovery mechanism.

Integration - Match engine platforms or software should be able to be seamlessly integrated with other technology types, ensuring the smooth and efficient functionality of your trading platform.

Real-Time Data - The match engines have a built-in data server, enabling you to power desktops and apps. This allows you to stream data to users on trading software and desktop platforms, enabling them to access data directly from the web and through the application.

Trade matching engines have significantly transformed finance markets by offering increased efficiency and fairness to sellers and purchasers. Despite some disadvantages, matching engine software is an essential component of financial markets, offering numerous benefits and likely to continue playing a significant role in the capital markets.