Co-location Servers in Algo Trading: Benefits and Uses Explained

Every second counts when it comes to the cutting-edge world of algo trading (or even trading in general). Traders can earn significant profits in a matter of seconds by executing high-speed transactions. In this journey, many 'big players' use co-location servers to execute trades faster and gain an edge over competitors. In this article, we’ll explore the role of co-location servers and their importance in algo trading!

Why is ‘Speed’ a Significant Factor in Algo Trading?

Algo trading relies on the ability to analyse market data quickly. The market is constantly changing, with prices fluctuating rapidly. Algorithms can scan large amounts of data to find the perfect moment to make trades. In such fast-moving markets, getting data too late can mean missing out on opportunities or taking extra risks. The quicker an algorithm receives real-time data, the more accurately it can execute profitable trades! 

Fast algorithms can place and execute orders more efficiently, reducing the risk of slippage (the difference between the intended price and the actual price at which the trade is executed). Moreover, when markets are volatile, algorithms can quickly react to changing conditions and adjust positions to minimise risk. Speed is crucial for implementing risk management strategies effectively. That’s why fast, reliable data is essential for success in algo trading!

What is a Co-Location Server?

Imagine the stock market as a massive building with walls that block signals. Far away traders, experience delays as the signals take time to reach them. Co-location servers function like powerful Wi-Fi routers, ensuring ultra-fast, lag-free connections for traders by bringing them closer to the data source. Co-location servers allow traders to place their machines close to the infrastructures of an exchange, enabling orders to be executed at faster rates. This gives them an advantage over those who are further away, thereby communicating changes in the market within a short time.

Before 2009, brokers and proprietary traders used certain machines linked with exchange servers. However, orders wouldn't be placed during peak trading volumes or for certain connectivity problems. On various occasions, these delays meant huge losses in high-frequency trading (HFT), as every millisecond is crucial. As a result, firms lost out because of the slow pace of placing orders.

[Proprietary traders are firms or individuals that trade financial instruments using their capital, rather than on behalf of clients.]

To combat this problem, the National Stock Exchange (NSE) offered co-location services in 2009. Under this service, brokers can place their servers within the exchange premises. The service helped traders to get real-time tick-by-tick price data. This gave an advantage in the HFT game, where algorithms would execute trades under a second. Co-location allowed traders to respond instantaneously with minimal latency to stay ahead of the competition.

The Bombay Stock Exchange (BSE) started co-location services in 2011. Brokers place their servers inside the BSE data centre through co-location. For traders, this reduced latency, increasing the order execution speed. Being close to the exchange helped them obtain quicker access to real-time data!

Why Are Co-Location Servers Important in Algo Trading?

Now that you understand what co-location servers are, let's look at some important aspects of it:

1. Low Latency:
These servers eliminate the need for data to travel across the globe, your trading system is positioned next to the exchange to collect data efficiently. Traders and firms get their orders executed faster giving them an edge over those who are waiting over long data travel times.

2. Better Data Access:
Co-location servers placed closer to an exchange have better access to real-time market feeds. This ensures that your algorithms get better access to data to identify market changes and take action, without much lag.

3. Enhanced Strategy Performance:
The performance of your strategy depends on latency and data access. With co-location servers, your strategies are the first to act and ensure your trades hit the market at the right moment.

Can Retail Traders Get Access to Co-Location Servers?

Retail traders typically cannot get direct access to co-location servers. These servers are primarily designed for high-frequency traders (HFTs) and institutional investors who require extremely low latency for their trading activities. The cost of renting server space is very high, some costing ₹15 lakhs a month, making it unaffordable for most retail traders.

However, retail traders can use broker/trading platforms like Zerodha and Upstox, and authorised data vendors like TrueData, Global Datafeeds, and Accelpix to source near real-time data access for algo trading. While these platforms may still need to fully utilise the speed advantages of co-location, they allow retail traders to compete in the stock market.

What are the Costs and Risks of Co-Location Servers?

1. Significant Expenses: Renting space in an Indian co-location centre will cost around ₹5 lakhs to ₹15 lakhs per month. This price includes power, cooling, and high-speed connectivity charges. These costs for co-location will be a huge financial commitment for small traders or firms with a minimal budget.

2. Tech Maintenance: Maintaining co-located servers requires a technically skilled team. You need experts to keep everything running smoothly. Any downtime or technical issues can lead to significant losses, so having a reliable support team is crucial.

3. Security Concerns: Storing your trading algorithms in a third-party data centre brings about security risks. Breaches or unauthorised access can expose your strategies, leading to financial and reputational damage. Keeping your systems secure is a top priority.

4. Regulatory Analysis: Co-location servers work under tight scrutiny due to fairness-related concerns. Traders must comply with several tight regulatory rules to continue co-location service usage. Regular reviews are made by authorities concerning data access, system performance, and trading behaviour for transparency. In cases of non-compliance, heavy fines, restrictions, or a ban from trading are imposed. 

Conclusion

Co-location servers help reduce latency and improve access to real-time data, providing an edge in trading. This technology is mostly utilised by high-frequency traders and large institutions to execute trades efficiently. While it enhances speed and data access, it comes at a very high cost and risk.

For retail traders, the costs and complexities of co-location servers make them less accessible. While you may not be able to fully leverage this technology, you can still succeed by focusing on strong trading strategies, risk management, and alternative tools to stay competitive!