Setting-Up An Algo Trading Desk

Setting up an algo trading desk involves creating an infrastructure to execute automated trading strategies using algorithms. This process is intricate and requires a blend of technology, finance, and compliance.

Algorithmic trading involves automating trades using algorithms. Key aspects for setting up the algo trading desk, briefly, are operational considerations such as capital requirements, market access, infrastructure, backtesting facilities, risk management tools, a team of professionals etc.

For those interested in automated trading for beginners, it's crucial to understand these fundamentals before diving in. Starting with simpler strategies and gaining experience with backtesting and risk management can lay a strong foundation for more advanced automated trading endeavors.

No doubt setting up an algo trading desk is multifaceted but this blog will give you a detailed insight into the requirements for setting up an algorithmic trading desk. There are mainly three broad requirements in the setting up of algo trading desk, that is, operational considerations, tools to manage risks in trading and a team to manage the trading desk. You will see the details of each requirement in different sections in the index of the blog.

This blog covers:

Overview of algorithmic trading
Operational considerations while setting up an algo trading desk
Additional tools
- Risk management software
- Order management systems (OMS)
Team structure and roles in an algo trading desk
Frequently asked questions regarding setting up algo trading desk

Overview of algorithmic trading

Algorithmic trading, or algo trading, involves using computer algorithms with a language such as Python, to automate trading processes. These algorithms analyse market data and execute trades at high speeds, aiming to optimise efficiency and get good returns. Algo trading is prevalent in financial markets due to its precision, speed, and ability to process vast amounts of data.

If you’re wondering whether algorithmic trading is complicated, the video below provides an answer:

If you wish to get briefed about Algo Trading in short, be sure to check out this helpful video:

Let us now check out the operational considerations while setting up the algo trading desk.

Operational Considerations while setting up an algo trading desk

This includes ensuring robust infrastructure, such as high-speed servers, reliable data feeds, and implementing stringent risk management protocols. Additionally, compliance with regulatory standards, regular system maintenance, and continuous monitoring of trading activities are crucial to ensure smooth and secure operations.

Let us now see all the operational considerations from the start while setting up the algo trading desk.

Registering company

Establishing a legal entity involves registering the company with appropriate authorities, and ensuring compliance with local and international regulations. This process includes acquiring necessary licences and permits for trading activities, setting up a corporate structure, and establishing a registered office, all of which are essential for legitimacy and operational readiness.

Capital requirements

Determining capital requirements is crucial for setting up an algo trading desk. This includes funds for initial setup costs, such as technology infrastructure, software, data as well as capital to cover operational expenses and potential trading losses. Adequate capital ensures the desk can operate smoothly and withstand losses due to market fluctuations.

The informative video below, by Nitesh Khandelwal (Co-founder and CEO, of QuantInsti), offers some insights into the capital requirements while setting up an algo trading desk:

Trading paradigm

Define the trading paradigm by identifying the specific strategies and approaches to be used. This involves selecting between high-frequency trading, market-making, arbitrage, or trend-following strategies, etc. The chosen paradigm should align with market objectives, risk tolerance, and available resources to guide the development and execution of trading algorithms effectively.

Access to market

Obtain direct market access by partnering with/going through the brokers or gaining membership to relevant exchanges. This facilitates the seamless execution of trading algorithms. Ensuring low-latency connections is critical for maintaining a competitive edge and achieving optimal trade execution.

Infrastructure requirements

To set up the necessary infrastructure, you will need to invest in high-speed servers, reliable data feeds, and secure networks. This setup ensures quick and accurate data processing and trade execution. Implementing strong backup systems and cybersecurity measures is vital to safeguard sensitive information and to ensure continuous operation.

Algorithmic trading platform

Choosing an advanced algorithmic trading platform is essential for developing, testing, and executing trading strategies. The platform should support a programming language that you are familiar with (such as Python, C++, etc), offer robust backtesting capabilities, and provide real-time data as well as tools for stock market data analysis. A reliable platform is crucial for achieving efficient and accurate trade execution.

Backtesting

Backtesting involves testing trading algorithms on historical data to assess their performance and refine strategies, helping identify weaknesses and optimise algorithms before live deployment. Backtesting platforms are crucial for simulating trades and evaluating strategy viability, ensuring that algorithms are robust and reliable under various market conditions.

One such platform is Blueshift which is a free platform for investment research, backtesting and algorithmic trading. Blueshift comes with the recently launched alpha version - a fast event-driven backtesting platform with minute-level data covering multiple asset classes and markets. Given that it enables the users to perform event-driven backtesting, instead of vectorised backtesting (which can be faster but not precise and misses many details), the backtesting results would be a potentially better estimate of how the strategy would have performed in the real market.

If you are wondering how much it can cost to set up an algo trading desk, Nitesh Khandelwal (Co-founder and CEO, of QuantInsti) has shared his knowledge regarding the same in this video:

The next requirement while setting up an algo trading desk is the software and tools. Let us check them out.

Additional Tools

Here are a few additional tools available which come in use for an algo trading desk:

Risk management software: Risk management software plays a pivotal role in monitoring and managing financial risks in real time. It provides the necessary tools to implement risk controls and set limits to protect against excessive losses. This software ensures that all trading activities comply with regulatory requirements and adhere to internal risk policies, thereby safeguarding the trading desk from potential financial and legal repercussions.
Order management systems (OMS): Order management systems (OMS) are essential for handling the entire lifecycle of trade orders, from inception to execution and settlement. OMS platforms streamline the order flow process, ensuring accurate and timely execution of trades.

Also, this informative video covers some important pointers regarding the relevance of a comprehensive course, that is, EPAT while setting up an algo trading desk.

Team structure and roles in an algo trading desk

A well-structured algo trading desk requires a diverse team, including quantitative analysts & traders, software developers, risk managers, IT infrastructure specialists, and compliance officers. Each role is crucial for developing, executing, and managing trading strategies while ensuring operational efficiency, regulatory compliance, and risk mitigation.

Here is a brief description of some of these roles:

Quantitative analysts and traders: Quantitative analysts and traders create and refine trading algorithms using mathematical models and statistical analysis. They design strategies, generate code, and perform backtesting to ensure robust performance. Their expertise in programming and data analysis is essential for developing profitable and efficient trading systems.
Risk analysts and managers: Risk analysts and managers monitor and manage the financial risks associated with trading activities. They assess potential losses, implement risk controls, and ensure compliance with regulatory requirements. Their role is vital in protecting the trading desk from significant financial losses and maintaining overall stability.
IT support and infrastructure specialists: IT support and infrastructure specialists maintain the technical backbone of the algo trading desk. They ensure the reliability and performance of servers, networks, and trading platforms. Their responsibilities include troubleshooting issues, implementing security measures, and ensuring seamless operation of all technological components essential for trading.

As we have reached the end of the blog, it is a must to mention that regular maintenance and updates are vital to ensure the trading system remains efficient, secure, and up-to-date.

This includes software patches, hardware upgrades, and performance optimisations. Continuously monitoring and fine-tuning the system helps in preventing issues and adapting to market changes, maintaining optimal performance.

Now, we will be moving to some frequently asked questions which commonly occur in the minds of traders while setting up the algo trading desk.

Suggested reads:

Frequently asked questions regarding setting up algo trading desk

Here are some of the most commonly asked questions which we came across during our Ask Me Anything session on Algorithmic Trading.

Q: What are the hardware requirements for Algorithmic Trading?
A: It depends on what kind of trading you are talking about. If it is Low-Frequency Trading then you don’t need much, what you need is a decent laptop/desktop on which you can open a browser and code a strategy and run it or install a broker platform and code your strategy and run it.

If we are talking about High-Frequency Trading along with quantitative analysis in which you are also doing a good amount of data analysis and data chunking. In that case, there are two options available for you:

either you go for a decent machine on your side that will not cost you a lot maybe around 1000-2000 USD (depending on which geography you are in) and
the other option is you can do a lot of analysis on the cloud, the cost of cloud services is going down very rapidly especially where Amazon and Google are offering competitive pricing.

This makes it much easier for an individual and retail trader to get access to the financial computing power which was not there probably a few years back, something that they can access without spending a huge amount of money on that kind of hardware.

If you are talking about medium frequency trading strategy, in that case, you would need to use some algorithmic trading platform which means you would need decent servers which will be around a few thousand dollars.

Q: What is the investment required to start the algo trading business? What will be the incremental investment for HFT?
A: For algo trading business if it is low or medium frequency not much. So you can use the Google platform or vendor platforms which are not that expensive. It can range from about a few thousand dollars a year to a few thousand dollars a month depending upon what vendors or platforms you are going for.

For HFT it will be a few hundred thousand dollars which you will be spending on acquiring the required infrastructure and platform. That is why the cost will be higher. I do not generally recommend people to start algo trading if they do not have established the business in place. So if you have not done automation, starting an HFT might not be a great idea because automation itself comes with several loops with it.

Q: How do I ensure the reliability of my trading infrastructure?
A: Invest in robust hardware and software, implement regular maintenance schedules, and have backup systems in place. Ensuring network security and uptime is crucial for uninterrupted trading operations.

Q: What capital is required to start an algo trading desk?
A: Capital requirements vary based on your trading strategy and market focus. Consider costs for technology, data feeds, compliance, and initial trading capital. Ensure you have sufficient funds to support operational and trading activities.

Q: How can I improve the performance of my trading algorithms?
A: Continuously analyse and optimise algorithms based on performance metrics. Utilise advanced backtesting, incorporate machine learning techniques, and adjust strategies based on market conditions and feedback.

Q: How do I manage risk in an algorithmic trading setup?
A: Implement risk management software to monitor real-time risks and set limits. Regularly review risk controls, perform stress testing, and ensure compliance with regulatory requirements to mitigate potential losses.

Q: What regulatory considerations should I be aware of?
A: Compliance with financial regulations is essential. Understand local and international trading laws, ensure your algorithms meet regulatory standards, and maintain accurate records for audits and reporting.

Conclusion

Setting up an algo trading desk is a complex yet rewarding endeavour that blends technology, finance, and regulatory adherence. A trading desk set up involves establishing a robust infrastructure, choosing the right trading platforms, and ensuring effective risk management. From selecting and backtesting algorithms to maintaining operational efficiency and compliance, every step is crucial for achieving seamless automated trading.

If you are looking for a comprehensive algorithmic trading course that can help you with the necessary knowledge and career assistance, you can enroll in Executive Program in Algorithmic Trading (EPAT). The course covers training modules like Statistics & Econometrics, Financial Computing & Technology, and Algorithmic & Quantitative Trading.

Author: Chainika Thakar (Originally written by Apoorva Singh)

Note: The original post has been revamped on 22^nd August 2024 for recentness, and accuracy.

Disclaimer: All data and information provided in this article are for informational purposes only. QuantInsti^® makes no representations as to accuracy, completeness, currentness, suitability, or validity of any information in this article and will not be liable for any errors, omissions, or delays in this information or any losses, injuries, or damages arising from its display or use. All information is provided on an as-is basis..

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