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Hedge funds need to up their game when it comes to risk management. While they tend to have modern portfolio management systems, many keep outdated risk management systems that don't provide real-time pre- and post-trade market risk analytics.
Hedge funds typically start small, with most launches falling between $10 million and $100 million. In these early stages, the priority is often to get the portfolio management system up and running in real-time, while risk monitoring tools may be given less attention. This can lead to compromises that result in data and technological debts down the line. Typically, a single tech person with limited domain and architecture knowledge will oversee the entire tech stack from day one, which can further exacerbate these issues. As a result, the foundation of the tech stack may not be as robust as it needs to be, particularly when it comes to market risk management.
Market risk is a critical aspect of hedge fund management. It is often where the first cracks in the tech stack foundation begin to form. Many hedge funds rely on Value at Risk (VaR) as their primary risk measure and increasingly as a capital allocation tool. VaR and more advanced derived measures such as Expected Shortfall or half-life VaR are statistical techniques used to quantify the level of financial risk at various levels of the organisation over a specific time frame.
The lack of prioritization for risk management systems at inception can lead to significant issues further down the line. As a hedge fund scales, so does its complexity and risk profile. Without a solid risk management foundation, it becomes increasingly challenging to manage and monitor risk effectively.
One of the major challenges in hedge fund risk management is the lack of real-time risk measurement. Official Risk calculations are often calculated in batches and not available until well into the next day, with limited granularity. This can lead to delays in responding to market events. Furthermore, to save on storage and compute running costs, the historical PnL vectors required for metrics calculation often cover only a short period of time, sometimes as little as a year of daily historical PnL. In today's financial markets, where conditions can change rapidly, this lack of real-time risk measurement can be a significant disadvantage. Real-time risk measurement allows for quicker decision-making, such as pre-trade what-if analysis, and can even help mitigate losses during market events.
In addition to real-time risk measurement, the ability to store and analyze large amounts of data is crucial for effective risk management. This includes being able to store long PnL histories that capture one or several full market cycles, as well as unlimited amounts of position history and their associated historical PnL vectors. This allows for the calculation of VaR evolution over any historical timeframe, as well as provides a critical amount of data for back-testing and building new trading models. As hedge funds scale, their complexity and risk profiles increase, making it essential to have a robust and scalable IT infrastructure that can provide real-time, pre- and post-trade market risk analytics.
Hedge funds need to prioritize risk management systems early on to avoid technological and data debts in the future. As funds scale, their complexity and risk profiles increase, making it crucial to have a solid risk management foundation. Without this foundation, it becomes increasingly challenging to manage and monitor risk effectively. Hedge funds should prioritize building a robust and scalable IT infrastructure that can provide real-time, pre- and post-trade market risk analytics. They should also prioritize the ability to store and analyze large amounts of data, including long PnL histories and unlimited amounts of position history and associated historical PnL vectors.
At Opensee, we help hedge funds overcome these challenges regardless of their maturity. Thanks to our cost-effective, easy-to-implement solution and our hedge fund domain experts, our risk management solution easily scales into other use cases such as managing market data historically. Whether you’re just launching or are an established fund, we’d love to partner with you.
About the author:
Edouard Precheur heads the Traded Risk coverage in the Markets department at Opensee. He has 20 years of experience in the industry, mostly in banking where he held a variety of roles, ranging from Market Risk to Head of IPV for Trading LOBs and Business Managers of the AI and Ml department.
