Derivatives play a fundamental role in financial markets, enabling firms to hedge risk exposure and access additional assets and types of market. Due to their diffusion and the complexity and variety of instrument types, derivatives trading requires large amounts of data and poses specific challenges when it comes to data management.
What is a derivative?
A derivative is a financial instrument that derives its value from an underlying asset. Derivatives are used to hedge risk, speculate on the spreads between assets, or for arbitrage.
There are many types of derivatives, including (but not limited to) futures, options, and swaps:
- Futures are contracts that obligate the buyer to purchase an asset at a predetermined price on a specific future date. They are often used to hedge against price fluctuations in commodities, currencies, and other assets.
- Options are contracts that give the holder the right, but not the obligation, to buy or sell an asset at a predetermined price on or before a specific date. There are two types of options: call options, which give the holder the right to buy the underlying asset, and put options, which give the holder the right to sell the underlying asset.
- Swaps are contracts in which two parties agree to exchange the cash flows of two different assets. For example, a company may enter into a currency swap to exchange the cash flows of a loan denominated in one currency for the cash flows of a loan denominated in another currency. Swaps are often used to manage interest rate or currency risk.
Derivatives can be complex financial instruments, and they carry a high level of risk. Before entering into a derivative contract, it is important to understand the terms of the contract and the potential risks and rewards. Their complexity and the potential risks associated with the derivatives market highlight the importance of effectively managing the data that supports the valuation of these assets.
What changes were made to derivatives regulations after the 2008 financial crisis?
The 2008 financial crisis was triggered in part by the failure of several large financial institutions that were heavily invested in complex derivatives. In response to the crisis, a number of regulatory reforms were implemented to improve the transparency, stability, and oversight of the derivatives markets.
One key reform was the implementation of central clearing for certain types of derivatives. Central clearing involves the use of a third-party clearinghouse to stand between buyers and sellers in a derivative trade, effectively acting as a guarantee of performance for both parties. This helps to reduce counterparty risk, as the clearinghouse acts as a buffer between the two parties in the event that one of them defaults.
Another reform was the implementation of margin requirements for non-centrally cleared derivatives. Margin requirements involve the setting of minimum levels of collateral that must be held by both parties in a derivative trade, to reduce the risk of default.
Other reforms included the establishment of trade reporting requirements, the creation of new regulatory agencies with authority over the derivatives markets, and increased capital and liquidity requirements for financial institutions.
Overall, these reforms were designed to improve the stability and transparency of the derivatives markets, and to reduce the risk of systemic failure in the financial system. The increased level of regulatory oversight meant that more focus was placed on the integrity and performance of the data management processes that underpin the market for these assets.
Why is data management important for derivative trading and valuation?
Data management is important for derivatives trading for several reasons.
First, derivatives are complex financial instruments, and they require accurate and up-to-date data to be properly valued and traded. This includes data on the underlying assets, market conditions, and the terms of the derivative contract itself. As a derivative can have a variety of underlying assets – e.g. stocks, bonds, commodities, currencies, interest rates, and market indexes, etc. – the data management system needs to be able to ingest and process all the data types associated with these. Not only this but the system needs to be capable of maintaining the link between the derivative instrument itself and the underlying asset or data point to ensure that any changes or corrections in these is reflected in the valuation.
Second, derivatives traders rely on data analysis and modelling to make informed trading decisions. Effective data management is critical for ensuring the accuracy and reliability of these analyses, both in terms of the quality of the data supporting the instrument, and understanding, storing and validating the calculated instrument itself. Calculations, and the calculated data, often require systems external to the main data repository.
Third, derivatives markets are often highly regulated, and firms are required to maintain accurate records of their trades and positions. This requires effective data management systems to ensure compliance with regulatory requirements. Data lineage that connects the calculated data with the raw underlying data, and records all the adjustments and decisions made when valuing the instrument is fundamental for reporting transparency and compliance.
Finally, derivatives traders often work with large volumes of data, and effective data management is necessary to ensure the efficiency and speed of trading operations. This data may be of different types and from a multiplicity of sources, and the data management system has to be able to aggregate, normalise and interrogate this data.
Summarising, we can see that any data management architecture supporting derivatives trading operations needs to be able to handle the following aspects:
- Complex data
- Data lineage and audit
- Data aggregation, volume, and speed
Overall, data management is a critical component of derivatives trading, and effective data management systems are essential for the success of any derivatives trading operation. Increased regulatory focus on the derivatives market post-2008 has placed greater demands on the data management aspect of derivatives trading, a trend that has continued over time, and presents ongoing challenges to many legacy systems and processes for managing this data.
Learn more: Xenomorph’s EDM platform was built to handle the complex data and calculations needed when pricing derivatives. If you are facing challenges managing data for your derivatives trading operations you can read more about our solutions here, or get in touch to speak to one of our experts.