Curves and their associated data points are an integral part of the pricing process. These curves – interest rate, forward, volatility, swap, etc. – are often used as standalone prices but also act as a required input to price complex securities and as a source of useful information for multiple systems like risk, performance and front-office applications. Creating and maintaining these curves, however, becomes a very difficult and manually intensive task for funds due to the extra bandwidth required from both technical and pricing teams. Fortunately, analysis suggests there are many areas throughout the process that can be streamlined and automated, such as:
- Defining a curve: Dealing with curves makes it important to have a clear workflow around their mapping, maintenance and sourcing. A curve definition is generally comprised of the constituents that form the curve, which are sometimes common across many. This calls for an intuitive visualization of how various curves are formed along with their audit.
- Defining curve data points and their mapping: Each curve point comes with a unique identity. This mapping, if maintained in an Excel file or database, requires extra bandwidth to make any necessary changes and perform audit checks, creating a difficult process to manage for the pricing team. Through a smart UI-based interface, this process can be simplified by allowing the pricing team to efficiently manage data and easily create, update and map curve points with different curves.
- Pricing curve data points: Market data vendors, including Bloomberg, provide prices on a daily basis via FTP and API. At times, pricing teams may decide to override some of the curve data points but dealing with such a multitude of sources and overrides becomes a manually intensive exercise that requires an additional amount of dedicated effort. Automating pricing consumption allows the team to focus primarily on pricing overrides and exceptions rather than reaching out to different sources for curve prices.
- Time series & exception management: Funds and pricing teams typically struggle with visualizing these data points on a time series – both for a curve and its underlying curve data points. However, this can be automated with a tool designed to store the data and provide a clear visualization of time series along with the capability to manage exceptions and take corrective actions.
- Input variables & sensitivity analysis: While there are many specialized sources to price complex securities, funds also run internal valuation models that require the input of pricing curves. If an integrated system is available, pricing teams can also run scenario analysis by adjusting the curve data points to various test scenarios.
- Cross-platform integration: Oftentimes, the final prices of curve data points need to be shared with other systems to serve various purposes like valuations, sensitivity analysis, risk analysis, etc., making it crucial to establish seamless and real-time connectivity with the pricing system (both upstream and downstream). This can be achieved through an automated pricing application that connects with other in-house and vendor systems.
Due to these array of factors, an increasing number of funds are looking for ways to streamline the management of curves and their data points with better data and more efficient tools.
Discover how IVP Price Master, IVP’s industry-leading pricing and valuation solution, can assist managers in automating their process and mastering curve data points by visiting IVP PRICE MASTER or contacting firstname.lastname@example.org.