Portfolio managers and traders that use over the counter (OTC) derivatives often lack an accurate real-time view of the valuations and risk of their derivative positions, especially when trading exotic derivatives. Unlike liquid securities or exchange traded products, there is not always a market price available for OTC derivatives. These products therefore need to be valued according to models that accurately calculate their theoretical fair value. Obtaining real-time risk metrics for a portfolio of derivatives has been challenging, as the commonly used valuation techniques for these products are computationally expensive and require significant machine time. Portfolio valuations and risk calculations typically require overnight runs in a data center or the cloud.
This whitepaper reports the successful use of Artificial Neural Network models (ANNs) by Quantifi to model and deliver real-time pricing with an accuracy considered equivalent to conventional approaches such as numerical integration and Monte Carlo methods, which will be referred to as the conventional model in this whitepaper.
Comparative testing shows that both the conventional and Quantifi ANN models exhibit a less than 0.01% deviation when compared to the theoretical fair value for the derivative. A deviation of less than 0.01% lies well within the bid-offer spread for credit options, which is the economically relevant comparison for a credit option trader. The ANN model is also orders-of-magnitude faster and can deliver real-time valuations. These accuracy and order-of-magnitude performance improvements are consistent with those observed when replacing Monte Carlo methods with ANNs in scientific fields such as High Energy Physics (HEP).
The Intel benchmarks show that the recently launched 3rd Generation Intel Xeon Scalable processors run the Quantifi ANN model 1.56x faster than previous 2nd Generation Intel Xeon Scalable processors—in part due to their greater core count. Overall, these new processors can generate accurate valuations 700x faster than the conventional model, which is sufficient to provide real-time results for common valuation workloads.
To establish that traders can receive fair value pricing in real-time without requiring specialized computational hardware, Quantifi partnered with Intel to evaluate the performance of their AI technology on CPU-based servers. As will be discussed in this whitepaper, the Intel benchmarks show that the recently launched 3rd Generation Intel Xeon Scalable processors, run the Quantifi ANN model 1.56x faster than previous 2nd Generation Intel Xeon Scalable processors—in part due to their greater core count. Overall, these new processors can generate accurate valuations 700x faster than the conventional model, which paves the path toward real-time results for common valuation workloads.