We count on the suggestions and comments left by advanced readers in the linkedIn thread to quickly complete this work with the quality expected from the Modern Computational Finance series.
The draft, co-authored by Jesper Andreasen and Antoine Savine, covers cash-flow scripting, a critical technology in modern Derivatives pricing and risk management, not covered in any alternative literature. Mathematically, scripting turns arbitrary descriptions of Derivatives cash-flows into a functional of the path of the market state so the prices and risks of arbitrary transactions may be computed in arbitrary stochastic models. Computationally, scripting produces a computation graph for the cash-flows of arbitrary transactions, which is then optimized and executed for the computation of prices and risks, in a similar manner to machine learning systems like TensorFlow.
Cash-flow scripting has been around for twenty-five years. It was invented in Societe Generale and Banque Paribas for the purpose of structuring exotic transactions and computing prices and risks in real-time. Since then, scripting has considerably evolved into a central piece in all Derivatives pricing, risk management and regulatory calculation platforms.
Jesper Andreasen and I have been working with cash-flow scripting since the mid 1990s, bringing this technology to production at BNP-Paribas, General Re Financial Products, BAML, Nordea, Danske Bank and Saxobank, among other places. We put in this book the sum of our experience, along with our views for the future of this technology. The book comes with an implementation in C++ available on GitHub. Scripting has strong ties to modern technologies like smart contracts or computation graphs for machine learning, although this is a chapter yet to be written.