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If there is one thing that is a constant in the financial industry, it is change. Investment firms need to continually review their investment strategies and explore new asset classes and markets in their search for yield. There have also been significant market shifts including the move to OIS discounting, and an extended period of negative rates. The pace and magnitude of change shows no signs

Last week Per Eriksson from FINCAD participated in a webinar, “ How to Apply Python to Complex Markets,” hosted by Risk.net. The webinar brought together industry experts to discuss the benefits that Python can bring investment firms and the challenges associated with adopting the language and extending its use. In addition to Per, speakers included Risk.net’s Joel Clark, Gary Collier of Man Group

If you are following the news it may appear prudent to consider preparing for the end of Libor by 2021. The process of preparing will undoubtedly mean facing increased model complexity and associated costs to transition legacy systems that rely on Libor, but the transition to alternative benchmark rates will also expose the presence of new kinds of risk for investors. This topic is covered in my

The unprecedented proliferation of data in derivatives markets has led to the rise in popularity of Python, a multi-purpose programming language known for its ease of use, versatility and flexibility. Undoubtedly, the increased adoption of Python has helped enable greater collaboration and customizations for valuation and risk modelling and reporting. To delve more deeply into the application of

Complexity of valuation and risk management is increasing for both sell and buy side institutions, especially when cost of capital, counterparty credit risk and funding costs are included. To support best execution and risk reporting, firms need transparency into all aspects of a given price—including CVA, and preferably other valuation adjustments (xVA’s) as well. However, the reality is that