In its latest margin survey, the International Swaps and Derivatives Association reported that initial margin (IM) collected by the top 20 firms increased by 22% to $130.6 billion at the end of 2017. As new transactions become subject to IM requirements, and a wider range of buy-side firms fall into scope, the amount of regulatory IM being posted is expected to grow. 

Using exotic swaptions as an example, Andrew McClelland, director of quantitative research at Numerix, identifies how IM requirements arise from client trades and the hedge trades they necessitate, and determines the total MVA impact of the trade to the bank. 

When the final phase of the swaps market’s new margining regime takes effect in 2020, hundreds – possibly thousands – of buy-side firms will be hit by complex margin requirements. 

The unprecedented proliferation of data in derivatives markets has led to a rise in popularity of Python, a multipurpose programming language known for its versatility and flexibility. Undoubtedly, the increased adoption of Python has helped enable greater collaboration and customisations for valuation, risk modelling and reporting. Risk.net convened a panel of experts to discuss the application of Python within financial markets, the benefits it can bring to businesses and the challenges associated with adopting and extending its use.