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Author Archives: Cyril
Recently I wrote an experience report on running Monte Carlo simulation on a GPU for the newsletter of TopQuants. My piece is here.
Recently I had to familiarise myself with commodity futures. One thing that surprised me was the common unit of measurement for natural gas. It is used in MMBtu, which is a short for a million of British thermal units. It … Continue reading
This is not so much of a post, just a collection of bitcoin-related links: https://bitcointalk.org/index.php?PHPSESSID=309cf9027c5144b5cf3eef31f09866d0&topic=35812.0 https://bitcointalk.org/ http://bitcoinmagazine.net http://bitcoincard.org/ https://bitpay.com/ https://localbitcoins.com/ http://acceptbit.com/ https://github.com/kangasbros/django-bitcoin
Recently I needed to build a Monte Carlo simulator of a continuous-time Markov chain. This is a pretty straightforward exercise; the only catch was that I wanted it to perform well, so I had to use a fast algorithm for … Continue reading
Let’s calculate CVA (credit value adjustment) analytically. We will see that analytical CVA calculation is quite complex even for a fairly simple transaction (a vanilla swap). A few shortcuts will help us simplify the calculation.
When we have to calculate exposure at default (EAD) on a particular trade, we seldom have to compute it analytically (e.g. as shown here). More often we just take the current MtM of the trade and add the so-called add-on. … Continue reading
To calculate counterparty exposure, we need to calibrate our scenario generator to historical data. However, for CVA calculations, we need scenarios based on implied volatilities of the underlying risk factors. Continue reading
Financial models are never precise, but it does not make them useless. Continue reading
Potential exposure is not additive: the total exposure on two trades can be very different than the sum of potential exposures on each trade. Continue reading
This paper by S. Zhu and M. Pykhtin provides a blueprint for counterparty risk modelling framework.