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Author Archives: Cyril
Monte Carlo on a graphics card
Recently I wrote an experience report on running Monte Carlo simulation on a GPU for the newsletter of TopQuants. My piece is here. Advertisements
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Units of measurement
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
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Bitcoin
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
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Diagonalising an intensity matrix of a reversible Markov chain
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
Posted in Mathematics
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CVA calculation example
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.
The dreadful 40-60 rule
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
Historical or implied?
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
Posted in Finance
Tagged counterparty exposure, credit value adjustment, CVA, EAD, historical volatility, implied volatility
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