Job Descriptions
Murex is a recognized global leader in software development for trading, risk management and processing. Every day banks, asset managers, corporations and utilities, across the world, rely on Murex people and Murex solutions to support their capital markets activities.
Our motto “pioneering again” sums it all up: since its creation, Murex has reinvented itself time and again to adapt to capital markets revolutions – each time offering innovative software solutions to the industry. Over 1,800 specialists are located across our 17 offices: Beijing, Beirut, Dubai, Dublin, Hong Kong, London, Luxembourg, Moscow, New York, Paris, Sao Paulo, Santiago, Seoul, Singapore, Sydney, Tokyo, and Toronto
The MX CVA Module provides an integrated solution for the calculation and management of CVA on a unilateral and bilateral basis. At the core of the solution, an efficient hybrid Monte Carlo simulation engine powers the computational framework to assess the credit risk of legacy books and accurately price the incremental CVA of new positions with full consideration of netting and portfolio effects.
The corresponding credit fees can be automatically transferred to a CVA desk's portfolios and accounting entries are generated by broking the marked-to-market charge from the unit of valuation to the desired unit of account in accordance with fair-value accounting standards.
Within the PES Credit risk team, your mission will consist in validating the CVA P&L Attribution tool and reconciling it with CVA sensitivities. First, you will have a learning phase: global overview of the Murex software training on Counterparty credit risk and CVA and on credit risk mitigants (netting, collateral agreements) focus on the Monte Carlo simulation engine and its diffusion models focus on financial products, particularly IRD and FXD pricing
Then, your mission will consist in:
-Validating the CVA figures calculated by our Monte-Carlo simulation engine for a given date on a portfolio containing representative trades from different asset classes, with a focus on IRD and FXD trades;
-this involves validating the Monte-Carlo simulation (risk factors diffusion according to their diffusion modeling assumptions) and the revaluations on these trades along the simulation pathes and dates;
-Validating the CVA 1st order sensitivities (CVA DV01, CVA FX delta, etc) that are computed using are finite difference method, on the same portfolio;
-Validating the difference in CVA between two dates T1 and T2 (typically yesterday and today) explained by time effect, market data effects and new deals activity;
-the CVA module allows to run this decomposition at once, but in order to validate it, one has to manually shift the calculation date then check the time effect is correct, then shift the rate curves (i-e apply T1 market quotes for date T2) and check the rate curve effect, and so on for the other market data, and last to calculate the CVA for the new trades inserted between T1 and T2;
-Reconciling the CVA P&L Attribution with CVA sensitivities meaning with a CVA P&L that would be calculated using 1st order sensitivities (Taylor expansion approach)
-Writing a validation document detailing your findings and presenting it to the team.
Job Requirements
Student in a last year of a Master's Degree, a Master's Degree in Engineering or of a Business school, you are looking for an internship.
You have a good level in finance and in mathematics
Apply by email.
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