Market Risk Analyst – Associate – VP – Singapore
The Role:
• To provide timely and accurate market data for internal Market and Credit risk systems.
• Assist with systematic model testing for VAR, SVaR, CRM, CVA, and also support Backtesting and Stress testing.
• Research alternate sources of data for continued comparison and quality assurance, including data extracted from the bank’s internal systems
• Analyse time series data for information content that may be of use to GBM Risk Managers, such as market liquidity, hedge efficiency, and so on
• Validation of time series data including security pricing, asset pricing, index, corporate actions, trading data and market level data.
• Management of own daily production, data integrity and testing projects.
• Build relationships with vendors to obtain the most accurate source for security references and pricing data.
• Build relationships with internal client groups, managing expectations of service delivery and specific data content or coverage initiatives.
• Conscientious and methodical approach with good attention to detail.
Project delivery focused with ability to work to strict deadlines
Ideal Candidate
• Can demonstrate a detailed knowledge of at least two different asset classes (Fixed income, Equities, Commodities, FX or Credit)
• Has experience working in an Investment bank or Asset management firm with 1 to 3 years experience, preferably in a Market Risk role.
Understanding of VaR and can demonstrate an understanding of the different VaR methodologies.
• Excellent analytical and problem solving skills, especially a good understanding of statistics.
• Strong Microsoft EXCEL skills; ideally with the ability to write own advanced VBA code.
• Relational Database experience, with the ability to write SQL code advantageous
• Strong user of Bloomberg and Reuters and their tools for interrogating time series.
• Experience working with Sungard’s FAME database solution is desirable but not essential.
• Time series analysis e.g. data modelling, PCA, etc.
Skills in further programming languages (Java, C++, etc) and / or experience of statistical analysis packages (R, S-Plus, Mathematica, Matlab, etc)