The Risk Training Course Page & Resource Guide is now up and live. You can review the first two days of lecture notes and supporting materials covering risk management, value at risk and the fuel hedging case study. More materials will be added over the next four weeks as the two part course winds down at the SP Jain campus in Singapore.
Risk Training Singapore 2013 – Week one outline and objectives
The course focuses on the following themes:
- Value at Risk (VaR) & Margin Lending
- Hedging Applications (Fuel, Oil)
- Asset Liability Management (ALM)
- Counterparty Risk
In terms of Value at Risk topic coverage (week one) here is the grand plan. Help participants understand, build and extend Value at Risk (VaR) models in Excel using market data by:
- Building VaR models for equities, currencies, commodities and bond portfolios.
- Tweaking VaR models for speed, robustness and market shocks.
- Extending the original model to calculate marginal VaR, incremental VaR & conditional VaR.
- Testing conditional VaR to the true historical distribution.
- Linking Stop Loss & Capital Allocation decisions to Value at Risk calculators.
Risk Training Course – Relevance and Applicability
The Risk Management I & II Course is a two part full time MBA elective course offered to Finance track students enrolled at the SP Jain Global MBA program. The study notes are shared for enrolled students as well as for anyone else in our online audience who can find his way to this page. However familiarity with Excel and Excel Data Analysis tools is a pre-requisite. Some familiarity with Value at Risk and market risk concepts is recommended but is not a requirement.
You will get the most value from the materials shared on the Risk Training Course if you are a market risk analyst, a risk manager, a back office or audit professional or belong to a capital allocation team.
While VaR calculators are common, the workshops introduces alternate hacks that can be put to work immediately to improve calculation speed and market relevance of models. The ability to examine the insides of a model by building it step by step makes it easier to acknowledge model weaknesses, develop intuition and answer difficult questions raised by Board Risk Committee members.