Market Risk Modelling
Market Risk Modelling
In-house Training (2 days)

The Market Risk Modeling Course is very suitable for those who want to get an understanding of market risk modeling. Through this training, participants are expected to gain more in-depth knowledge of the latest modeling used for the calculation of market risk equipped with practical examples to facilitate understanding. In addition, we will also be discussing on stress testing and how to validate the models (backtesting). This program can be conducted in your office with approximately 12 hours or according to the needs of your company. In addition to getting the presentation materials of training, participants also get the software Excel-based Monte Carlo Simulation and various other spread sheets. Therefore, each participant is expected to bring a notebook respectively.

The agenda includes the following topics
  • Bank Risk Management: banking crisis, role of banks, balance sheet risk management, sources of risk, Basel II regulation, risk management framework, financial products;
  • Term structure of interest rate: time value of money, bond pricing, bootstrapping, discount factor, yield curve;
  • Sources of risk: market risk (interest rate risk, currency risk, equity risk, portfolio risk), asset liquidity risk, funding liquidity risk, credit risk, counter party risk, operational risk, and other risks, linear versus non-linear risk, modeling risk factors;
  • Market risk modeling: risk Measurement, Value-at-Risk, Variance Covariance Method (VCM), derivative pricing, cash flow mapping, Delta Normal, Cornish Fisher, Historical Simulation (HS), Full Valuation, Grid Based Valuation, Boudoukh-Richardson-Whitelaw, Monte Carlo Simulation (MCS), Full Valuation, Boot Strap, Grid Based, tail smoothing, IMA Basel II - Revision, Stressed VaR, incremental charge, stress Testing & scenario analysis, backtesting framework, Binomial Test, Kupiec Test, Conditional (Christoffersen) Backtest;
  • Computer workshop: VCM, HS dan MCS;
  • Counter party risk: settlement risk versus pre-settlement risk, current replacement cost, potential credit exposure
  • Liquidity VaR: liquidity adjusted VaR, cash flow-at-risk;
  • Monte Carlo simulation: introduction, random generator, probability distribution, Cholesky decomposition, define assumptions, determine forecast variables, calculate credit loss distribution using default mode model, VaR vs expected shortfall
  • Computer workshop: Monte Carlo Simulation