Risk quantification has emerged as a very important component to a firm’s financial well-being. This course provides training on the usage of tools used in quantification of financial risk (including market risk, credit risk and operational risk) and problems related to financial risk management. The financial risk management course is full of hands-on and implementation of tools and techniques using recent market data. The course will provide the practitioner’s perspective in measuring various kinds of financial risks. It attempts to strike a balance between institutional details, theoretical foundations, and practical applications. The course will extensively make use of MS Excel and R.


At the end of the course, participants are expected to understand:

  • How to quantify financial risk as a number with perspective of measuring it
    • What is Value-at-Risk (VaR) and Expected Shortfall (ES)
    • How to estimate VaR and ES (using Historical Simulation, Monte Carlo Simulation, GARCH, EGARCH, GJR-GARCH and other GARCH family models, Range based models, Extreme Value Theory) of single asset, portfolio and single asset influenced by many factors using various tools
  • Basics and implementation of estimating VaR for the fixed income security
  • Basics and implementation of estimating VaR for the financial derivatives (options)
  • Basics and implementation of estimating VaR from perspective of credit risk measurement (CreditMetrics)
  • How to measure credit risk
    • Probability of default/expected default frequency and to estimate it
  • Basics of estimating VaR from perspective of operational risk
    • Aggregate Loss Distribution/Loss Distribution Approach
  • Liquidity risk.


The primary method of instruction will be through LIVE lectures that will be delivered online via internet to participant desktops/laptops or classrooms. The lectures will be delivered by eminent faculty from IIM Kashipur and expert(s) from industry. The course will be primarily taught though a combination of class exercises, presentations, take-home exercises, simulation and case studies. The course contents are organized in a way so as to provide the participants an introduction on application of analytics to various business aspects, followed by concepts of machine learning and their business applications and finally on leveraging big data technologies for analytics. All enrolled students will also be provided access to the Cloud Campus through which students may access other learning aids, reference materials and assessments, case studies, projects and assignments as appropriate. Throughout the duration of the course, students will have the flexibility to reach out to the Professors, real time during the class or offline via the Cloud Campus to raise questions and clear their doubts. Participants successfully completing and submitting the assigned project work and presentations will be awarded a Certificate of Completion.


The Executive Development Program in Applied Financial Risk Management will include lectures and learning material on the following topics.


Module 1: Basics of Financial Risk Management and Fundamental Probability Theory, Brief Overview of Financial Derivatives

Module 2: Market Risk Analysis for single asset: Non-parametric and parametric approaches to estimate VaR and Expected shortfall

  • Historical Simulation, Monte Carlo Simulation, RiskMetrics, GARCH, EGARCH, GJR-GARCH and other GARCH family models, Extreme Value Theory
  • VaR Evaluation: Backtesting

Module 3: Market Risk Analysis: For portfolio and an asset influenced by various factors

  • Standard Covariance/Correlation approach, RiskMetrics, Monte Carlo Simulation, Multivariate GARCH, VaR of factors

Module 4: Risk Measurement in Fixed Income Markets

  • Duration based partial revaluation approach (Historical Simulation), Cash Flow Mapping

Module 5: Credit Risk Measurement

  • Introduction to credit risk, Default Risk, Managing credit risk, CreditMetrics, Default probabilities, Agency ratings, Credit scoring and Internal rating models, Structural models for credit risk (Merton, KMV), Reduced form models, Logistic model for loan default evaluation

Module 6: Operational Risk Measurement

  • Introduction to operational risk with evidence of operational failures, Estimating VaR for operational risk (Aggregate Loss Distribution/LDA) using Monte Carlo Simulation, Operational risk management framework, Operational risk process models
  • Basics of Liquidity Risk – Liquidity Adjusted VaR under normal and stressed market

Module 7: Asset Liability Management in Banks – BASEL I, II and III


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