FRM Valuation and Risk Models [Learn Implementation on R / MATLAB]

FRM Valuation and Risk Models 

Research areas:

1. Binomial trees (2 level are given, but they are easy, no real derivations are required)
2. Delta Hedging (It uses a part of Black Scholes and is interesting)
3. Coherent Risk
4. Black Scholes (80% intricacies in Derivative world is about this formula, and also used in Greeks, Greek is an area of research)
5. Worst case distribution 
6. We should have Neural network,Genetic algo, programming, detailed distributions for Monte Carlo, actuarial etc in this FRM but we donot have so still exam is manageable for those who have never studied quant. Probably these things are there in SOA exams.

Risk Neutral Approach using binomial tree, single step model

VAR and Risk models is an area that is different from the routine CFA syllabus which overlaps. Here the two important areas what I liked are:

Delta Normal Method, Linear and Non-Linear in VAR1

Expected and Unexpected Loss in VAR2

Some tough questions tough areas for FRM Level 1:

1. Inverse floater duration and convexity 
2. MBS convexity
3. Cheapest to Deliver 
4. Required return on bond the weird formula (was unseen to me)
5. VAR Correlation and different calculation methods (same as correlation)
6. VAR is then linked to currency 
7. Playing bonds and Duration and balancing the things

These 2 areas were not very clear while I read them so I will try to add some more stuff on these 2 areas.

Quant Risk Job looks like this:

Capital & liquidity modeling

Market risk stress testing

Counterparty risk, VaR and exposure modeling

AMA modeling/ Operation Risk identification and measurement

Valuation of financial instruments/ products

FRM Levl 1: Here VaR, Monte Carlo and Stress testing are the three most area of Risk Jobs.

FRM Level 2: Risk regulatory framework of one more of the major economies across globe (i.e. US, EU, etc.). Knowledge of Basel II/ III  or Solvency II principles and practice

FRM Derivatives areas for Jobs: Interest rate pricing models, equity and FX option pricing models, single and multifactor derivative pricing models, stochastic volatility models

Analytical tools recommended for Risk are SAS product suite (Base Stat, E-miner, Sas EGRC, Risk Dimensions),Excel/ VBA, Matlab, C++

This is more theoretical part.

Valuation and Risk Models 20feb