Applications of VaR
- Equity portfolio application
- Domestic pension fund application: equities, bonds and cash
- Derivative structures
- Global portfolios: currency risk
- Hedge Funds
Strengths of VaR
- An attempt to put a single figure to the potential loss across different classes of securities
- No need to assume that manager style stays consistent over time
- VaR is the best measure available to estimate market risk in a forward-looking manner
- VaR reacts fast to changes in market risk/volatilities in the market
Weaknesses of VaR
- Indication of market fluctuations during normal market conditions
- Based on historical performance – no consideration of what the market might do in future
- A change in manager style can not be identified until enough data is collected
- Risky holdings can not be identified immediately
Advantages of Monte Carlo Simulation
Disadvantages of Monte Carlo Simulation
- model instruments with non-linear and path-dependent payoff functions
- not affected as much by extreme events
- can use any statistical distribution to simulate the returns as far as comfortably possible
Disadvantages of Monte Carlo Simulation
- Time consuming and complicated
- Costly to develop a VaR engine
Advantages of the Parametric Method
- Computation time is minimal
- It's simple
- It's simple
- Assumes that the historical returns and the changes in prices of the assets follow a normal distribution
- Does not cope well with securities that have a non-linear payoff like options or mortgage-backed securities
- Underestimates VaR at high confidence levels and overestimates VaR at low confidence levels
Advantages of Historical Method
- It computes quickly
- It's easy to explain to people
- Assumes the future will be similar to the past
- It produces misleading estimates
- Not easy to preform "what-if" analyses