As trading portfolios have become more complex, it has become more difficult for senior management to obtain a useful yet practical measure of market risk.
The most widely used summary measure is commonly known as VaR. Value-at-Risk is the maximum am...
As trading portfolios have become more complex, it has become more difficult for senior management to obtain a useful yet practical measure of market risk.
The most widely used summary measure is commonly known as VaR. Value-at-Risk is the maximum amount of money that may be lost on a portfolio over a given period of time, with a given level of confidence.
VaR is obtained by translating the riskiness of any financial instrument into a common standard-potential loss.
This paper focuses on introducing VaR and comparing historical simulation with Monte Carlo simulation for measuring VaR considering non-linear model.