A simple transformation is used to transform the normally distributed random variable E to a random variable R such that the distribution of R has fatter tails and thinner waist than the normal distribution. The fat-tail distribution is shown to give a good fit to the data on return of the portfolio in the Kuala Lumpur Stock Exchange. The following methods are used to find the distribution of the return of the portfolio: 1)Simulation 2)A combination of simulation and numerical integration. 3)Approximate method which involves the derivation of the first four moments of the return of the portfolio. The distribution thus found for return of the portfolio agrees well with the observed distribution of return of the portfolio. Value at Risk (VaR) based on the fat-tailed distribution is found to outperform the VaR based on the multivariate normal distribution. An approximate 95% confidence interval is found to be able to cover the true value of the VaR with a probability which is close to the target value of 0.95. The book is intended for practitioners in risk management, postgraduate students and academics working on risk measurement research.