The following points highlight the three main types of risk measurement techniques in relation to investment. The techniques are: 1. Capital Asset Pricing Model (CAPM) 2. Value at Risk (VAR) 3. Monte Carlo Simulation Method for Valuation.

#### Technique # 1. Capital Asset Pricing Model (CAPM):

CAPM is a model based on the proposition that on any stock required rate of return is equal to the risk free rate (coupon rate of government bonds) plus risk premium, where the risk premium reflects the effects of diversification. In other words CAPM return is risk adjusted through diversification.

Any investment in financial markets is subject to risk and return. Expected return on the investment depends on the amount of risk. Investors expect a high return for compensating higher risks. This is where capital asset pricing model (CAPM) helps us to calculate investment risk and what return on invest­ment we should expect.

Formula:

RR= γ + β(R-n)

Where:

r = Risk free rate

β= Beta of the security

R = (Expected) market return

RR= Required Rate of Return

Example:

If stock beta is 1.5%

Risk free rate is 9%

Market return is 15%

Required rate of return is 9 + 1.5 (15- 9) = 18%

#### Technique # 2. Value at Risk (VAR):

Value-at-Risk (VaR) is commonly used by investment banks to measure the market risk of their asset portfolios. VaR measures market risk by determining how much the value of a portfolio could decline over a given period of time with a given probability as a result of changes in market prices or rates.

In other words VaR answers the question, “What is my worst-case scenario?” or “How much could I lose in a really bad day?” A VAR statistic has three com­ponents: Time horizon, probability and an estimate of portfolio loss (or loss percentage).

Example: 12 months VaR of Rs.5,00,000 at the 95% confidence level implies that one would expect a loss more than Rs. 5,00,000 5% of the time or once in 20 years.

There are three methods of calculating VAR:

1. Historical Method:

This method assumes that asset returns in the future will have the same distribution as in the past.

2. The Variance-Covariance Method:

This assumes that risk factor returns are always (jointly) normally distributed and that the change in portfolio value is linearly dependent on all risk factor returns.