For Investors, risk is about the odds of losing money.
What is my worst case scenario?
How much could I lose in a really bad month?
“VAR summarizes the worst case loss over a target horizon with a given level of confidence.”
- Philippe Jorion “
Value at risk measures the worst case expected loss that an institution can suffer over a given time interval under normal market conditions at a given confidence level. It assesses this risk by using statistical and simulation models designed to capture the volatility of assets in a portfolio.”
-Cormac Butler A portfolio is a bundle or combination of individual assets or securities.
VaR of a portfolio is simply
σ X z
σ:standard deviation of portfolio
z: z score value at a given confidence. eg:2.33 @ 99%
VaR CALCULATION METHODS Three methods:
1) HISTORICAL METHOD
2) VARIANCE-COVARIANCE METHOD
3)
MONTE-CARLO SIMULATION How investors can lower the risk in their equity investment portfolio by sensible diversification ? To calculate the Value at Risk of the industrial securities portfolio, so that, the investor can invest in modified Sensex portfolio by choosing similar alternative securities within ‘A’ group securities in terms of volatility with his own level of risk taking ability.
To understand the awareness of institutional investor and the technique used by those to manage risk adjusted return.
An investor invests on the basis of his risk taking ability. This study is to develop a methodology to measure or to calculate the possible loss in worst case. If the investor is ready to take that much of the risk, then only he will invest in that portfolio.
RESEARCH METHODOLOGY NATURE OF THE STUDY:
Analytical Study SAMPLING TECHNIQUE:
Judgmental Sampling (Sensex) SAMPLE Primary Data: A web based questionnaire was developed for professionals working in the field of Risk Management.
Sample Size :
3 Secondary Data:
The secondary data (share prices) is collected from www.bseindia.com
SOFTWARE USED FOR STATISTICAL CALCULATION
MS Excel 2003
Crystal Ball 5.1 Student Edition ANALYSIS:::::
ASSUMPTIONS Dividend is not taken into consideration.
The Scrip’s rate of return follows a normal distribution.
The holding period for VaR calculation is one day.
STEP ONE Data Adjustment
Capital Gain
(P1-P0) / P0
Average Rate of Return
Standard Deviation (Volatility)
Correlation Matrix
STEP TWO Sorting
Formation of Portfolio
Portfolio 1 Portfolio 2 Portfolio 3 Small SD* Medium SD* High SD*
Glaxo RANBAXY IPCL
BAJAJAUTO GRASIM INFOSYSTCH
ABB DRREDDY BPCL
*SD (Standard Deviation)
STEP 3 Portfolio Values are inserted
Crystal Ball is invoked
STEP 4 Assumptions, Decision Variables & Forecast Cells are defined.
MODELLING EQUATION
STEP 5 SIMULATION
The Crystal Ball generates the descriptive statistics.
QUESTIONNAIRE: Financial Institutional Investors Measuring risk is one of the crucial activities carried out by these financial institutions.
These institutions have group of experts for the purpose of calculating VaR.
As per the response from the designed questionnaire we have seen the that , Value at Risk is being used by the financial institutions. It is very specialized field of activity, utilized by experts.
For the purpose of calculation of VaR, they are using almost all possible method of calculations.
PORTFOLIO ANALYSIS VaR is calculated at
99% confidence
95% confidence
FINDINGS: TABLE OF RESULTS Portfolio SD Minimum Maximum Mean Portfolio 1 2,959.92 -9,032 10,638 205
Portfolio 2 3,042.05 -8,474 10,712 222
Portfolio 3 5,676.53 -17,278 20,330 393
Portfolio 3* 4,867.49 -14,255 17,327 686
RECOMMENDATIONS While maintaining the return it is possible to reduce the VaR in a portfolio by substituting with a less volatile security from a group instead of most volatile sensex security.
Such improvement in the risk adjusted return on capital (RAROC) can be achieved in each of the 3 above mentioned portfolios.
It is for each institutional investor to restructure his equities portfolio in accordance with his objectives using the tools and techniques that have been demonstrated in this project work.
Conclusion The methodology used to optimize the portfolio risk by measuring value at risk of the portfolio is very useful in real life situation also, as it is based on Monte Carlo Simulation. An investor can easily ident