Check VaR Margin to Evaluate Portfolio Risk

By Advisorymandi
20-April-2018 11:25:45 AM
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VaR Margin

The complexity of stock market showed that one margin is not enough to handle risk or uncertainty in price for all shares. That’s why Securities & Exchange Board of India (SEBI) has advised different ways to margin cash and derivative trades. It is because shares traded on cash market are settled in two days whereas derivative contracts take a long time to expire. And the most important margin in the cash market segment is the Value at Risk (VaR) Margin which is quite different from Volatility.

From the retail investor’s point of view, volatility is about the “How the security price changed in the past?” It is a more like a traditional measure to check the uncertainty/risk. On the contrary, the value at Risk (VaR) Margin cares about the risk of losing and most of all it tells that “How much you could lose in a day or month?” Therefore, VaR Margin is the best way to calculate the uncertainty and consider all the options.

In shorts, VaR margin is a technique which is used to measure the level of financial risk within the investment portfolio or firm.
Now we will discuss, “How we can calculate Daily VaR margin to evaluate portfolio risk?”

Componenets of VaR

  • Time Period
  • Loss Amount
  • Time Period

Methods of Calculating VaR

  1. Variance-Covariance

  2. Historical Simulation

  3. Monte Carlo Simulation

Variance-Covariance
To calculate VaR margin by the Variance-Covariance method, we assume that daily price returns are normally distributed. There are different ways to calculate the VaR for of an asset or group of assets (portfolio of shares). In the Variance-Covariance method, the underlying volatility can be calculated either by using an exponentially weighted moving average (EWMA) or simple moving average (SMA).

Historical-Simulation

This is a methodology we use to calculate Value at Risk Margin. In doing so, we believe that history will repeat itself from the future risks perspective. This is a non-statical approach where we order past returns from worst to best. This method estimates VaR without any parameters or assumptions about the distribution of data.

Monte Carlo Simulation

Monte Carlo Simulation is a VaR calculating method which follows the footsteps of historical simulation model except for one major difference of data used. In the historical simulation, we used historical data set but Monte Carlo worked on hypothetical data set generated by a statistical distribution.

VaR margin in risk measurement is a very common measurement technique which widely used by many financial-industry professionals. On top of that, it is very easy to understand and can be easily calculated to estimate the probability of the value of asset or group of assets. The only downside is the model based on a normal distribution. But, in reality, financial markets are known for non-normal distribution of returns which are so unpredictable.

Final Thoughts: –

Overall, we can say that VaR Margin is the heart of cash market segment and highly-recommendable for retail investors who are looking to check the probability of security prices of financial asset or assets. Although the models have some flaws like distribution set used to calculate VaR but no doubt, it is one of the best ways to address the risks of investment.
If you have any doubt or would like to add something then don’t forget to add in the comment section below.

 

Note: All information & data provided in this article is for the educational purpose as well as to give general information on the finance & economy, not to provide any professional advice or service. Views & opinions are not biased against the company and do not affect any official policy or any other agency, an organization within the content.

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Author: Advisorymandi

AdvisoryMandi is India's most trusted Stock Market Advisory marketplace covers NSE, BSE, MCX & NCDEX. Invest with confidence and harness the power of AdvisoryMandi to make smarter investment decisions in Stocks, Indices, Commodities, Forex & IPO.

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