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Sceptical to buy at all-time high? Hedging can help you participate with peace

If your trading positions are a mix of stocks and indices, you can use portfolio beta to calculate the hedge required. This methodology can be used against futures positions.

SHUBHAM AGARWAL | 12-Jun-21
Reading Time: 3 minutes

Have you bought an expensive phone and worried about what if it spills, drops or hardware fails? To protect yourself from that risk, you can opt for insurance. You pay a fixed amount for the insurance and in return can be confident that your phone is safe for a given tenure.

Similarly, taking a trade when the market has already ran-up, invites the additional risk of a mean-reversion/pullback. If a pullback happens, that can affect your short-term trades and this fear does not let you participate in the trend. Buying a hedge can provide peace of mind at a fixed cost.

Let us understand a simple way to hedge your short-term trades. Since the hedge, we are creating against is short-term trading positions the tenure of the hedge could be small and targeted for the expiry.

Hedging can be done for each position i.e. each instrument like Index, Stocks (if options are available against them), or can be a common hedge against the portfolio with a benchmark Index. In most cases, using a benchmark index like Nifty will be preferred where the options are highly liquid.

How much should you hedge?

If your trading positions are a mix of stocks and indices, you can use portfolio beta to calculate the hedge required. This methodology can be used against future positions.

To calculate portfolio beta, you can multiply the individual beta of each instrument with its weightage in your trading portfolio. Then the hedge required will be gross exposure multiplied by the portfolio beta.

If you have options positions , you can calculate portfolio normalized payoff and match the hedged PnL against the exposure.

Risks in hedging

If the hedge is not against the same underlying instrument and a benchmark Index is being used, it cannot be a perfect hedge but only an approximation. The positions still hold the risk of the stock not moving as per historical beta. Un-systematic risk is also open which could be scenarios of adverse news on individual stocks or for a sector. To eliminate this risk, each stock wise hedging is the solution that may not be practically possible due to the lack of availability of options, liquidity, etc.

How to hedge?

There could be many possible ways to fit the right hedge, but I’ll talk about two very simple strategies.

Long Put

The simplest form of hedging is buying a put option against a bullish trading portfolio. This strategy gives you unlimited protection on the downside and any quantum of fall is protected. However, this is an expensive hedge and may cost around 1%-3% for a monthly hedge within the IV range of 10% to 25% which is the general range of IV for Nifty .

Now comes the question do you really need an unlimited hedge while trading for the short term? If you are comfortable taking some risk and hedging only a normal market behavior this can save some cost. Let us say the recent pullbacks in Nifty has lasted only 300 points and you want to protect only 300 points fall in Nifty for the current expiry, this can save you a lot of costs and a Bear put spread can be deployed.

Bear Put Spread

In this strategy you will buy a higher strike put (preferably ATM) and will sell a lower strike put (OTM). This will save you cost, and a range of protection can be decided. This can bring down the hedge cost to within 1% for the expiry.

The hedges can be further optimized using OTM butterfly and many other strategies but Long Put and Bear Put spreads can be a good start.

Learn and read more about stock trading from Quantsapp classroom which has been curated for understanding of Nifty index from scratch, to enable option traders grasp the concepts practically and apply them in a data-driven trading approach.

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SHUBHAM AGARWAL is a CEO & Head of Research at Quantsapp Pvt. Ltd. He has been into many major kinds of market research and has been a programmer himself in Tens of programming languages. Earlier to the current position, Shubham has served for Motilal Oswal as Head of Quantitative, Technical & Derivatives Research and as a Technical Analyst at JM Financial.

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