Open Interest Query

#1
I came across something that reads...

"The Nifty call options added 31.77 lakh shares in open interest, whereas the Nifty put options added 2.15 lakh shares in open interest."

What can you interpret from the above statement? I am not certain if this signals bullish or bearish for what matters is were these options in the money or out of the money?

i.e. if Nifty is at 5600, call options are below 5600 then most people are bearish, if call options are for 5800 then most people are bullish. Same for put, but how do I interpret this statement?

Second, the provider says this info is as per NSE data, any clue on where can we get this information on NSE site? & can we get it on live basis?

Thanks.
 

Alchemist

Administrator
Staff member
#2
Usually, it's opinion of option sellers that is considered more important in option markets.

That's because option sellers (option writers) risk much more money than option buyers.

If call writers write many calls for a particular strike price, it can be assumed that the call writers believe that this strike price is a tough resistance.

Similarly, if put writers write many puts of a particular strike price, it can be assumed that the put writers believe that this strike price is a good support.

On Friday, the Nifty corrected sharply the last one hour. Call writers became more confident and started writing more calls.

That's why there was a significant increase of open interest for calls.

All the data that you want for Nifty options is available on NSE's site.

Here is the option chain data for NSE Nifty:

NSE - National Stock Exchange of India Ltd.

5800 and 5900 Nifty calls have the highest open interest among all Nifty options.

As on Friday, call writers were confident that those levels will not be crossed in this series.

Open interest changes as market moves up and down. That's because opinions also change with market.

When you look at options data, do keep in mind that usually options data only reflects the short-term opinion of option traders.

Don't over-analyze this data.
 
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