Data update on:

The table below lists the correlation coefficient of all Nifty FnO stocks with each other, Nifty and Banknifty Index. The correlation has been calculated based on the daily % return of stocks for last one year. The first column is an indicative column just to tell which industry the company belongs to. You can sort the table by clicking on table headers and can do a textual search on the table using the search box below. We have done some color coding to depict high (green), medium (blue) and low values (red).

Data only available for paid subscribers

What can I do with stock correlation data?

In one line, you can use this data to build a low risk stock portfolio. And also can use it for correlation based pair trading. More on Pair Trading here.

Sounds interesting. Tell me more.

Ok, so you have seen the raw data in the table above. I agree that it's too much data to browse manually. So let's try to turn it into information. Just for the unaware, a one line definition of correlation (obviously in context of stock market):

Correlation is a statistic that measures the degree to which two stock prices move together

Correlation coefficient ranges from 1 to -1. A correlation coefficient of 1.00 between stock pair indicates perfect positive correlation - meaning when one moves up, the other moves up and vice versa. A correlation coefficient of -1.00 between stock pair indicates perfect negative correlation - meaning when one moves up, the other moves down and vice versa. Correlation coefficient near 0 indicate that the stock pairs are not correlated and generally do not move in tandem. With this high level understanding, look back at the table above and pick any cell value. if the value is nearer to 1 you can infer that the stock pair moves in same direction. If the value is nearer to -1, they move in opposite direction and if it's nearer to 0 (-0.3 to 0.3) then they move independent of each other. 

Yes makes little bit of sense now, but so what?

Ok, so now you have data and some information about the data. Let's focus on turning this information to knowledge. Look at the chart below. It's a bar chart showing all FnO stocks correlation with Nifty. All stocks which move with Nifty to the left (correlation coefficient > 0.8), all which don't prefer to move with nifty in the middle (correlation coefficient between 0.3 and -0.3) and all who prefer to move in opposite direction to Nifty to the right (correlation coefficient < -0.8). Don't be too surprised if you do not find any stock in the third category - think about it and you will get to understand why. It's basically survivorship bias - all the naysayers got eliminated from FnO ;-).

Let's also check how different FnO stocks correlate to Banknifty. No surprises here too - you will see most of the banking stocks on the left side of the chart. And again not many negatively correlated stocks here too for obvious reasons.

Time to go one level up and check how stocks from different industries correlate to Nifty. Look at the chart below. We are plotting industry average correlation figures against Nifty here. So now you know which industries are positively correlated, uncorrelated and negatively correlated to Nifty.

I have started loving it. Give me more.

Ok, so you looked at the correlation data, extracted some info and gained knowledge about correlated stocks. Only thing left is how to turn this knowledge to wisdom (real action and profit). So the wisdom here is to use this data to create a low risk portfolio - means selecting those stocks for your portfolio that are less likely to lose value at the same time in market downturn while simultaneously giving appreciable return in market uptrend. Here are some other benefits of holding a low risk portfolio?

  1. You will be less likely to push the panic sell button in blood bath as your portfolio will show less losses as compared to the market.
  2. You have the option of portfolio switching from uncorrelated stocks to correlated stocks when the tide turns - so you might not be forced to accept appreciable return in market uptrend but can actually reap stupendous returns. Don't get bogged down by the term portfolio switching - it simply means selling a set of stocks and buying another set of stocks. In your portfolio context it means to sell the uncorrelated stocks when the market is bottoming out and switching to positively correlated stocks with the index. By the nature of it, highly correlated stocks fall much in market downturn as compared to uncorrelated once so you can enjoy the benefit of selling stocks which are showing less losses as compared to market and switching to the once which are showing more losses as compared to the overall market. When market turns back and shoots up, this new set of highly correlated stocks to index will replace the word appreciable with stupendous.
  3. Using approach 2 above will save you from a lot of expenses if you are a mutual fund investor as you can manage your own portfolio now. Mutual funds charges you several kind of fees for offering similar kind of management while simultaneously offering you lesser returns most often than not. Having said that mutual funds have their own benefits and am not against them. The point I am making is you can act like a mutual fund for your own portfolio with more control and better return prospects.

Can you summarize - what do I need to do?

A key insight to draw from the above charts is - which are the stocks that actually move with the index (positively correlated stocks with the index) and those who don't (uncorrelated or negatively correlated stocks). Now look at the portfolio stocks you hold. Are they all positively correlated to index and to each other. If so you hold a positively correlated high risk portfolio. Why? Because when market falls, all your stocks will fall with the index and most probably they will fall more than the index. Not a good position to be in when market is trading near top as then chances of fall keeps increasing with every passing day.  However, if most of the stocks in your portfolio are uncorrelated or negatively correlated to index and each other, then you hold a low risk portfolio. Means when the market falls, some of your stocks will either not fall, go up or at least will fall less that the index. Surely a nice position to be in when the market is trading near top. 

So rule of thumb when you are building a correlation based portfolio:

In case you want to do fresh investment

If market is trading near high and you hold a positively correlated portfolio, your next buy should always be an uncorrelated or negatively correlated stock. Similarly, if market is trading near lows and you hold a uncorrelated or negatively correlated portfolio, your next buy should always be a positively correlated stock. 

In case you want to book profit/loss

If market is trading near high and you hold a positively correlated portfolio, your next sell should always be a positively correlated stock from your portfolio. Similarly, if market is trading near lows and you hold a uncorrelated or negatively correlated portfolio, your next sell should always be an uncorrelated or negatively correlated stock from the portfolio. 

Let me be the devil's advocate

Correlation is not static and changes for stock pairs on daily basis based on price movement. Having said that we should not be worried about every day movement. What we should focus on is the range shift over a period of time. if the correlation is shifting from range of 1 - 0.8 to 0.8 - 0.3 or even lower then we must relook at our portfolio if we hold the range shifting stock pair in the portfolio. 


Ok that sounds like a good pointer. But the data in the tables and charts above are daily snapshots, so how can I track the correlation shift for a particular pair over a period of time? Not to worry. You can choose your pairs in the drop down below and do the historical analysis for the same.  

This in not the end of it. There are various other creative things you can do with correlation data. Just do some googling and you will get to understand what I mean. Earlier all those articles and approaches might have sounded too theoretical to apply, however with easy access to all the correlation data above you can be more experimental now. So don't restrict yourself to what we have shared above. I will leave you here, but feel free to send us your feedback and suggestion. We would try our best to implement them.

Oh wait. There is something more for the more curious mind who wants to explore non FnO universe. Here is the correlation stats for approximately 1100 nifty stocks. We plan to update this list once a month. Do not freak out if you see small difference in correlation figure of FnO stocks in this view and the above view. The slight difference can be attributed to difference in number of rows we have taken for calculating correlation figures (ranges from 246 to 248 rows for last 1 year data).


Disclaimer* - The data on this page comes from what we have in our database and is not complete plus there might be inaccuracy in the numbers shown in the tables and charts above. So use this data for analysis purpose only and do not treat it as any recommendation to trade or invest. Also do a second level check for data accuracy from direct sources like NSE and BSE websites.

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