Module 10 Trading Systems

Chapter 12

Trade Identification

39

12.1 – Trading the equation

At this stage, we have discussed pretty much all the background information we need to know about Pair trading. We now have to patch things together and understand how all these concepts make sense while taking up a pair trade.

Let’s start with the basic equation again. I understand we have gone through this equation earlier in this module, but I want you to relook at this equation from a trader’s perspective. I want you to think about ways in which you can trade this equation. I want you to see opportunities here. This is where everything starts to culminate.

y = M*x + c

 

What is this equation essentially trying to tell you? Well, frankly, it depends on how your perspective of this equation. You can look at it from two different perspectives –

  1. As a statistician
  2. As a trader

Since we are dealing with two stocks here, the statistician would look at this as an equation where the stock price of a dependent stock ‘y’ is being explained with respect to an independent stock price ‘x’. This process of ‘price explanation’ generates two other variables i.e the slope (or beta) ‘M’ and the intercept ‘c’.

So in an ideal world, the stock price of y should be exactly equal to the Beta times X plus the intercept.

But we know that this is not true, there is always a variation in this equation which leads to the difference between the actual stock price of Y and the predicted stock price of Y. This difference is also termed as the ‘residual’ or the error term.

In fact, we can extend the above equation to include the residuals and with that, the equation would look like this –

y = M*x + c + ε

Where, ε represents the error or the residual of the equation. Of course, by now we are even familiar with the stationarity of the residuals which adds more sanctity to the above equation.

Fair enough, now for the interesting bit – how would a trader look at this equation? Let me repost the equation again –

y = M*x + c + ε

Let us break this equation into smaller pieces –

y = M*x , this essentially means, the price of the dependent stock ‘y’ is equal to the independent stock price ‘x’, multiplied by the slope M. Well, the slope is essentially the beta and it tells us how many stocks of x would equal the price of y.

For example, here is the linear regression output of HDFC Bank (y) vs ICICI Bank (x) –

And here is the snapshot of the prices of ICICI and HDFC –

Now, this means, the price of HDFC Bank is roughly equal to the price of ICICI times the Beta. So, 1914 = 291 *7.61.

Don’t jump in to do the math, I know that does not add up ☺

But for a moment, assume if this equation were to be true, then, in other words, this essentially means 7.61 shares of ICICI equals 1 share of HDFC. This is an important conclusion.

This also means, if I were to go long on one share of HDFC and short on 7.61 shares of ICIC, then I’m essentially long and short at the same time, hence I’ve hedged away a large amount of directional risk. Don’t forget the basic premise here, we are considering these two stocks because they are co-integrated in the first place.

So here is the equation again –

y = M*x + c + ε

If this equation were to be true, then by going long and short on y and x, we are hedging away the directional risk associated with this pair.

This leaves us with the 2nd part of the equation i.e c + ε

As you know, C is the intercept. Now, at this point, I want you to recollect the ‘Error Ratio’ which we discussed in chapter 10.

Error Ratio = Standard Error of Intercept / Standard Error.

As you may recollect, we discussed the lower the error ratio, the better it is. Mathematically, this also implies that we are looking at pairs which have a low intercept.

Again this is a very crucial point for you to note, we are selecting the pairs, such that the standard error of the intercept is low.

Remember, in this equation  y = M*x + c + ε we are trying to establish a trade (or hedge) every element. We are hedging y with Mx. We are trying to minimize c or the intercept because we are not trading or hedging it. Therefore, the lower it is, the better for us.

This leaves us with just the residual or the ε.

Remember, the residual is a time series. We have even validated the stationarity of this series. Now, because the residual is a stationary time series, the properties of normal distribution can be quite beautifully applied. This means, I only need to track the residuals and trigger a trade when it hits the upper or lower standard deviation!

Generally speaking, a trade is initiated when –

  1. Long on the pair (buy y, sell x) when the residuals hit -2 standard deviation (-2SD)
  2. Short on the pair (sell y, buy x) when the residuals hit +2 standard deviation (+2SD)

Like in the first method, the idea here is to initiate a trade at the 2nd standard deviation and hold the trade till the residual reverts to mean. The SL can be kept at 3SD for both the trades. More on this in the next chapter.

I know this is a short chapter, but I will conclude it here, as I don’t want to clutter your mind with other information.

It is important for you to understand this equation from a trader’s perspective and figure out what exactly you are trading. Remember, we are only trading the residuals here. We are hedging away the stock price of y with x. The intercept is kept low, and the residual is traded.

Why is the residual tradable? Because its stationary and therefore, its behavior is kind of predictable. In the next chapter, I’ll try and take up a live trade and deal with the practical aspects of pair trading.


Key takeaways from this chapter

  1. The pair trading equation is actually the main equation which we trade
  2. Every element of the equation is looked into
  3. We hedge the stock price of y with the stock price of x. The beta of x tells us the number stocks required to hedge 1 stock of y
  4. By looking into the error ratio, we are ensuring the intercept is kept low. Please remember we are not hedging the intercept, hence this needs to be kept low
  5. The residual is what we trade as it is stationary and follows the normal distribution quite well
  6. A long trade is initiated when residuals hit -2SD. Likewise, a short trade is initiated when the residuals hit +2SD
  7. Long on a pair requires us to go long on Y and short on X
  8. Short on a pair requires us to go short on Y and long on X
  9. When we initiate a pair trade, we expect the residual to hit the mean, so we hold until then
  10. The SL can be kept at 3SD for both long and short trades

39 comments

  1. KUMAR MAYANK says:

    Hello sir
    It was quite a short chapter but very crucial i guess. Well i have a question. We can trade residual because it being a stationary time series but can we treat this data as normal distribution? I have plotted the graph of residual and it was forming skewed ND.
    Thanks
    Varsity student

    • Karthik Rangappa says:

      Yes, this is a crucial chapter, hence kept it short and to the point.
      As long as its stationary and has a p-value of less than 0.1 don’t bother about plotting the graphs. Just consider it stationary and look for trades.

  2. Mahendra Narayan Chavan says:

    Before reading varsity zerodha I was confuse about share market.But after reading this 10 chapters , I got lot of knowledge about stock market.I am very thankful to Nithin Kamat sir,who written varsity in so easy language.

    • Karthik Rangappa says:

      Nithin will be happy to note this, Mahendra 🙂
      Keep learning.

      • KUMAR MAYANK says:

        When i started reading the contents of Varsity in 2k16 i thought it was Nithin writing all these. But in few days i got to know it was you Karthik Rangappa 🙂 I guess many people get confused initially.
        Thanks

  3. KUMAR MAYANK says:

    I took the values of residual of HDFCBANK-HDFC and in next column z-score or what you say density curve. These two stocks are highly co-integrated with p value(SIC) .0146 and 0.0054 (AIC). For shorting when Z-score>=0.975 and for long z score =<0.025.
    It showed total of 4 trading opportunities during last one year and all were successful. One thing i noticed the profit gets maximised when z-score approaches 0.5 from both the sides. One more thing i noticed if one stock made gains other ended in loss.
    The average net profit was 80 points. Still i haven't figure out about the stop loss. We are eagerly waiting for the next chapter.
    Thanks
    Varsity student

  4. KUMAR MAYANK says:

    I conducted ADF test on residuals of regression analysis b/w 2 stocks for case 1) stock 1 as ‘X’ and S2 as ‘Y’ case2) S1 as ‘Y’ and S2 as ‘X’. Residual of case one was non-stationary (p=0.1386) while that of case 2 was stationary (p=0.0088).
    Here is the link for snapshot of the result:
    http://prntscr.com/jevuqj
    http://prntscr.com/jevv2u
    We need your comments, sir. If this analysis is valid then we should first test for stationarity of the series before comparing error ratio, shouldn’t we?
    Thanks
    Varsity student

    • Karthik Rangappa says:

      You need to select the pair based on the error ratio, Kumar. Do this first and then run the stationarity test.

      • KUMAR MAYANK says:

        Thank you!

        • akash patel says:

          @Kumar Mayank
          which software that was? for counting probability (p-value).
          i use amibroker with python to check cointegration…
          can u test mail me, i want to know something more about coint…my mail is anmpatel at gmail dot com.
          thanks.

          • KUMAR MAYANK says:

            Hello Akash
            I use EViews to check the stationarity of a time series. Sorry, but i didn’t get you, Akash.Can you let me know what you’re asking for?

  5. Akash Patel says:

    @kumar mayank and Kartikji
    P-value/probability/cointegration
    All are same things? You use Eviews to check probability* value right?
    The same thing i check in amibroker with help of python server.
    I just want to check whether all r same thing with different name or not…
    If same thing then its ok, otherwise i have to make some improvement with my existing system, thanks in advance.
    Ya and also want to know that Eviews is free? If not how much is fees.

    • Karthik Rangappa says:

      I’m not too familiar with either amibroker or Eviews. But yes, they are all essentially same.

    • KUMAR MAYANK says:

      Hello Akash
      Two securities are co-integrated when the residuals which we get after regression analysis are stationary. The stationarity of the residuals is checked by many tests one of them is Augmented Dicky-Fuller test. The o/p of ADF test is in terms of probability. The threshold value (p-value) is 0.05 or 5%. The lower the probability value the more securities will be co-integrated.
      Here is the link for EViews software: http://www.eviews.com/home.html
      Thanks.

  6. Akash Patel says:

    @mayank kumar
    I had download Eviews 10 student lite and registered it for 1 year.
    How to check cointegration for banknifty and nifty…can u please tell in few step?
    I am a good learner i will catch-up quickly..just need some initial help.
    Thanks.

    • KUMAR MAYANK says:

      Hello Akash
      Step1: Import your excel file into EViews
      Step2 : Go to file and select Unit root test option from drop menu.
      Step3: Select ADF test and run it.
      That’s all.
      Thanks.

      • Akash Patel says:

        Thanks
        Will try and get back to you.

      • akash patel says:

        ADF select only one series..though i typed in two series name.
        i select banknifty and nifty series from imported file.
        but test displayed only banknifty results.
        how can i select two series…
        thanks.

        • KUMAR MAYANK says:

          Hey Akash
          I guess you didn’t get what Karthik sir had written. We have to check the stationarity of residual time series data. The residual you obtain after regression analysis is to import to EViews. And if the probability of the data being a stationary time series is high then only it is of our use.
          Thanks

  7. Akash Patel says:

    @kumar mayank
    Yes..i still confused about heavy terminology of stats.
    U mean i have to run ADF test on bn/n ratio column(series)?
    Thanks for taking pain of my questions☺️

    • akash patel says:

      @Kumar Mayank
      i did this in Eviews..
      http://prntscr.com/jj3h30 for banknifty/nifty ratio series and
      http://prntscr.com/jj3kpi for dvr/motor ratio series
      i did not include todays (17-may-18) data…the p-value is more than 0.05 at present
      in amibroker for same period co-integration is
      http://prntscr.com/jj3m8g banknifty&nifty data from 23-5-17 to 16-5-17
      http://prntscr.com/jj3ndj dvr/motor from same data set.
      there is a diff. now question is which one is reliable? value from python server or from Eviews?
      and if we check cointegration directly from Eviews..there is totally diff values..
      http://prntscr.com/jj3pag
      http://prntscr.com/jj3oqs
      for eview which is correct?
      thanks bro.

      • KUMAR MAYANK says:

        Sorry i didn’t see the screenshot. I have no idea what Amibroker is showing in terms of cointegration. It is expressing cointegration as a number which i guess should not be probability. It will be better if you ask this to Karthik sir. One thing i want to add is that i have run ADF test on ratio and they are not stationary.
        Thanks

    • KUMAR MAYANK says:

      We run ADF to check the stationarity of time series data and it(data) could be ratio or residual. You need to load data into an excel sheet and then import this sheet to EViews. Now run ADF test and you have the results.
      Hope i have answered you, Akash.
      Thanks

  8. ricky patel says:

    All modules are very good organize for the one who does not have any knowledge about stock market will receive by reading all above modules.
    all i wanna know is there are more chapter comes in this module or it is done. also i request you to add one more module on Quant trading if you can.

    all though i like the way you guys explain things with example so i think you can explain easily Quant topic as you have done.

    again you have done very good work here..
    Thanx

    • Karthik Rangappa says:

      Ricky, thanks for the kind words. This module is still work in progress. Will add few more chapters here.

  9. pratim says:

    I could not find download pdf option in module-10, it would have helped. Thank you.

  10. Thirumal Sharma says:

    Hi Karthik ji, first of all would like to thank you for the wonderful insights as how professional trading is done. Was just curious to know, if you take an example of Kotak Bank and RBL bank from the pair data list when we calculate the regression for last 1 year (Kotak as Y and RBL as X) , i am not able to calculate mean of residuals as its throwing error (out put is something like -2.28E00..) Standard deviation is 71 also not able to apply normal distribution for this. Not sure where i am going wrong 🙁 could you please guide? it would be very helpful.

    Thanks again.

  11. Sivan says:

    Sir,
    You are doing a great job by teaching all of us and fantastic, Nowadays, you are teaching on subjects where PhD can be done and topics are so complicated where average people like me lost interest on following such topics. I remember very well that I will be checking for new contents very frequently and learn from your teaching but as of now I am not visiting the varsity due to advanced topics. Hence, I request you sir to take very common subjects and take us along with your teaching journey
    Sivasankar

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