Chapter 16

# Momentum Portfolios

## 16.1 – Defining Momentum

If you have spent some time in the market, then I’m quite certain that you’ve been bombarded with market jargons of all sorts. Most of us get used to these jargons and in fact, start using these jargons without actually understanding what they really mean. I’m guilty of using few jargons without understanding the true meaning of it and I get a feeling that some of you reading this may have experienced the same.

One such jargon is – momentum. I’m sure we have used momentum is our daily conversations related to the markets, but what exactly is momentum and how is it measured?

When asked, traders loosely define momentum as the speed at which the markets move. This is correct to some extent, but that’s not all and we should certainly not limit our understanding to just that.

‘Momentum’ is a physics term, it refers to the quantity of motion that an object has. If you look at this definition in the context of stocks markets, then everything remains the same, except that you will have to replace ‘object’ by stocks or the index.

Simply put, momentum is the rate of change of returns of the stock or the index. If the rate of change of returns is high, then the momentum is considered high and if the rate of change of returns is low, the momentum is considered low.

This leads us to to the next obvious question i.e is what is the rate of change of returns?.

The rate of change of return, as it states the return generated  (or eroded) between two reference time period. For the sake of this discussion, let’s stick to the rate of change of return on an end of day basis. So in this context, the rate of change of returns simply means the speed at which the daily return of the stock varies.

To understand this better, consider this example –

The table above shows the daily stock closing price of an arbitrary stock for 6 days. Two things to note here –

• The prices are moving up on day to day basis
• The percentage change is 0.5% or higher on a daily basis

Consider another example –

Two things need to note –

• The prices are moving up on day to day basis
• The percentage change is 1.5% or higher on a daily basis

Given the behavior of these two stocks, I have two questions for you –

• Which stock has a higher rate of change in daily returns?
• Which sock has a higher momentum?

To answer these above questions, you can look at either the absolute change in Rupee value or the percentage change from a close to close perspective.

If you look at the absolute Rupee change, then obviously the change in Stock A is higher than Stock B. However, this is not the right way to look at the change in daily return. For instance, in absolute Rupee terms, stock in the range of say 2000 or 3000 will always have a higher change compared to Stock A.

Hence, evaluating absolute Rupee change will not suffice and therefore we need to look at the percentage change. In terms of percentage change, clearly Stock B’s daily change is higher and therefore we can conclude that Stock B has a higher momentum.

Here is another situation, consider this –

Stock A, has trended up consistently on a day to day basis, while stock B has been quite a dud all along except for the last two days. On an overall basis if you check the percentage change over the 7 day period then both have delivered similar results. Given this, which of these two stock is considered to have good momentum?

Well, clearly Stock A is consistent in terms of daily returns, exhibits a good uptrend, and therefore can be considered to have continuity in showcasing momentum.

Now, what if I decide to measure momentum slightly differently? Instead of daily returns, what if we were to look at the return on a 7 days basis? If we were to do that, then both Stock A and B would qualify as momentum stocks.

The point that I’m trying to make here is that traders generally tend to look at momentum in terms of daily returns, which is perfectly valid, but this is not necessarily the only way to look at momentum. In fact, the momentum strategy we will discuss later in this chapter looks at momentum on a larger time frame and not no daily basis. More on this later.

I hope by now, you do have a sense of what exactly momentum means and understood the fact that momentum can be measured not just in terms of daily returns but also in terms of larger time frames. In fact, high-frequency traders measure momentum on a minute to minute or hourly basis.

## 16.2 – Momentum Strategy

Amongst the many trading strategies that the traders use, one of the most popular strategies is the momentum strategy. Traders measure momentum in many different ways to identify opportunity pockets. The core idea across all these strategies remains the same i.e to identify momentum and ride the wave.

Momentum strategies can be developed on a single stock basis wherein the idea is to measure momentum across all the stocks in the tracking universe and trade the ones which showcase the highest momentum. Do note, momentum can be either way – long or short, so a trader following single stock momentum strategy will get both long and short trading opportunities.

Traders also develop momentum strategies on a sector-specific basis and set up sector-specific trades. The idea here is to identify sector which exhibits strong momentum, this can be done by checking momentum in sector-specific indices. Once the sector is identified, further look for the stocks within the sector which display maximum strength in terms of momentum.

Momentum can also be applied on a portfolio basis. This involves the concept of portfolio creation with say ‘n’ number of stock, with each stock in the portfolio showcasing momentum. In my opinion, this is a great strategy as it is not just plain vanilla momentum strategy but also offers safety in terms of diversification.

We will discuss one such strategy wherein the idea is to create a basket of stock aka a portfolio consisting of 10 momentum stocks. Once created, the portfolio is held until the momentum lasts and then re-balanced.

## 16.3 – Momentum Portfolio

Before we discuss this strategy, I want you to note a few things –

• The agenda here is to highlight how a momentum portfolio can be set up. However, this is not the only way to build a momentum portfolio
• You will need programming skills to implement this strategy or to build any other momentum strategy. If you are not a coder like me, then do find a friend who can help
• Like any other strategy, this too has to be backtested

Given the above, here is a systematic guide to building a ‘Momentum Portfolio’.

### Step 1– Define your stock universe

As you may know, there are close to 4000 listed stocks on BSE and about 1800 on NSE. This includes highly valuable companies like TCS and absolute thuds such as pretty much all the Z category stocks on BSE. Companies such as these form the two extreme ends of the spectrum.  The question is, do have to track all these stocks to build a momentum portfolio?

Not really, doing so would be a waste of time.

One has to filter out the stocks and create something called as the ‘tracking universe’. The tracking universe will consist of a large basket of stocks within which we will pick stocks to constitute the momentum portfolio. This means the momentum portfolio will always be a subset of the tracking universe.

Think of the tracking universe as a collection of your favorite shopping malls. Maybe out of the 100s of malls in your city, you may end up going to 2-3 shopping malls repeatedly. Clothes bought from these 2-3 malls make up for your entire wardrobe (read portfolio). Hence, these 2-3 malls end up forming your tracking universe out of the 100s available in your city.

The tracking universe can be quite straightforward – it can be the Nifty 50 stocks or the BSE 500 stocks. Therefore, the momentum portfolio will always be a subset of either the Nifty 50 or BSE 500 stocks. Keeping the BSE 500 stocks as your tracking universe is a good way to start, however, if you feel a little adventurous, you can custom create your tracking universe.

Custom creation can be on any parameter – for example, out of the entire 1800 stocks on NSE, I could use a filter to weed out stocks, which has a market cap of at least 1000Crs. This filter alone will shrink the list to a much smaller, manageable set. Further, I may add other criteria such as the price of the stock should be less than 2000. So on and so forth.

I am just randomly sharing few filter ideas, but you get the point. Using the custom creation techniques helps you filter out and build a tracking universe that exactly matches your requirement.

Lastly, from my personal experience, I would suggest you have at least 150-200 stocks in your tracking universe if you wish to build a momentum portfolio of 12-15 stock.

### Step 2– Set up the data

Assuming your tracking universe is set up, you are now good to proceed to the 2nd step. In this step, you need to ensure you get the closing prices of all the stocks in your tracking universe. Ensure the data set that you have is clean and adjusted for corporate actions like the bonus issue, splits, special dividends, and other corporate actions. Clean data is the key building block to any trading strategy. There are plenty of data sources from where you can download the data free, including the NSE/BSE websites.

The question is – what is the lookback period? How many historical data points are required? To run this strategy, you only need 1-year data point. For example, today is 2nd March 2019, then I’d need data point from 1st March 2018 to 2nd March 2019.

Please note, once you have the data points for last one-year set, you can update this on a daily basis, which means the daily closing prices are recorded.

### Step 3– Calculate returns

This is a crucial part of the strategy; in this step, we calculate the returns of all the stocks in the tracking universe. As you may have already guessed, we calculate the return to get a sense of the momentum in each of the stocks.

As we discussed earlier in this chapter, one can calculate the returns on any time frequency, be it daily/weekly/monthly or even yearly returns. We will stick to yearly returns for the sake of this discussion, however, please note; you can add your own twist to the entire strategy and calculate the returns on any time frequency you wish. Instead of yearly, you could calculate the half-yearly, monthly, or even fortnightly returns.

So, at this stage, you should have a tracking universe consisting of about 150-200 stocks. All these stocks should have historical data for at least 1 year. Further, you need to calculate the yearly return for each of these stocks in your tracking universe.

To help you understand this better, I’ve created a sample tracking universe with just about 10 stocks in it.

The tracking universe contains the data for the last 365 days. The 1-year returns are calculated as well –

If you are wondering how the returns are calculated, then this is quite straight forward, let us take the example of ABB –

Return = [ending value/starting value]-1

= [1244.55/1435.55]-1

= -13.31%

Quite straightforward, I guess.

### Step 4 – Rank the returns

Once the returns are calculated, you need to rank the returns from the highest to the lowest returns. For example, Asian paints have generated a return of 25.87%, which is the highest in the list. Hence, the rank of Asian paints is 1. The second highest is HDFC Bank, so that will get the 2nd rank.  Infosys’s return, on the other hand, is -35.98%, the lowest in the list, hence the rank is 10. So on and so forth.

Here is the ‘return ranking’ for this portfolio –

If you are wondering why the returns are negative for most of the stocks, well then, that’s how stocks behave when deep corrections hit the market. I wish, I had opted to discuss this strategy at a better point

So what does this ranking tell us?

If you think about it, the ranking reorders our tracking universe to give us a list of stocks from the highest return stock to the lowest. For example, from this list, I know that Asian Paints has been the best performer (in terms of returns) over the last 12 months. Likewise, Infy has been the worst.

### Step 5 – Create the portfolio

A typical tracking universe will have about 150-200 stocks, and with the help of the previous step, we would have reordered the tracking universe. Now, with the reordered tracking universe, we are good to create a momentum portfolio.

Remember, momentum is the rate of change of return and the return itself is measured on a yearly basis.

A good momentum portfolio contains about 10-12 stocks. I’m personally comfortable with up to 15 stocks in the portfolio, not more than that. For the sake of this discussion, let us assume that we are building a 12 stocks momentum portfolio.

The momentum portfolio is now simply the top 12 stocks in the reordered tracking universe. In other words, we buy all the stocks starting from rank 1 to rank 12. In the example we were dealing with, if I were to build a 5 stock momentum portfolio, then it would contain –

• Asian Paints
• HDFC Bank
• Biocon
• ACC
• Ultratech

The rest of the stocks would not constitute the portfolio but will continue to remain in the tracking universe.

What is the logic of selecting this subset of stocks within the tracking universe, you may ask?

Well, read this carefully – if the stock has done well (in terms of returns generated) for the last 12 months, then it implies that the stock has good momentum for the defined time frame. The expectation is that this momentum will continue onto the 13th month as well, and therefore the stock will continue to generate higher returns.  So if you were to buy such stocks, then you are to benefit from the expected momentum in the stock.

Clearly, this is a claim. I do not have data to back this, but I have personally used this exact technique for a couple of years with decent success. It is easy to back-test this strategy, and I encourage you to do so.

Back in the days, my trading partner and I were encouraged to build this momentum portfolio after reading this ‘Economist’ article. You need to read this article before implementing this strategy.

Once the momentum portfolio stocks are identified, the idea is to buy all the momentum stocks in equal proportion. So if the capital available is Rs.200,000/- and there are 12 stocks, then the idea is to buy Rs.16,666/- worth of each stock (200,000/12).

By doing so, you create an equally weighted momentum portfolio. Of course, you can tweak the weights to create a skewed portfolio, there is no problem with it, but then you need to have a solid reason for doing so.  This reason should come from backtested results.

If you like to experiment with skewed portfolios, here are few ideas –

• 50% of capital allocation across the top 5 momentum stocks (rank 1 to 5), and 50% across the remaining 7 stocks
• Top 3 stocks get 40% and the balance 60% across 9 stocks
• If you are a contrarian and expect the lower rank stocks to perform better than the higher rank stocks, then allocate more to last 5 stocks

So on and so forth. Ideally, the approach to capital allocation should come from your backtesting process, this also means you will have to backtest various capital allocation techniques to figure out which works well for you.

### Step 6 – Rebalance the portfolio

So far, we have created a tracking universe, calculated the 12-month returns, ranked the stocks in terms of the 12-month returns, and created a momentum portfolio by buying the top 12 stocks. The momentum portfolio was built based on the 12-month performance, with a hope that it will continue to showcase the same performance for the 13th month.

There are few assumptions here –

• The portfolio is created and bought on the 1st trading day of the month
• The above implies that all the number crunching happens on the last day of the month, post-market close
• Once the portfolio is created and bought, you hold on to the stocks till the last day of the month

Now the question is, what really happens at the end of the month?

At the end of the month, you re-run the ranking engine and figure out the top 10 or 12 stocks which have performed well over the last 12 month. Do note, at any point we consider the latest 12 months of data.

So, we now buy the stocks from rank 1 to 12, just like the way we did in the previous month. From my experience, chances are that out of the initial portfolio, only a hand full of stocks would have changed positions. So based on the list, you sell the stocks which no longer belongs in the portfolio and buy the new stocks which have featured in the latest momentum portfolio. In essence, you rebalance the portfolio and you do this at the end of every month.

So on and so forth.

## 16.4 – Momentum Portfolio variations

Before we close this chapter (and this module), I’d like to touch upon a few variations to this strategy.

The returns have been calculated on a 12-month portfolio and the stocks are held for a month. However, you don’t have to stick to this. You can try out various options, like –

• Calculate return and rank the stocks based on their monthly performance and hold the portfolio for the month
• Calculate return and rank the stocks based on fortnightly performance and hold the portfolio for 15 days
• Rank on a weekly basis and hold for a week
• Calculate on a daily basis and even do an intraday momentum portfolio

As you can see, the options are plenty and it’s only restricted by your imagination. If you think about what we have discussed so far, the momentum portfolio is price based. However, you can build a fundamental based momentum strategy as well. Here are a few ideas –

• Build a tracking universe of fundamentally good stocks
• Note the difference in quarterly sales number (% wise)
• Rank the stocks based on quarterly sales. Company with the highest jump in sales gets rank one and so on
• Buy the top 10 – 12 stocks
• Rebalance at the end of the quarter

You can do this on any fundamental parameter – EPS growth, profit margin, EBITDA margin etc. The beauty of these strategies is that the data is available, hence backtesting gets a lot easier.

## 16.5 – Word of caution

As good as it may seem, the price based momentum strategy works well only when the market is trending up. When the markets turn choppy, the momentum strategy performs poorly, and when the markets go down, the momentum portfolio bleeds heavier than the markets itself.

Understanding the strategy’s behavior with respect to market cycle is quite crucial to the eventual success of this portfolio. I learned it the hard way. I had a great run with this strategy in 2009 and ’10 but took a bad hit in 2011. So before you execute this strategy, do your homework (backtesting) right.

Having said all of that let me reassure you – a price based momentum strategy, if implemented in the right market cycle can give you great returns, in fact, better more often than not, better than the market returns.

### Key takeaways from this chapter

• Momentum is the rate of change of return and can be measured across any time frame
• A price based momentum portfolio consists of stocks which have exhibited highest momentum over the desired time frame
• Tracking universe should be carefully populated. BSE 500 is a good tracking universe
• Calculate the returns for the tracking universe
• Rank the stocks based on highest to lowest return
• The momentum portfolio is simply the top 12 or 15 stocks
• The expectation is that the momentum will continue during the holding period
• The asset allocation technique can vary based on backtesting Equally weighted portfolio is a good asset allocation technique
• Momentum can be measured on fundamental data as well – growth in sales, EBITDA margins, EPS growth, net profit margin etc
• Price based momentum works best in an upward trending market and not really in a sideways or a down trending market.
Module 10

#### Chapters

1. Keshav says:

Dear sir,What about volatility based delta hedging strategy?

• Karthik Rangappa says:

Kehav, perhaps I’ll add that sometime as an addendum. Moving forward onto the next module.

2. Ankit Bohra says:

When will Varsity Android app launch.. waiting for it..

• Karthik Rangappa says:

Here you go, Ankit – https://play.google.com/store/apps/details?id=com.zerodha.varsity&showAllReviews=true, please don’t forget to rate us on play store 🙂

• Ankit Bohra says:

Hey thanks sir.. app is awsum.. hopeing for all the modules to be added soon.. and even the new app of kite 3 is awsum.. thanks alot…

• Karthik Rangappa says:

I’m happy to note that, Ankit! Lots of efforts towards building these apps 🙂
Yes, eventually all the modules will be added to the app. Did you check out the wall feature?

• dec says:

h1

3. Nick says:

Sir,
Thanks for an this topic was waiting for it to be covered..
According to you which is the best source to get eod data which is adjusted of splits and bonus for bse 500 stocks apart from nse/bse websites.

And secondly you said u need a coder to get a this strategy working can u share excel sheets to calculate momentum score as you did for pair trading chapter

Thanks

• Karthik Rangappa says:

Nick, there are plenty of data vendors who provide you clean data. I’d suggest you subscribe to any of them. Unfortunately, I was unable to produce the excel, hence I took up the example of 10 stocks.

4. Shakeel ahamed says:

At present I am investing on long-term basis and good results and very much Happy with the returns. I want to start trading shortly and watching articles related… thanks… waiting further.

• Karthik Rangappa says:

Good luck, Shakeel!

5. Sundeep says:

Sir correct me if I’m wrong but this is one of the longest chapters in varsity and I enjoyed reading it in one sitting. I’m currently in the process of back testing the portfolio based on momentum. What would the next chapter be about sir?

• Karthik Rangappa says:

I’m glad you could read through it in one sitting, do share the backtested results if you are comfortable with it 🙂

This module ends with this chapter. We are moving ahead with the next one.

6. Sankar says:

Sir, Happy to see you in writing back. We, lot of individuals reading this but has fear in investing trade market. Hence, please write on Personal Investing on the next module. My humble opinion. Thanks

• Karthik Rangappa says:

Sankar, I’m happy to hear that. The next module that I’m thinking about is more on personal finance, including topics on mutual funds.

• Sankar says:

Eagerly expecting topics on Personal finance like how to allocate money in different instruments and mutual funds pros&cons. I know many friends who had reasonably lost money in share market. I am sure that those read this VARSITY may or may not gain money but they will not lose money. Great and different approaches taught by you is mesmerizing. Although I am an engineer, the way you thought us about straight-line equation is superb and thought provoking. No book can teach like this. Thanks

• Karthik Rangappa says:

Sankar, thanks for the kind words. I’ll put my best efforts to put up a good module on PF.

7. Chandan Chatterjee says:

Hi, Sir,
Coincidentally i was reading a book called. ” Stocks on the move by Andreas F. Clenow”. Awesome book on momentum strategies.
Thank you as always for your efforts to make us understand jargons in a very simple manner.

8. Satnam Singh Chhabra says:

Hi,

• Karthik Rangappa says:

We are working on the PDF, should be up by next week or so.

9. Arun says:

Dear Karthik,

I wonder where to put stop loss in momentum strategy?
in case I have intraday momentum portfolio, what shall be my stoploss?

• Karthik Rangappa says:

You can keep a 2% SL at a portfolio level, Arun.

10. Ankit says:

Sir, could you please guide as to how to download historical data for momentum protfolio? I am struggling with this. Also how does one identify if the trend is not up and when to sit in cash? thanks

Karthick, Is there any way to download historical data for multiple stocks at the same time??. From the nse website , I can download only one stock at a time, I am looking to download historical data for 200 stocks at the same time as I am planning for a 200 stock universe

• Karthik Rangappa says:

Sadha, I think you should check with an NSE approved data vendor for a solution for this.

Karthick,

I have searched over the internet for the past few weeks and could not able to find one.

Please note : I have not tried excel macros kind of things, is this can be downloaded only by this way?

12. Kulbir says:

Hi Karthik,

Thanks for putting in the efforts to compile this module on Trading Systems.
You discussed Calendar Spreads in great detail and also discussed Momentum Portfolios.

Do you think that you can add other trading systems to this module , for example Mean Reversion Systems and Trend Following systems ?

Kulbir

• Karthik Rangappa says:

Kulbir, pair trading is mean reversion and trend is momentum portfolio 🙂

13. Sukumar says:

Dear sir ..what will be the next module… I wish if it could be on mutual fund and fixed income / debt markets

• Karthik Rangappa says:

That’s the plan. Hopefully soon 🙂

14. somi reddy says:

can u please provide the pdf for this module?

• Karthik Rangappa says:

Looking into that Somi, will update soon.

15. sahil swaroop says:

sir if u can it would great if u can show the use of kalman filters for pairs trading in one chapter

• Karthik Rangappa says:

Ah, that can be a little tricky. Will check though.

16. vishant says:

why i can not downlod this module in pdf ?
all other module downlode in pdf then why is not ?

• Karthik Rangappa says:

We are yet to make this as a PDF, working on it.

17. Sundeep says:

Sir, I have been live testing momentum portfolio and thanks a ton for this chapter. My question is, I want to get more into Quantitative Trading and want to learn more like the Pair Trading strategies you’ve put up. What do I start for this? What kind of Statistics do I start learning?

• Karthik Rangappa says:

You need to know the basic of descriptive statistics, Sundeep. The ones that I have explained is the starting point for this. I’d suggest you pick up from here and learn more in that direction.

18. K Karthik Kaushal says:

Sir, how to calculate 1 year return… is it the algebraic sum of daily returns over the year? Or is it just with the two values at the start and end of the year?..If it is the latter then, could please verify the example calculation of yearly returns of ABB that you have shown.The ending value is wrong when taken from the table in step 3.

• Karthik Rangappa says:

If the return is for less than a year, then a simple absolute return will do. Yes, the start and end of year value will do. Can you please quote the numbers that you are seeing? I’m unable to figure.

• karthik kaushal says:

“Return = [ending value/starting value]-1

= [1244.55/1435.55]-1

= -13.31%”
I Just wanted to know if the ending value is the close price on 6th March 2019 which is not specified in the sample tracking universe table.

• K Karthik Kaushal says:

Sir, and also why do we need the entire 1 year historical closing prices to calculate the yearly return of a stock .What if we get to know only the starting and ending closing prices for that period or year?

• Karthik Rangappa says:

You need daily returns to see the trend. Starting and ending values gives you the absolute return.

• Karthik Rangappa says:

Thats right Karthik, the ending value is the closing price on the last day.

• Karthik Kaushal says:

Sir, how should we judge the momentum of stocks with daily returns over a period of 1 year after finding the yearly return for that year.Can u give me the logical explanation such that I can program it because the daily returns are sometimes negative and sometimes positive unlike the example of consistent positive returns you have illustrated?

• Karthik Rangappa says:

Karthik, frankly I just took a set of random stocks. If you think about it, stock selection should not really matter since you rank the returns anyway.

• karthik kaushal says:

Sir,do you mean it is enough to rank the stocks in the trading universe based on yearly returns and then assume that stocks in top have good momentum and can be held for the 13th month(or next one month)?

• Karthik Rangappa says:

Yes, this is one of the many ways you can define momentum.

19. Harish says:

Hi karthik,

I Would like to know whether,if we download Bhav Copy Archive of Historical Data for any Scrip from BSE/NSE. Do they Adjust all corporate actions like Stock Split,Dividend,Bonus issue etc. Inorder to perform BackTesting on a particular Scrip say from 1999 to 2019.How can we rely on that Data?

Regards
Harish

• Karthik Rangappa says:

Harish, Bhav copy is for the day and it just shows the change in price wrt to the corporate action. I personally think its best to look for the data from an exchange authorized data vendor.

20. Kulbir says:

Hi Karthik sir,

First of all I want to thank you a lot for posting all this content in such a logical manner in Varsity. This has been very helpful to me and I am sure to many other traders like me. Please keep contributing to trading community in the future as well.

Previously you suggested this book(Quantitaive Value Investing by Joe Marwood), this book is good for investors , but could you also suggest other books which have quatitative trading strategies discussed for swing traders or short term traders. You can please suggest some advanced books as well, I am sure I will be able to handle them after going through your content in Varsity.

Your guidance will be greatly appreciated.

Kulbir

• Karthik Rangappa says:

Kulbir, thanks for the kind words. Unfortunately, there aren’t many books related to Quant trading strategies. Let me run through my list once and get back on this.

21. sahil swaroop says:

• Karthik Rangappa says:

Hey Sahil, thanks for the kind words and encouragement 🙂
I’m guilty of not taking the efforts to learn to programme. But from what you say, it seems doable. Hopefully, I should motivate myself to dabble with it soon. Thanks for letting me know 🙂

22. Sankar says:

Awaiting for next chapter keenly Sir on Managing Personal finance and mutual funds

• Karthik Rangappa says:

Will start work on that soon, Sankar 😉

23. Sundeep says:

Sir what is the first chapter in next module and when is it coming out? I’m just very eagerly waiting.

• Karthik Rangappa says:

Will start work on that soon, Sundeep.

24. Kulbir says:

Hi Karthik,

I have started working on creating and testing a trading system which trades “With Trend Pullbacks”.

I was able to do this using technical analysis by looking at candlestick charts but after going through your modules I want to adopt a more staistics oriented approach.

Could you suggest something on how to go about creating a pullback entry system using a statistical approach.
Any help in this direction will mean a lot.

Kulbir

• Karthik Rangappa says:

Kulbir, the classic approach to get you warmed up is by testing the mean reversion strategies. Measure the average, figure where the stock is now wrt to the standard deviation and then estimate the reversion.

• Kulbir says:

Hi Karthik,

I was not able to get what you meant by: “Measure the average, figure where the stock is now wrt to the standard deviation and then estimate the reversion.”
Are you suggesting something with respect to a pullback system, can you please elaborate a little ?

Kulbir

• Karthik Rangappa says:

I’m talking a simple mean reversion strategy, Kulbir. All you have to do is figure out the current market price of the stock and estimate how many SD away it is wrt to the mean. The general perception is that stocks which have deviated away from the mean tend to revert to mean. You may want to test this hypothesis across different stocks and indices.

25. nikhil says:

Sir out of topic question but wanted to ask your opinion on Quantinsti Epat course if you know about it….?
Is it worth the price..- 2L?

• Karthik Rangappa says:

I’m really not sure, Nikhil. However, I’ve met the guys who run Quantinsti and they come across as really good in their domain.

26. Sundeep says:

Sir I am trying find 3-5 different different stocks from different sectors that do not have any correlation to each other. My question is, how do i find the relationship between different sectors?

• Karthik Rangappa says:

Sundeep, instead of finding sectors and being subjective, maybe you should run the correlation test and figure out the actual value.

• Sundeep says:

Sir you mean correlation test between the stocks present in the portfolio?

• Karthik Rangappa says:

Yup. Select the universe and run the correlation test.

27. Sundeep says:

Sir also, you have recommended me some amazing books like Mastering the trade, Little book of valuations.. Etc. If I’m being honest, I am s better trader now because of that book. It taught me how to fix my psychology. Of course varsity taught me the abcs of Stock markets. I had requested you put out the comprehensive books you think would help traders? I would really love to read more sir. Thanks for all your service. Greatly appreciated.

• Karthik Rangappa says:

I’m super happy to note that you read and enjoyed the books 🙂 Will certainly try and put up a list of books.

• Sundeep says:

Sir I’ll certainly wait for your list. But since I have some time on my hands right now, would you recommend 3 advance trading books that you think might be useful? Thanks a lot.

• Karthik Rangappa says:

28. Satyam Itankar says:

Sir, I am great fan of your teaching, and want to lean algo trading, please add some chapters on algo trading from basic (including topics from excel algo, amibroker, streak etc). I am not able to find from where should I start and build my system in a economical way. Please add chapters from start to end like you did for every topic in zerodha varsity.

• Karthik Rangappa says:

Thanks Satyam. I will try my best to do that, however, algo trading involves quite a bit of programming which I don’t know. Will try and see if I collaborate with someone for this. Thanks.

29. Sundeep says:

Sir I wanted to know which sectors in Indian equity are cyclical? And how do i study the cycles in market sectors?

• Karthik Rangappa says:

Most of the business (barring health care and education) are cyclical in my opinion. Business involved with commodities are (BPCL/HPCL/Hindalco etc) are all cyclical in nature.

• Sundeep says:

Sir could you please expand what exactly cyclical means? And would you point me towards how one would go about studying the cyclicality of sectors? Thank you.

I am not kidding but this happend today.

BNF is -300 in spot

BNF 32400 CALL is up by +100 which is 1500%

How is this possible?? and please make me understand the technical reason behind it?

14 chapters

21 chapters

16 chapters

12 chapters

23 chapters

13 chapters

7 chapters

19 chapters

16 chapters