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Seasonality | Portfolio Yoga

Dogs of Nifty 50

Dogs of the Dow is a very old strategy strategy popularized by Michael B. O’Higgins in 1991 (Wiki Link). The concept if you aren’t too interested in checking out the link is to buy the top dividend yielding firms and holds for a period of 1 year before a new set is selected and invested therein.

On the US markets, this strategy has shown promise as per stats (Link).  I haven’t back-tested the same on Nifty 50 though I would assume that the risk of such a portfolio would not be too different from holding a portfolio of all Nifty 50 stocks.

So, here are the Dogs of Nifty 50. Will check back on this in Jan 2018 to see both the performance and the changes required for the forthcoming year.

 

Gann Day & its Implication

Today it seems is celebrated as Gann Day. I learnt this via blogger, Eddy Elfenbein who himself references this article from Barron’s (Link).

Gann has quite a large number of followers who believe that the future can be foretold using methods preached / written down by Gann. While I am a strong disbeliever in one’s ability to know how the markets will unfold in the near term future (its much easier to predict the extreme long term – it will be Up :)).

The thing about Gann day as the article explains is that and I quote “when markets are more likely to reverse than any other day of the year.”. Since I believe only when such wide (wild?) predictions are backed by substantial data, I decided to check the behavior of Nifty 50 in the following days of September 22.

Data itself is pretty hazy showcasing more of randominity than there being any order which in itself does not surprise me. A single day cannot be a major turning point year after year. In fact, even in cycle theory, practioniers look out for cycles that vary and aren’t concerned with it being of a fixed nature. Its only the ease of plotting cycles in our charting softwares that make us look for fixed width cycles.

As the data below showcases, after 2008, markets have barely moved much for the next 3 months (60 Calendar days). Then again, there is always a first time 🙂

Gann

 

CNX Nifty – First day of the month

One of the rational behind trading systems is to ensure that we are able to capture as much of the return as possible without having to go through a draw-down similar to what a Buy & Hold strategy would entail. This is achieved by being exposed to the market for as less a duration as possible.

One of the strategies which I stumble quite often is the strategy of the First day. The concept here is simple enough – Buy at close on the last day of the month and sell on close on the first day of the month (both trading days and not calendar).

I tested that idea for CNX Nifty (Spot) and while we are exposed just 1 day (out of average 20 trading in a month), we are able to capture 26% of the total move that happened in the interim period. For a strategy that has no major rationale behind it, this number is pretty awesome.

The testing period was between 1st Jan 1996 to 1st April 2015. The expectancy of the system comes in at 8.62. The system has 141 Winners and 90 losers. Average win is 38.04 points vs a Average loss of 37.39 points

A interesting point to note is the fact that not all months are the same in terms of profit potential (or at least, that has been the case historically speaking). June, March and July are the best months for the strategy while December, August and February turn out to be pretty bad months.

To get a better understanding, here is the chart showcasing month-wise break up of the return.

Mon

If one were to ignore months that were not in our favor, the odds increase even further. But then again, unless we have a clue as to why some months are better than the others, treating all months as the same would be the best way to trade strategies such as these.

The Equity Curve (points) generated by the system shows no major hiccups other than in 2008 when it saw quite a bit of volatility.

Mon

To get a better sense of the risk, here is the chart of the draw-down it would have faced.

Mon

The period between 2003 and 2007 was when it had the best performance with the equity more or less hitting a new peak every month or so. 2000 and 2008 were times when even the most disciplined trader who traded this strategy would have been shaken off by the incessant losses. Post 2009, while markets have been on a consistent rise, the strategy has had quite a few setbacks with one seeing multiple instances of 5% draw-downs.

The fact that this strategy has generated just 282 points from September 2011 till date shows that maybe, just maybe the strategy is getting out of favor with the rewards not worth the risk it entails.

But before we dump this strategy, lets run a Bootsrap on the returns to see whether the returns out here are due to pure luck or is there something more.

The p-value one gets is 0.55. For anyone who was not put off by the high draw-down one saw earlier, this should definitely be a deal breaker. Then again, the lack of any substantial profit over the last 43 months in itself says that the markets may have changed and this strategy no longer works as it did in a earlier time.

On a side note, it seems that this strategy has been under-performing since 2011 even on $SPY. Food for thought I think on how global markets may have become.