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Prashanth Krish | Portfolio Yoga - Part 81

Thomas Cook – Multi Year Breakout

Prof. Sanjay Bakshi had a recent article on why he bought Thomas Cook. You can read the same out here,

http://fundooprofessor.wordpress.com/2013/12/01/why-i-bought-thomas-cook/

So, how does the stock look Technically?

Here is a Monthly Bar Chart

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As can be seen, we are sitting just below a multi year resistance line. If the stock crosses & closes (on monthly timeframe) above 85, we should be able to see the high of 2007 (142) which in itself would mean a move of 67% from the breakout levels.

 

Full Moon – New Moon affect on Indian Markets

On the web, there is a lot of material on how Full Moon and New Moon affect a variety of events on earth and the stock market is said to be no exception either.

Here are some links you may want to glance through,

http://emf.sagepub.com/content/12/1/107.abstract

http://www.theidiotandthemoon.com/moontrading.html

http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1366663

Above and many others which can be easily searched for seem to suggest a linkage between Lunar Cycle and Market Returns. But as a trader, the question we need to get an answer for is

Does the linkage have predictive ability? 

If we can see a Predictive ability in terms of Pre and Post Lunar day, we can then use that information to modify the style of trading to take advantage of the same.

For this test, I used BSE Sensex (since the history is the largest available among Indian Stock Indices).

Period of testing was from 1980 to 2013 (November)

Not being a statistical does limit the amount of tests I can run.

The first thing I wanted to do was compare and contrast (correlation in other words) the average returns of 5 days Prior to the D day to the 5 days Post the D Day.

Reason for choosing 5 (and not 4 or 6): A month consists of 30 days which is equal to 2 Lunar Cycles. In a 30 day month, we generally have markets open for around 20 days (Saturday / Sunday being holidays). 20 divided by 2 = 10 and hence I have used 5 for post information and 5 for Pre information.

While the time frame is long enough to dismiss Sample Size Bias, there is still a problem in terms of Lunar Days which fell on either Sunday / Saturday or a Holiday. Since the whole excercise was done in AmiBroker, it has omitted days when there was no data and hence the test may not be complete in all respects.

But since this can affect both New Moon and Full Moon, I believe that the probability of they cancelling each other is high and hence do not believe that they will affect my conclusions in a great manner.

Now for the raw results:

The Correlation between return (average) of 5 days prior to Full Moon compared to 5 days post Full Moon = 0.05

The Correlation between return (average) of 5 days prior to New Moon compared to 5 days post Full Moon = 0.01

The correlation being so close to Zero essentially suggests that returns are random in nature and there is no way to guess as to if markets will rise in the next 5 days if they have fallen 5 days prior to the D day.

Below is the other data points I thought may give some indication of the returns as well as the probabilities;

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The only thing that caught my eye was that regardless of whether the previous 5 days were positive or negative, the next 5 were positive. But this can be easily explained by the fact that the markets have moved tremendously over the same period. The best way to remove that bias would have be to Zero Center the same, but that is for some day in the future 🙂

 

 

 

 

AD Volume line for CNX 500 stocks

A rally is said to have legs if the move is accompanied by strong volumes. One such indicator to measure the breadth of a market is the AD Volume Line. You can read more about the indicator here: http://stockcharts.com/help/doku.php?id=chart_school:technical_indicators:ad_volume_line

Below is a chart of the same calculated on stocks forming part of CNX 500 from the day market made a major bottom 28/08/2013 till date (19/11/2013). 

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Bank Sector – Active Investing vs. Passive Investing

Over the last 1 year, Bank Bees has returned a negative 1.22% ROI. Dedicated Bank Sector Mutual funds on the other hand have done much worse save for ICICI Prudential Banking and Financial Services Reg. 

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UTI Banking Sector fund seems to have done far worse despite its current portfolio showing it having its top 3 investments to the tune of 66.84% in Private Sector Banks. 

Internationally there has been a lot of evidence of how in the long run passive investing by investing into low cost index funds is a much better compared to active investing. Unfortunately lack of ETF’s in India is a big limiting factor when one wants to invest beyond Nifty / Bank Nifty. 

Is it time to invest into PSU Banks?

Even though the markets are near to all time highs, one major sector that is lagging behind is PSU Banking Index. The chart below is a relative plot of Bank Nifty and CNX PSU Bank Index. While PSU Bank Index has been found lagging the Bank Nifty, the gap was never as wide as it is now.

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But does that mean PSU Banks are cheap? The chart below plots the historical trailing PE of PSU Bank Nifty Index and a look at it does say that we are very near to valuations that were seen way back in 2009.

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But the difference between Bank Nifty (where Private Sector Banks are now the main movers and shakers) and PSU Bank Index shows that the difference is not due to a fall in Banking stocks as a whole but a fall based on the perception of quality of assets and the returns one may achieve going forward.

A play on Banks is a play on the Indian Economy as well. If one believes that we have seen the worst and the economy should be rising from here onwards, a long on PSU Bank is the best bet since there does exist some “margin of safety” in terms of one buying them at a near historical cheap valuation. But on the other hand if economy is seen to deteriorate even further,  the best bet would be to be long Bank Nifty and short PSU Bank Index (though this trade cannot be set up due to non availability of PSU Bank futures). 

Tendulkar vs. the Rest – Test Averages

Comparison of batting averages of players who have played a minimum of 50 test matches in their career.

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Indian Presidents and Sensex Returns

Of the many well known cycles in the market, one such cycle is the Presidential Cycle. This is applicable only to United States.

Quote about it from Investopedia:

A theory developed by Yale Hirsch that states that U.S. stock markets are weakest in the year following the election of a new U.S. president. According to this theory, after the first year, the market improves until the cycle begins again with the next presidential election.

While India follows the West Minister style of governance and hence we should maybe just replace the President with the Prime Minister, it does not work since there is not much of a fixed tenure either of the Prime Minister or the election themselves.

While our President has a fixed tenure and almost all of them have lasted their time, owning to he not being the decision maker as the US President is, there is not much of an influence he can create on the economy.

But I felt it would be interesting to analyze how the markets have behaved during the tenure of various Presidents starting from Giani Zail Singh and here are the results,

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Average Performance of the market during the 1st year of the President Term is the lowest with Year 2 and Year 3 competing head on head.

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The biggest gain came in the 3rd Year of Zail Singh when Sensex doubled. K R Narayan on the other hand saw 4 of his 5 years Sensex ending in Red.

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And finally, percentage returns of Sensex during their respective terms.

The first year of Pranab Mukherjee saw a return of 12%. With 2nd being positive across all Presidents, shall we see a continuation of the ongoing bull rally?