What is 'too good to be true' is generally so - especially so, in stock markets.
You come across something like Calendar Effects and your first reaction is: nice try. Maybe it used to work but cannot work anymore. After all, markets are efficient and if everybody knows something to work, lo and behold, it will stop working.
In this post, let's look at the so called 'turn of the month effect'. For an accessible commentary, see Larry Connors 'Do Stocks show a bullish bias at month end'? Larry concludes: 'We show that over the past 11 3/4 years, stocks have been much stronger near months-end than they have been any other time of the month ... The fund managers like to buy near months-end, ...'.
So here we have:
a) an effect which has been documented in other markets &
b) there is a plausible reason why it works and might continue to work
Let's test it in Indian markets.
I split the data into 10 groups so that group 1 contains dates 1st - 3rd, group 2 contains dates 4th - 6th and so on.
If there is any turn of the month effect, we should be able to see it when we plot average returns for each group. If there is turn of month effect then the group 10 (dates 28 to 31 of month) should have higher average returns. See the graphs for yourself.
Conclusion: Yes Virginia, there is a turn of the month effect in Indian equity markets. Last 3 days of month have been unusually good historically.
This is the graph for last 11 years: 2001 to 2011
Let's plot data for last 3 years i.e. 2009, 2010 and 2011.
How about the really bad 2008 - when nothing worked?
Cool. Even in the horrendous 2008, you actually made money if you were in the market only for last calendar week.
Notes:
(1) Data: S&P Nifty index data for last 11 years viz. from 1st January 2001 to 31 Dec 2011. You can download it from NSE. The data is already clean and in CSV format.
(2) For the geek reader, the code in R is hosted here
Hi Ravi,
ReplyDeleteis it not related with F&O expiry as last thursday normally comes last 3 days??
Regards
Sameer
I mean plot graph for strength of nifty on four four days Monday, Tuesday, Wednesday, Thursday with Thursday being F&O expiry date.
ReplyDeleteHi Ravi,
ReplyDeleteCan u find through your data analyser
what influence/correlation
week (having second last Thursday of a month)
have on
week (having last thursday/F&O expiry of a month)?
I mean influence of
ReplyDeleteNIFTY MOVE of week (having second last Thursday of a month)
ON
NIFTY MOVE of week (having last thursday/F&O expiry of a month).
Sameer,
ReplyDeleteThanks for your interest. I have made the data and code available and you can look into such stuff - that's the purpose of the blog i.e. raise the curiosity and let the data answer the questions.
Do let me know if you find anything interesting.
Regards,
Ravi
not at all aware of R language :)
ReplyDeleteYou can do it in Excel. It is a bit tedious in Excel compared to R but you can do it.
ReplyDeleteGreat post! A simple hypothesis to start with and a powerful 10-3-1 year regression. I like it. Looking forward to a hypothesis which works in the US market and doesn't shows a similar trend here.
ReplyDelete