Imagine you are a farmer and you want to grow Kharif crops (monsoon crops) like rice, maize, corn, peas, etc in your 10 acre field in India. Now, would you start sowing the field after rainy season ends or before rainy season starts. The probability of getting a good crop is more when you start sowing before the rainy season as certain conditions like water and moisture required for the crop are readily available to it.
Similar is the nature of markets. There are particular days (like rainy season) in a month where the probability of a bullish move is greater than other days. So, we did a thorough analysis of Nifty over the last 9 years and found out that there are some days where the market tends to rise.
Is there a trend?
We took 1 day Nifty data from 2011-2019. Then, we calculated the daily %change on closed prices and grouped it according to the date of the month. We took mean of this grouped data to get the mean of daily %change according to the date of the month.
You can notice irregular ups and downs right from the 1st week to the second last week of the month. But, it is worth noting that the last week of the month i.e., from 27th to 31st continuing to 2nd of next month, has a consistent trend of positive returns. This intrigued us to find whether this positive trend in the last week of the month can be exploited to make a trading system with an edge. But, we needed to confirm this seasonality before we can make any system out of it.
One way to confirm this seasonality in Nifty is to check if we can get similar conclusions when analyzed on days when Nifty was above 200DMA (200 day moving average). As we know that when Nifty is above 200DMA, its primary trend is bullish. So, we get a better idea whether this seasonality is true or we are just getting fooled by data.
We get a similar observation when Nifty was above 200DMA. You can also observe that since the primary trend is bullish, most of the days gave positive average returns. So, the results of this barplot might have been a bit biased towards our seasonality theory.
To check if the results are biased or not, we also tested this when Nifty was below 200DMA i.e., when the primary trend was bearish. The results showed us that compared to other days of the month, these 7 consecutive days (green bars) on average gave lesser negative returns.
The quest for reconfirming the theory did not end here. We checked the mean of 5 day rolling returns of each and every day of the month. This means if one would’ve started the bullish trade on 1st day of month, what would be his returns after 5 days. In this case, we got to see the trend starting from 22nd of the month since we are taking 5 day rolling returns and thus a shift of 5 days on the plot as compared to previous 1 day return plot. Hence, we got similar results supporting our theory of seasonality in Nifty.
Is there a seasonality of bullish trend in Nifty in the last week of the month? Yes, we just confirmed that with the data. A quick rationale supporting this theory is that Mutual funds need to disclose their Monthly portfolio at the start of the month and thus a huge inflow of money (rain) into the markets (field) by the end of the previous month.
But, these results might be considered true only when a trading system based on our theory gives a definite edge. We can try backtesting simple trading systems like buying a call option or selling a put option at the start of the last week of the month and squaring off the position after 5-6 days. If you’re successful in backtesting your systems based on this seasonality theory; do contact us irrespective of the results and we will help you share it with the trading community and improve your system.
That’s it for today.