Kirubakaran Rajendran Profile picture
Data is the new oil,if you can interpret it,You can make money. Quant | Founder | https://t.co/wEkZGqw7Bj Telegram https://t.co/nRnMk50yUH Bots | https://t.co/XmXbkaX3c8
Deep Sarkar Profile picture 1 added to My Authors
21 Mar 20
Considering recent volatile movements in #Nifty and #banknifty due to #CoronaVirus ,did data analysis with 20+ years of historical data to find how the index moved after such gap days, how #intraday traders can develop a #TradingStrategy out of it. Here's the details.
Analysed the following scenarios.
List of gap down days, more than -1% on Nifty & Bank Nifty
List of Gap up days, more than +1% on Nifty and Bank Nifty
What is the % movement during gap down days, i.e from Open to close on such days.
What is the % movement during gap up days
There are in total only 82 times #Nifty opened gap down more than -1% in last 20+ years and this is how the Intraday movement were during such days. X axis represents percentage of gap down and Y axis represents percentage of intraday movement.
Read 21 tweets
29 Jan 20
In order to build #OptionsTrading strategy to make use of #budget volatility, we need to find out what has happened in the previous budget sessions. I did an extensive historical data analysis for the period 2008 to 2019, to find what kind of #TradingStrategy one can use
1/n
This is what happened during the intraday time frame on the #Budgetday for last 10 years of budget sessions.
2008
2009
Read 23 tweets
10 Jan 20
This is a simple #investing strategy applied on #BAJFINANCE, buy when stock price close above 200 dma and exit when it closes below. But I have applied another similar rule, and made better returns with just 7 trades and with much lesser drawdown. Can anyone guess? whats that?
the answer - 200 day moving average is almost equal to 10 months. We know on daily basis there is always lot of noise, but on monthly time frame the noise is less. So we avoid noise by moving to monthly time frame, just apply 10 MA on monthly time frame. squareoff.in/single-post/A-…
Read 2 tweets
15 Dec 19
How a timely help lead to a formation of multi billion dollar company #PAYTM Here’s the story
It was the year 2004. Vijay was struggling with his company One97 Communications,it was difficult for him to pay salaries for his employees and cost of business operations was also high
So some days he would do training or consultancy work to make money. He would go to companies and teach their employees about the InternetHe was paid Rs.1000 for a day of training. For some of the companies, he would setup a website & email while his team ran the One97 operations
The money Vijay earned this way kept One97 going. While on the training-consultancy circuit, Vijay ran into Piuyush Agrawal, whose Polar software needed help with its technology. Vijay’s work took Agrawal’s company from no profits to handsome profits.
Read 14 tweets
5 Dec 19
There are 1000s of companies listed in #NSE & #BSE, but how many of these companies were able to make at least more than 10% returns on yearly basis? Here's the details
There are always certain stocks that makes multi fold returns in short span of time, for example all Tech stocks were making huge returns during 1999–2000 period and all real estate stocks were making huge returns during 2006–2008 and NBFC recently.
So when you calculate annualized returns of all stocks, such bubble stocks can also come into list.
Instead I calculated all stocks yearly returns since listing and checked how many times, they were able to make at least 10% returns on yearly basis.
Read 5 tweets
28 Nov 19
Is it a good idea to keep accumulating #NiftyBees on every market crash for a long time? Just happen to read this question on Quora, so went head & did a 18 years of historical data analysis. Here's what I found.
Let’s analyze two scenarios.
1. How much we would have made by now, if we had invested X amount in Nifty bees every month from year 2002.
2. How much we would have made by now, if we had invested X amount only on Months when Nifty gone down significantly.
From Year 2002 to 2019, Nifty bees moved from 100 levels to 1300 levels. Consider we have invested Rs.10,000 every month from year 2002 to till now. Then our total investment value would be Rs.21.5 lacs and our returns is Rs.79.2 Lacs, that’s around 268% over all.
Read 10 tweets