We have provided you multiple market datasets from NSE (National Stock Exchange), BSE (Bombay Stock Exchange), Bitcoin (BTC/INR), S&P 500 (US Markets).
Your goal is to build an algorithm / model which is able to predict the market as accurately as possible (exciting!) You can choose the market of your choice from above to predict for or you can predict for multiple markets as well (The choice is yours depending on which one excites you most)
You also have freedom to choose the time period you predict forward for (you know your model best, so choose a time period that shows your models performance best) That means anything from next day predictions, to next month, to next year!
You can choose any libraries of your choice and any language of your choice (Python preferred)
The aim is to predict the future, have fun and make money while we do it :)
Your performance is evaluated based on the out of time results you publish and the quality of your code and the approach taken. Please also publish train and test performance results and keep an out of time set which is never shown or used by the model at the time of training.
This is a sample of a fork and pull request
You submit your final code by creating a branch and submitting it as a pull request to the main branch Put your name as the branch name and in the commit message you can put your Email ID and as an additional optional item a base64 encoding of your mobile number. eg. (911111000 becomes OTExMTExMDAw). In case you are not comfortable putting your encoded mobile number you can just put in your email and name. In the pull request please have a readme file called results.md with published results
In case you have any questions or issues just simply put it up as an issue in the github issues section here
Our philosophy for recruiting is why make it a process that doesn't add value in everyones lives! It doesn't need to always be a process of making people do things that doesn't help them in their futures. Have you ever sat through hours of testing, not got selected and felt, what was the point.
As such we have innovated in a process that ensures that even if you don't get selected, you learn something useful that can be helpful to you wherever you go.