JPMC-Quant-Challenge-2022

The J.P. Morgan Quant Challenge is designed to introduce you to this team, and give you a flavor of algorithmic programming, data science & machine learning and derivative modelling in finance. The hackathon is divided in three sections – Algorithmic Programming, Data Science & Machine Learning and Derivative Modelling.

Challenge Link

Structure

• Machine Learning & Data Science: 9 am – 12 pm
• Derivative Modelling: 1 pm – 4 pm
• Algorithmic Programming: 5 pm – 7 pm

Top 3 participants from each category are selected for the finals. Shortlisted participants from each problem section will be invited for an on-site presentation to present their work to a panel of senior J.P. Morgan management.

Other Preparation Help

1. https://github.com/abhilashreddys/JPMC-Quant-Challenge-2019

2. https://github.com/ashaywalke/JPMC-Quant-Challenge/blob/master/Question%201-%20mathminers.zip

3. https://github.com/ffs97/jpmc-quant-challenge

4. https://github.com/Arkadeep-sophoIITG/JP-Morgan-Quant-Challenge-2018

5. https://github.com/sat14Siv/JP-Morgan-Quant-Challenge-2018?fbclid=IwAR0Iu2Ykh9ahzJmO0nqy7HJBfPrMrd2sQMeSY40zVtuhu6raaJJGJpXNraw

6. https://www.kaggle.com/code/r1shbh/notebook4c49155ee2

7. https://github.com/sat14Siv/JP-Morgan-Quant-Challenge-2018?fbclid=IwAR0Iu2Ykh9ahzJmO0nqy7HJBfPrMrd2sQMeSY40zVtuhu6raaJJGJpXNraw

Contributing

If there are any missed questions or any error please do let me know.
Your can contribute by providing explanations, solutions, codes etc for any of the problems. Just create a directory for your solution for any question you wish to solve.