1.	You should only train your model with the given data. Any use of external data is prohibited.
2.	You are allowed to write your code in ‘Answer.ipynb’ only.
3.	Late submission on either Kaggle or report will not be accepted.
4.	Your submission to Kaggle is limited to 10 times a day.
5.	Only specified libraries are permitted to use.
- Python basic library, Numpy, Pandas, Scikit-learn, Matplotlib, Pytorch, Tensorflow, Keras + dependent packages installed by them.
6.	Any kind of action or code considered as cheating is strongly prohibited.
7.      You must predict the closing price ratio r_t with only subset of the given time-series input data [x_(t-60),…,x_(t-1)]. Using other data not mentioned is considered as cheating.

We will provide the accuracy of baseline models (DecisionTreeRegressor, RNN) for you to check your performance.