Company: Mckinsey data scientist IITB
Difficulty: medium
Predicting the S&P 500 Index Problem Description The S&P 500 index is an American stock market index based on the market capitalizations of 500 large companies that have common stock listed on the NYSE or NASDAQ. Build a model using the prices of 500 stocks and the value of the S&P 500 index. This data is collected 4000 times per minute, Monday through Friday, from 9:30 AM to 4 PM New York time. The model then predicts the S&P index for the next 1000 minutes given the prices of all 500 stocks. Dataset You are provided with the training dataset in the form of a CSV file, train.csv . The file contains exactly 4000 rows and each row contains exactly 501 comma-separated values. The first 500 values describe the stock prices and the last is the S&P 500 index value. You are also provided the testing dataset in the form of a CSV file, test.csv that contains exactly 1000 rows. Each row contains exactly 500 comma-separated values that describe the stock prices. Submission Details Write the code