2 days ago

Sarthak • 0

Hyderabad

Predicting the S&P 500 Index

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 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 to build the model and predict the S&P index in the editor below. The code must save the predictions in the file prediction.csv, which contains exactly 1000 rows. Each row contains the value of S&P index that corresponds to the stock prices provided in the test.csv file. Note that both the files are provided in the current working directory. Use the file read-write techniques in your preferred language and then build the model to predict the S&P index for the stock prices provided in the test.csv file. The files do not have header rows.