# Fintech x DSS UCL Hackathon — Data

来源：https://www.kaggle.com/competitions/fintech-x-ds-ucl-hackathon/data

本地 Meta Kaggle 快照；不是本次实时页面。

# Dataset Description

This section outlines the files included in the competition and the format of each, helping participants understand how to use the data effectively.

Files

	•	train.csv: This file contains the training set, which you will use to train your machine learning model. It includes historical stock data with various features for a specific company.
	•	test.csv: This file serves as the test set. You will apply your trained model to this dataset to make predictions. The accuracy of your predictions on this data will determine your rank in the competition.
	•	sample_submission.csv: This is a sample submission file that demonstrates the correct format for submitting your predictions. Ensure that your submission follows this structure.
	•	metaData.csv: This file provides supplemental information about the dataset, including descriptions of each feature and any relevant notes that may assist participants in understanding the data better.

Columns

	•	ID: A unique identifier for each data point in the dataset.
	•	Open: The opening price of the stock for the day.
	•	High: The highest price reached during the trading day.
	•	Low: The lowest price reached during the trading day.
	•	Close: The closing price of the stock for the day (this is the target variable you will be predicting).
	•	Volume: The total number of shares traded during the day.
	•	Dividends: The dividend yield (annual dividend per share divided by the stock price) and the dividend payout ratio. 
	•	StockSplits: A history of stock splits, including the date and ratio.
	•	Date: The date of the stock, given as an object value