Where Can I Get a Dataset for Stock Trading Signals and Indicators?

Entering the world of stock trading signals and indicators can be overwhelming, with numerous datasets and resources available at your fingertips. Whether you are a beginner or an experienced trader, this article provides a comprehensive guide on where to find datasets that contain trading signals, such as buying or selling signals, as well as key indicators like the Relative Strength Index (RSI).

Financial Market Data Providers

Financial market data providers can be a gold mine for traders seeking detailed stock data and technical indicators. Some of the most popular sources include:

Yahoo Finance: This platform offers free historical stock data, which can be downloaded and analyzed to calculate indicators like RSI. (Keyword: Yahoo Finance) Alpha Vantage: This service provides free APIs that offer historical stock data along with various technical indicators, including RSI. (Keyword: Alpha Vantage) Quandl: This platform hosts a vast array of financial and economic datasets, including stock prices and indicators. While some datasets are free, others require a subscription. (Keyword: Quandl)

Trading Platforms

Trading platforms often come equipped with tools for storing and analyzing stock data, as well as generating trading signals based on various indicators. Here are a couple of popular platforms:

TradingView: This platform allows you to access a wide range of technical indicators and create custom scripts to generate signals. (Keyword: TradingView) MetaTrader: This advanced trading platform offers tools to analyze stock data and generate trading signals based on technical indicators. (Keyword: MetaTrader)

Python Libraries

For those who prefer a more programmable approach, Python libraries can be very useful. Libraries like Pandas and TA-Lib make it easy to retrieve stock data, such as from Yahoo Finance or Alpha Vantage, and to calculate indicators like RSI or generate trading signals programmatically. Additionally, yfinance provides an easy way to download stock data from Yahoo Finance.

Academic and Research Databases

Around the academic and research community, you can find a variety of datasets related to stock trading, including those with trading signals and indicators. Here are a couple of useful resources:

Kaggle: This platform often hosts datasets related to stock trading. You can search for specific datasets that contain the data you need. (Keyword: Kaggle) Google Dataset Search: This tool helps you find datasets hosted across the web, which can be a great starting point for finding the right dataset. (Keyword: Google Dataset Search)

GitHub Repositories

If you are looking for more specific datasets or code related to stock trading algorithms, open-source projects on GitHub might be just what you need. Many repositories focus on stock trading algorithms or financial analysis and provide datasets and code for calculating indicators, such as the RSI.

Example of Calculating RSI in Python

For those who want to dive directly into the code, here's a simple example of how to calculate the RSI using the Pandas library and yfinance for retrieving historical stock data. This example calculates the RSI for Apple Inc. (AAPL) and can be adapted for other stocks and time frames:

import pandas as pd
import yfinance as yf
# Download historical data for a stock, e.g. AAPL
stock_data  ('AAPL', start'2021-01-01', end'2022-12-31')
# Function to calculate RSI
def calculate_rsi(data, window14):
    delta  data['Close'].diff()
    gain  delta.where(delta > 0).rolling(windowwindow).mean()
    loss  -delta.where(delta 

This code fetches historical data for Apple Inc. (AAPL) and calculates the RSI, which you can then use for generating trading signals. Make sure to adjust the stock symbol and dates as needed for your specific use case.

By combining these resources, you can build a robust dataset for stock trading signals and indicators, making it a valuable tool for enhancing your trading strategy. Whether you prefer working with pre-built platforms, writing your own scripts, or leveraging academic research, there are plenty of options to choose from.