Scrape Yahoo Finance Market Data for Free
The bulls love the peaks and the bears love the stock market troughs. Big data is no magic wand to create wall street rags to riches stories or to save traders from bankruptcy. But data can help you in taking calculated market risks. It can help you identify, quantify and validate investment opportunities. It can help you find good investment deals that naked eyes might fail to notice. Read this insight to scrape yahoo finance market data for free.
Financial Data for Stock Trading
“Experts often possess more data than judgment.” – Colin Powell.
What does the latest financial news tell us? We are missing the big deals all the time. Should we follow the idea of momentum investing? What matters is how the entity performs in the business world and financial data tells everything. The truth is most of us are ignoring this data and not investing rather gambling.
In 2015, JCPenney’s second-quarter results shocked everyone. The company outperformed most of the market analysts and the stock jumped by 10%. But by using satellite imagery (an alternative data source) of JCPenney’s parking lot, RS Metrics and its client were able to foresee this improved performance and bought JCPenney stocks way before the 10% jump. This case study demonstrated how useful data can be for investors.
You can scrape financial data from official stock exchanges, and financial websites like Google Finance, Yahoo Finance, MarketWatch, Bloomberg, Nasdaq, NSE, SSE, etc., After you have the data, you may run GNN, RNN, CNN, and other deep learning models to correlate between different data points and predict future prices of stocks.
Scrape From Yahoo Finance
Yahoo finance is the financial media branch of the Yahoo network, now under Verizon. It provides financial news and data including currencies, cryptocurrencies, stock quotes from world indices, press releases, and financial reports.
We can scrape both qualitative, and quantitative financial data from yahoo finance. Stock-specific financial reports and daily stock trends (Volume, price movements, top gainers & losers, etcetera) are some of the quantitative data that you can collect around a stock. News, social media conversations, etcetera are some of the alternative data points that you can scrape to analyze customer sentiments.
Stock Data: Most-active, Gainers & Losers
From Yahoo finance, you can scrape stock data like trending tickers, most active stocks, top gainers, top losers, MFs, ETFs, Futures, Options, Treasury Bonds, Currencies etcetera. Scraping this data helps you identify intraday trends, as well as long-term gain early trends which barely get covered in the news while the opportunity exists.
Stock tickers change within a fraction of seconds, so do top gainers and losers. You can build custom scraping templates to scrape stock data frequently. Use the scheduled scraping feature of advanced no-code web scraping solutions to frequently scrape stock data every few minutes, hours, or days.
Finance News and Conversations
Financial news is very crucial from momentum trading in the stock market. Economic news often spurs strong up/down moves in the stock market. For example, a new policy by bank governing organizations, government, international unrest, a labor organization strike, hike in petrol prices, inflation, acquisition, stock buyback news, etcetera can create good trading opportunities in the market. Parallelly, based on what stock buyers are talking about on social media also indicates market sentiments about a particular stock. You as a market analyst can scrape financial news to early detect the bull/bear mood of the market.
From Yahoo Finance you can get all sorts of major financial news. Yahoo Finance’s home page itself is a news aggregator and collects news from all major financial organizations like Bloomberg, Barrons, Investopedia, MarketWatch, MoneyWise, Coindesk, IBD, etcetera. You can easily build scraping templates to scrape market-sensitive news using no-code click and scrape solutions within a few minutes. DealLogic is a company that offers integrated content, market analytics, and insights for financial firms to make intelligent investments. They used Octoparse to shorten its turnaround time by 75%. Read the full case study.
Now, you may scrape all the qualitative data in the world but nothing beats financial reports when it comes to long-term investing. Financial reports are like medical reports of listed companies. It contains all the crucial information that can help you in investing. Financial reports help you to invest in the right companies at the right price at the right time. What’s the point of missing the deal and then thinking “Oh! What if I had known this stock was about to skyrocket :|”.
Now, you can scrape company financial reports as soon as they are out, also you can scrape all the expert coverage related to these reports. These help you get the pulse of the market sentiments, and you can accordingly decide whether to invest or not.
How Octoparse Scrape From Yahoo Finance
Octoparse is a no-code, AI-powered web scraping tool. It’s a market leader in the automated scraping tools space. Using Octoparse you can easily scrape both qualitative and quantitative stock data. If you’re not already acquainted with Octoparse, refer to this resource. If You’re already a user, you would know there are two ways to scrape using Octoparse:
Use pre-built templates to scrape popular websites
Octoparse provides you with 100s of templates for popular websites across industry verticals. Using these templates you can start scraping within a few seconds/clicks. For Yahoo Finance, we have a template available:
To scrape using a pre-built template, refer to this tutorial.
Build your own custom web scraping template
In this, you point and click your cursor on the target data points to build a scraping template. The best way to describe this is by demonstrating with an example. Let’s scrape financial data of “AAPL” which is a ticker for Apple Inc on Yahoo finance. Also, you can check a video tutorial that may be more helpful:
Let’s get scraping.
Prerequisites to scraping using Octoparse:
Step 1: Create an advanced template by clicking on the +New button.
Step 2: Enter the target URL of Apple Inc’s financial data.
You can observe that we have used the Enter Manually option of the Input URL(s). There are alternative ways to input URLs:
- You can import from a file, say a text file with links on new lines.
- You can batch generate URLs
- You can import from an existing task
Step 3: Click on Auto-detect web page data to use the AI features of Octoparse and automatically build the template.
Step 4: Click on “Switch auto-detect results” to get to the following format of scraped data.
In my case, the 3rd result suits the requirements as it’s the correct format. Now click on create a workflow.
Step 5: Click on “save” to save the automatically created workflow. And then click “Run” to run the task template.
Step 6: Run the task on your local device.
You may also run on Cloud, and use scheduled scraping features. But as these cost significant resources to the company, you are required to have a membership.
As soon as you click on run, it starts scraping. For APPL inc, it scraped 30 lines in the 17s.
Finally, you can scrape the data in your desired format, database.
Now, let’s view the data in Google Sheet or any spreadsheet application of your preference:
Similarly, you can scrape the financials of any company. Most importantly, you can schedule these to automatically scrape periodically when new financials are available. Companies usually reveal the financial report release data in advance.
You can leverage the yahoo finance stock market data to intelligently invest/trade in the market. Every piece of news, data matters in the very sensitive stock market. This was a major issue with DealLogic’s previous data collection mechanism, they were not able to scrape all data points efficiently. But with Octoparse they solved this problem and are now collecting all relevant data at scale and speed. Reach out to the Octoparse team for any scraping assistance. Happy scrapping, investing!
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