3 Ways to Scrape Financial Data WITHOUT PythonMonday, August 31, 2020
Financial market is a place of risks and instability. It’s hard to predict how the curve will go and sometimes, for investors, one decision could be a make-or-break move. That’s why experienced practitioners never lose track of the financial data.
We human beings are wired to see in short term. Unless we have a database with data in well structure, we are not able to get a handle on voluminous information. Data scraping is the solution that gets complete data at your fingertip.
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What We Are Scraping When We Scrape Financial Data?
When it comes to scraping financial data, stock market data is in the spotlight of attention. But there’s more, trading prices and changes of securities, mutual funds, futures, cryptocurrencies, etc. Financial statements, press releases and other business-related news are also sources of financial data that people will scrape.
Why Scrape Financial Data?
Financial data, when extracted and analyzed in real time, can provide wealthy information for investments and trading. And people in different positions scrape financial data for varied purposes.
- Stock market prediction
Stock trading organizations leverage data from online trading portals like Yahoo Finance to keep records of stock prices. This financial data help companies to predict the market trends and buy/sell stocks for the highest profits. Same for trades in futures, currencies and other financial products. With complete data at hand, cross-comparison becomes easier and a bigger picture manifests.
- Equity research
“Don’t put all the eggs in one basket.” Portfolio managers do equity research to predict the performance of multiple stocks. Data is used to identify the pattern of their changes and further develop an algorithmic trading model. Before getting to this end, a vast amount of financial data will involve in the quantitative analysis.
- Sentiment analysis of financial market
Scraping financial data is not merely about numbers. Things can go qualitatively. We may find that the presupposition raised by Adam Smith is untenable - people are not always economic, or say, rational. Behavioral economics reveals that our decisions are susceptible to all kinds of cognitive biases, plainly, emotions.
Using the data from financial news, blogs, relevant social media posts and reviews, financial organizations can perform sentiment analysis to grab people’s attitude towards the market, which can be an indicator of the market trend.
How to Scrape Financial Data without Python
If you are a non-coder, stay tuned, let me explain how you can scrape financial data with the help of Octoparse. Yahoo Finance is a nice source to get comprehensive and real-time financial data. I will show you below how to scrape from the site.
Besides, there are lots of financial data sources with up-to-date and valuable information you can scrape from, such as Google Finance, Bloomberg, CNNMoney, Morningstar, TMXMoney, etc. All these sites are HTML codes in nature, which means that all the tables, news articles, and other texts/URLs can be extracted in bulk by a web scraping tool.
To know more about what web scraping is and what it is used for, you can check out this article.
Let’s get started!
There are 3 ways to get the data:
Use a web scraping template
Build your web crawlers
Turn to data scraping services
1. Use a Yahoo Finance web scraping template
In order to help newbies get an easy start on web scraping, Octoparse offer an array of web scraping templates. These templates are preformatted crawlers ready-to-use. Users can pick one of them to pull data from respective pages instantly.
The Yahoo Finance template offered by Octoparse is designed to scrape the Cryptocurrency data. No more configuration is required. Simply click “try it” and you will get the table data in minutes.
2. Build a crawler from scratch in 2 steps
In addition to Cryptocurrency data, you can also build a crawler from scratch in 2 steps to scrape world indices from Yahoo Finance. A customized crawler is highly flexible in terms of data extraction. This method is also workable to scrape other pages from Yahoo Finance.
Step 1: Enter the web address to build a crawler
The bot will load the website in the built-in browser, and one click on the Tips Panel can trigger the auto-detection process and get the table data fields done.
Step 2: Execute the crawler to get data
When your desired data are all highlighted in red, save the settings and run the crawler. As you can see in the pop-up, all the data are scraped down successfully. Now, you can export the data into Excel, JSON, CSV, or to your database via APIs.
3. Financial data scraping services
If you are scraping financial data from time to time in a rather small amount, help yourself with handy web scraping tools. You may find joy in building your own crawlers. However, if you are in need of voluminous data for a profound analysis, say millions of records, and have a high standard of accuracy, it is better to hand your scraping needs to a group of reliable web scraping professionals.
Why data scraping services deserve?
- Time and energy-saving
The only thing you would bother is to convey clearly to the data service provider what data you want. Once this is done, the data service team will deal with the rest of all, no hassle. You can plunge into your core business and do what you good at. Let professionals get the scraping job done for you.
- Zero learning curve & tech issues
Even the easiest scraping tool takes time to master. The ever-changing environment in different websites may be hard to deal with. And when you are scraping on a large scale, you may encounter issues such as IP ban, low speed, duplicate data, etc. Data scraping service can free you from these troubles.
- No legal violations
If you are not paying enough attentions to the terms of service of the data sources you are scraping from, you may get yourself into trouble. With the support of experienced legal counsel, a professional web scraping service provider works in accordance with laws and the whole scraping process will be implemented in a legitimate manner.
Edited by Cici