The stock market is one of the most volatile things out there. The recent pandemic has proven that stock prices can change in the blink of an eye. As such, it has accumulated quite a lot of interest. At the moment, stocks are cheaper than they used to be, and this has brought quite a few people into the stock market.
In our blog posts, we usually talk about scraping data that applies to a very wide audience. Stock market data is different – it is more niche and useful only to a small set of professionals. If you have web scraping project ideas for financial instruments, then read on!
Web scraping is the process of accumulating as much data as possible from a preset index of sources or websites. If a corporation has an expanded index on a demographic, scraping it for particular data is going to reap accurate and viable information that a company can use for many things.
Commercial and marketing companies aren't the only entities that can benefit from data scraping, as stock data acquisition is a profitable process by itself. Stock data in the investing world is vital and can give investors information on the following:
Stock market trends
Web scraping stock data isn't the simplest thing in the world, but if done correctly, it could reap some fantastic results. It could give investors critical insight into a multitude of things, all of which can serve as relevant information for smart investing. Price scraping allows companies to gather publicly available information relevant to data-driven decisions.
In a nutshell, the scraping process for stock data can be divided into three main steps.
First, you need to define prerequisite data sources for stock data. In other words, you need to determine what type of data you need and where you can find it. Once you’ve identified the URLs of the websites you want to scrape, you need to send GET requests to the destination website. Also, you should clearly define the characteristics of your desired data in the GET request so that the scraper can collect it effectively.
Your second step will be parsing, which is the process of structuring data. In most cases, you’ll receive data in HTML or XML documents which isn’t a useful format for data analysis. Thus, you’ll need to parse the data into a tree structure path. For example, the Python library Beautiful Soup is often used to create structured data from HTML or XML documents.
Finally, you’ll need to store the structured data in a usable format. In most cases, this will be CSV, an Excel file, or JSON. With these, you’ll be able to perform data crunching or data analysis to generate insights about the financial market.
Stock market data scraping can be beneficial for businesses
Businesses can benefit from any form of scraping – user information, economic trends, and, finally, the stock market. When it comes to stock data, investment firms commonly utilize web scraping tools. They need an in-depth piece of data to make a proper assessment before investing in a particular stock.
Yet, safely investing in the stock market isn't the easiest thing in the world. The stock market is quite complicated and consists of multiple volatile variables. Each variable can have a large and unpredictable impact on the value of the stock. When all of these are analyzed based on the accumulation of data, investments can become significantly safer.
A great way to accumulate as much data as possible is to practice stock market data scraping. That means extracting data in huge amounts from stock markets through the use of a web or stock market scraper.
This software will automatically collect all viable information that can later be parsed to make smart and studied investments in the stock market.
There are several APIs that professionals use to acquire stock data from the web. Back in the day, Google Finance could have been used, but the project has been deprecated since 2012.
One of the most popular options is Yahoo Finance. Their API has been working on and off for years, as it has been both deprecated and revived several times. Several private companies offer APIs for those looking for more answers on where to get stock data if neither Yahoo Finance doesn't seem to mesh well with your project. Alternatively, stock exchange or finance websites can act as good data sources.
Investment firms and other businesses looking to increase their profits through stock market investment will have to use the tools required in stock data scraping. Data scraping isn't a straightforward process and requires multiple different tools to collect data, remove the variables and redundancies, and provide viable data.
Python is one of the most popular tools used to scrape stock market data. It’s a high-level programming language that has become a go-to option due to its simple syntax and reliability. In addition, it has in-built libraries such as Pandas, Selenium, and Beautiful Soup that save time by performing routine tasks.
A web crawler usually consists of a network of algorithms known as spiders. They can crawl finance websites based on predetermined rules. A web crawler is often confused with a web scraper, and even though they sometimes work hand in hand, they’re quite different. For example, a scraper focuses on specific targets and data extraction, whereas a crawler identifies targets and focuses on data discovery which can then be extracted or, in other words, scraped.
Some providers offer web crawlers as standalone products with some additional features. They’re usually targeted at people with little coding knowledge, which makes them easy to implement.
A Scraper API is a bit more sophisticated than a simple Python scraper or a web crawling software. In fact, it combines the best features of both. For example, an API will include a scraper, a crawler, and a parser which means that you only need to send the request for the information you want to extract, and the results will be delivered to you in a structured format such as JSON.
More importantly, products like Oxylabs’ Scraper APIs include such useful features as an in-built proxy rotator which allows you to effortlessly bypass geo-restrictions. Furthermore, with Oxylabs’ robust infrastructure, you won’t have to worry about maintenance or development. Finally, you can have peace of mind regarding cost-effectiveness because you only pay for successfully delivered results.
Stock market data scraping is not without challenges
Web scraping isn't the simplest thing in the world, as mentioned above. It's a careful collection of steps that need to be done in an accurate and timely manner to result in viable information and data. At times, there are preventive measures put in place to cut down data scraping.
That is why most high-end companies choose to create their tools, as there are plenty of obstacles that can obstruct the flow of the web scraping process. One of the most common issues associated with stock data scraping is blocked IP addresses. These will prevent the tool from accessing the directory, thus reaping no information.
Most of these issues are avoided by programming the stock data scraper in-house and outsourcing the resources such as proxies. While some of these issues are ultimately unavoidable, making a private scraper tool allows businesses to bypass some of these restrictions.
The stock market is extremely volatile and changes quite frequently. That's why it's best to use a real-time data scraper. A real-time data scraper is a data scraper that will collect, refine, and analyze the data in real time.
These are more expensive than their slower counterparts but are ultimately the best options for investment firms or any business dealing with precise, abrupt, and quick stock market investments.
Using a scraper tool to scrape stock market data is essential for any serious investment firm or any company looking to make informed decisions about stock market investment.
While there are a couple of issues associated with these tools that can hinder their operation, using one within your company's arsenal is integral to proper investment.
Scraping the stock market for data is as easy as indexing many different stock market websites and APIs, using a web scraper tool to scrape the directories for data – refining, analyzing, and finally using the resulting data.
Want to find out more about web scraping and data acquisition? Read our blog for more scraping and specifically Python web scraping ideas! We have plenty of information on almost every data gathering method out there.
About the author
PR Team Lead
Adomas Sulcas is a PR Team Lead at Oxylabs. Having grown up in a tech-minded household, he quickly developed an interest in everything IT and Internet related. When he is not nerding out online or immersed in reading, you will find him on an adventure or coming up with wicked business ideas.
All information on Oxylabs Blog is provided on an "as is" basis and for informational purposes only. We make no representation and disclaim all liability with respect to your use of any information contained on Oxylabs Blog or any third-party websites that may be linked therein. Before engaging in scraping activities of any kind you should consult your legal advisors and carefully read the particular website's terms of service or receive a scraping license.
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