Investment firms nowadays are in the race of developing sophisticated algorithms for stock trading. Whether it is about stock price prediction, stock market sentiment analysis or Equity research, they need a large volume of accurate data. It is often the case that they have the capital to hire a troop of developers. For independent researchers to predict the stock market, there is an affordable method to obtain the data at scale effortlessly.
In this article, you can learn the step-by-step guide on how to scrape stock data without any coding.
Best Stock Data Scraper
This method doesn’t require coding. You can extract valuable information from stock market websites without a tech background. Octoparse is such a web scraping tool that helps you extract data from any website including Yahoo, CNN Markets, The Economist, etc. You can export the market stock data in Excel, CSV, or any other formats you like. Learn more details from the steps in the next part, or the video case below.
Case study: scraping Yahoo Finance stock data
Steps to Scrape Stock Data
We will scrape the Balance Sheet from the Bank of America stock from Yahoo! Finance as an example. With the balance sheet in hand, you can build up a database altogether with the historical stock price. With this data, you could further build up algorithms/machine learning that correlates numbers with the prices of a stock. When you scale up the number of stocks, you have a bigger pipe to train your AI’s model.
The URL we are going to need is https://finance.yahoo.com/quote/BAC/balance-sheet?p=BAC
Step 1: Create a new project
Click “+ Task” under Advance Mode. Enter the URL into the box and click “Save URL”. This will bring to the Bank of America Stock Market with Octoparse built-in browser.
The data is presented in the form of Table cells. As a result, the bot needs to scrape by table rows. To clarify what I mean, we can open up Chrome developer tools and inspect the website source. The whole table is constructed with <tr>, and <tr> consists of multiple <td>s which stands for the data of a row. The data we are going to extract is stored inside each <td>. It makes sense that the bot follows the logic of the source code, and extracts the information by rows.
Step 2: Select the stock data you want to scrape
Next, we need to tell the bot what data we want to obtain. Click any number from the table cell. The bot discovers other numbers from the same column. As I mentioned earlier, we need to follow the logic of the source code and extract by rows. In this case, click “TR” at the bottom of the Action Panel. Now Octoparse finds the first row. This is great! Choose “Select All Sub-Element”, then choose “Select All” to proceed.
Step 3: Confirm your selection
Now, all elements have been selected successfully. Choose “Extract Data in the loop” command to continue.
Step 4: Start scraping stock data
Now we finish building the crawler! Click “Start Extraction” and choose “Local Extraction” to run the task. Notice that “Local Extraction” is to run the crawler on your own computer. Unlike Cloud Extraction which has multiple parallel extractions distributed into different servers, Local Extraction only taxes the local resource and the speed gets affected by internet and hardware. It is likely to get overloaded if you have concurrent running tasks. Therefore, Cloud Extraction is an optimal choice for large-scale extractions.
Step 5: Export scraped stock data for market analysis
The data you scraped can be exported in an Excel or CSV file. You can pick a preferred format to download the data to your local devices.
Final Thoughts
When it comes to an investment opportunity, it is a fundamental step to analyze how one company performs by examining the balance sheet. It is because a balance sheet is the financial statement of one company’s assets, debts, and returns. If the current assets are greater than the liabilities, this means the company can cover the short-term debts and is likely to hold a favorable position. When one company grows at a steady pace over the years, it is more likely your investment is in good hands. However, the balance sheet of a bank is much more complicated than that of one company. Bank investment tends to be riskier yet lucrative. It is reasonable to keep tabs on the bank’s financial performance for comprehensive decision-making.
