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Use web scraping for alternative data for finance

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By the one and only

The demand for alternative data is surging, due to its availability, scale, and striking ability to generate alpha. Hedge funds and investors are increasingly incorporating alternative datasets into their workflows to inform the investment decision-making process. Among them, web data has consistently proven the most powerful and popular.

Web data is the #1 source of alternative data, helping to inform the world’s best asset managers of market opportunities and arming them with the insight needed to act quickly and develop positions carefully. When it comes to extracting high-quality data from the web, there’s virtually no limit to the type and quantity of data available.

In this guide, we’ll explain several types of web data available for scraping and how they can be used to inform the investment decision-making process.

  • Product data
  • SEC filing data
  • Product reviews
  • Company news
  • Sentiment analysis

Product data

Scraping product data from complex online marketplaces is a difficult task, but one providing huge insights into a number of factors critical for evaluating company fundamentals and stock performance.

This data unlocks lucrative opportunities for investors when determining market orders and positions, while also providing insights into long term trends.

SEC filing data

Taking a dive into the lengthy and often vague pages of a company’s SEC filings can lead to amazing investment insights. It arms investors with high-quality, reliable information — data already held to strict standards by the US government.

Now, by scraping SEC filing information, the discovery process familiar to investors can be replicated tens of thousands of times across an unlimited amount of filings, unearthing precious alpha in otherwise unseen places.

Product reviews

To accurately predict how a stock is going to perform for any given company, it helps to understand how key products are tracking in the marketplace.

Unfortunately, the delay between company performance and quarterly earnings can dampen the usefulness of these reports for real-time analysis. Scraping product reviews can allow investors to proactively gather information on a product life cycle and make more up to date assumptions about company earnings.

Company news

More than just the company’s communications themselves, one can scrape the web for the frequency of company mentions across social media platforms and business content providers, generating extremely useful data on a company’s trajectory.

Sophisticated algo traders can integrate this type of data into their processes to ensure major news events are taken into consideration when performing trades, and that’s only a taste of what’s possible when this type of data is incorporated into the machinery of investment.

Sentiment data

A while back, Bloomberg declared that access to the Twitter stream offers one of the largest and most nutritious alternative data sets for alpha-seeking investors, and new developments in behavioral economics research suggest that  “collective mood states derived from large-scale Twitter feeds” could predict Dow Jones movements with an astonishing 87.6% accuracy.

By extracting sentiment data from the web, investors can make timely, accurate decisions within the ever-hastening market.

Modern data sources span such a large variety, from those yet discussed to geolocation data, emailed receipts, and even satellite imagery to name a few. The possibilities seem endless, but sophisticated investors will achieve the best results by combining machine learning, human analytics, and large, high-quality sets of alternative data.

More and better data means your investment decision-making process produces more value, more consistently. Furthermore, adjusting to the new practices of alternative data ensures your models are in sync with the pending data-based transformation of virtually every sector of business.

Learn more about web scraping for alternate data for finance

Here at Zyte (formerly Scrapinghub), we have been in the web scraping industry for 12 years. We have helped extract web data for more than 1,000 clients ranging from Government agencies and Fortune 100 companies to early-stage startups and individuals. During this time we gained a tremendous amount of experience and expertise in web data extraction

Here are some of our best resources if you want to deepen your web scraping knowledge:

Written by Colm Kenny