How A.I. and Web Data Scraping Will Influence Investment Research

Feb 11, 2020

Information has always been essential to investors and investment companies. Data gives insights, helps with decision making, increases competitiveness, and reduces risk exposure.

One modern trend that is now firmly taking hold of investors is the fact that all data is useful. The question is not whether the data might be helpful or not but rather how can you collect the data and then make effective use of it.

In fact, those with the most data are often those who are making the best investments.

An important factor in this data trend is that data is so readily available. In fact, it is everywhere and covers just about every conceivable topic.

So, while the availability of data may have been challenging in the past, it is not an issue anymore. However, there are two challenges that exist:

Investors are using technologies to overcome these challenges and are having considerable success in the process.

Web Scraping and Alternative Data

There are traditional sources of data that investors have always used. Examples include earnings data and other common forms of market data. These are still important datasets for investors to collect.

A lot more data is now available to the modern investor, however. This data is known as alternative data.

Examples of alternative data include search trends, web traffic, consumer transaction data, and social media data. Web scraping is the most popular form of alternative data, however.

Web scraping involves using tools to access, read, and collect data from a range of different sources. Those sources include company websites, other websites on the internet, apps, satellite information, social media, news websites, and more.

Furthermore, web scraping tools enable investment companies to collect huge amounts of data from a vast range of sources because the process is automated. Most large investment companies then use a process called web data integration to aggregate and manage this data from multiple sources in one workflow.

Benefits of Web Scraping for Investors

Web scraping gives investors access to a wide range of information. Theoretically, anything that can be found on the internet. This data has the potential to give investors key insights on consumer behavior, market intelligence, trends, and more.

Therefore, web scraped data can be used to backup investment decisions, find new investment opportunities, determine the timing of an investment, and enhance automated trading algorithms.

Making Effective Use of Data

As mentioned above, collecting data is only one piece of the puzzle for investors. They also need tools to process, analyze and make use of the data collected. For this task, most are turning to AI – Artificial Intelligence.

In particular, investors are using specific AI technologies, namely machine learning, natural language processing (NLP), and deep learning.

These AI technologies are used to process the data collected through web scraping and by other means. Using big data technologies as well as ML and NLP, investors can quickly process massive datasets to produce usable insights.

Practical Examples

Practical examples are often the best way to demonstrate the power that AI and web scraping gives to forward-thinking investors:

  • Satellites – data from images taken by satellites can be used by data scientists and AI algorithms to predict crop yields. This assessment can then be used by investors to predict commodity prices.
  • Weather – satellite data and other sources of weather information can also be used to predict the impact of weather on commodities and other markets. Again, this information on weather can be used by investors to predict the movement of commodity prices as well as the prices of assets in other markets.
  • Web traffic – web traffic data from publicly accessible sources like Alexa can be scraped and analyzed over time to identify trends. For example, identifying an e-commerce website with increasing levels of web traffic could result in an investor deciding the performance of that company will improve. This could, in turn, contribute to a decision to make an investment.
  • Flight data – another example often quoted by companies involved in web scraping for investment purposes is the monitoring of flight data. Much of this information is publicly available. Sophisticated tools and algorithms can then be used to piece together any information that is missing. As a result, web scraping and AI tools can be used by investors to, for example, identify the owners of private jets as well as where those jets are landing and taking off from. This can provide valuable insight that can be used in the investment decision-making process.
  • Social media influence – social media can also be highly influential in relation to the movement of asset prices. This particularly applies to consumer behavior. For example, a tweet by a significant social media influencer, celebrity, or major politician that references a company, positively or negatively, can directly impact the share price of that company in the days and weeks that follow. With knowledge of these tweets and experience of how they can impact consumer attitudes, investors can then make investment decisions.
  • Social media trends – there are other ways data from social media can be valuable when making investment decisions. Social media gives information on societal and consumer trends, for example. Crucially, gathering and processing data from social media can give investors information on trends at their inception, i.e. before the trend has started to have an impact on asset prices. With this information and the capability to process and analyze it, investors can make use of this data to make predictions and, ultimately, investment decisions.
  • In-depth company information – scraping information from company websites means investment companies can process and analyze every piece of information that a company publishes, from reports to corporate communications to news articles and more. Furthermore, they can do this almost in real-time.

Tools Becoming Increasingly Sophisticated

The tools available to investment companies to gather data, particularly web scraping tools, as well as AI technologies used to process that data, are changing the investment landscape. Those that don’t invest in these technologies risk being left behind.

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