Investing today is inseparable from big data. Algorithmic investment models increasingly rely on multiple alternative data sources, which help investors gain a competitive advantage and make data-backed investment decisions. With hundreds of unique data points, our public resume and firmographic datasets bring immense value to hedge funds, VCs, and other financial firms, enhancing their investment intelligence.
Coresignal’s datasets help companies train algorithms and operate intelligent solutions that track significant market events based on predetermined criteria and automatically provide signals. These actionable, data-based insights ensure that valuable opportunities will not be missed.
People and company data is also used as an additional, alternative information source that helps both investment consulting and financial firms to enhance trading and investment decisions for a variety of users.
Financial institutions also use our datasets as an alternative data source to extract strategic or operational insights. This information enables them to understand the business environment of specific companies better or have a strategically useful overview of the general state of various industries.
For both pre and post-investment analysis, Coresignal’s rich alternative data helps hedge funds and VCs gain strategic business insights, enhance their decision making process, and maintain algorithms that signal investment opportunities.
Our in-depth firmographic, company employee review, and company funding data makes it possible to gain unprecedented insights by monitoring business strategy, predicting next steps, tracking companies and their performance.
Aside from the already mentioned use cases, investors also use our main public resume and firmographic datasets to:
These are just some of the many ways to use our datasets. If you would like a free consultation on whether our data is right for you, feel free to schedule a consultation and we will be happy to answer all of your questions.
Investment intelligence is the identification and evaluation of a particular organization’s investment insights gathered from alternative data sources.
Coresignal offers rich alternative data from 20 unique data sources spanning 8 categories.
Investment intelligence can be measured with a variety of metrics including, but not limited to, ROI, price-to-earnings ratio, and debt-to-equity ratio.
Many hedge funds conduct quantitative research with a team of analysts. These analysts are responsible for tracking patterns, risks, losses, trends, and more in order to help develop successful trading strategies that are executed by a portfolio manager.
Hedge funds utilize AI-based technology to analyze current data and to help predict future market and industry trends. Hedge funds also leverage machine learning and deep learning (a subset of machine learning) to help recognize patterns and extract valuable insights from alternative data.
Hedge funds are able to use NLP, also known as natural language processing, for various reasons. Primarily, hedge funds are able to leverage NLP to analyze larger text documents and files, such as press releases, filings, and call transcripts, for risk management, investment intelligence, and sentiment analysis.