In a world of exponential data creation it’s easy to get lost in the noise. Finding clear, persistent signals indicative of future performance is paramount: understanding who the key players are and which transactions are relevant can mean the difference between portfolio performance or loss. Fundamental investing requires precision and in-depth understanding of a company’s inner workings and growth potential. Those with the deepest knowledge are often within the company: directors, managers and board members.
These individuals are closest to the action and their trading can signal trends which other analysis may not catch – but you have to know what to look for, as well as where and when. Both industry and academic research show unequivocally that the actions of company insiders provide consistent predictive power across all market conditions. The evidence is clear: if insider transactions data is not already a part of your investment process, it should be.
2iQ Research is the leading provider of global insider transactions data to the investment sector. The database history, coverage, and speed of updates are unmatched in the industry. Our control of this powerful data combined with the analytical power of our terminal product, API, and customized data feed infrastructure could transform your investment process.
We leverage over a decade of experience working with insider transaction data and some of the top quantitative managers globally to create a custom insider transactions rating model. This model ranks companies based on insider sentiment to identify the transactions and insiders with the highest predictive strength, then delivers a trading signal in the form of a score which can be used as an input to the quantitative portfolio construction process.
Click here to learn more about the 2iQ Insider Transactions Model
The most complete insider transactions historical data set in the industry, available via API, real-time, or end of day feed.
Please contact us for more detailed information regarding our methodology, historical data availability or any other questions.