| May 20, 2020
This study shows how insider transaction data can be used to generate profitable trading signals, and enhanced using a News Sentiment overlay
News about how company executives are trading their share holdings, also known as insider transactions data, can provide novel insights for investors and an information edge, according to this white paper.
When put to the test the data can lead to alpha-generation, says the research carried out by RavenPack’s Data Science team.
Their findings show a trading strategy based on insider insights delivered, “a robust global portfolio performance with little exposure to systematic risk factors,” says Peter Hafez, Chief Data Scientist at RavenPack.
The strategy achieved Annualized Returns of 8.6% and 13.9% and Information Ratios of 1.82 and 2.64 for the Mid/Large-Cap and Small-Cap strategies, respectively, based on a one-day holding period.
Overlaying daily insider value signals with RavenPack news sentiment data led to a further optimizing effect on returns.
It was found that when insiders bought in the midst of a negative news trend, for example, it could be a sign the stock price was about to turn around and recover.
This might be because, “the insider may have certain information or intuition related to a positive change in the company fundamentals, given that he/she is buying against what seems to be an overall negative environment,” speculates Hafez.
RavenPack’s insider transaction data allows users to condition insider trading signals with company news sentiment which reflects the positive or negative media attention the company has received over the trailing 3 months.
“In particular, we observe that insider buys or sells are, on average, more likely to precede large price moves when the long-term sentiment associated with the company has been negative,” says Hafez.
The strategy made use of RavenPack’s new Insider Transactions Dataset, which enables greater classification and categorization of the different types of insider data dependent on size and type, and, therefore, the gauging of likely impact and relevance.
“In this study, we showcased the value contained within the RavenPack Insider Transactions data and demonstrated a global strategy that delivers idiosyncratic alpha,” says Peter Hafez.
When decomposed from other possible market factors the insider signal remained significant.
“We also showed that the performance is not attributable to traditional factors within the MSCI Barra GEM 3 model; hence the Net Insider Value is a valuable source of alpha,” adds Hafez.
Easily implement the results of this White Paper using the RavenPack Analytics Platform, which includes a comprehensive and high-quality database of global insider transactions. Request a trial today.
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