RavenPack Enhances Systematic Credit Investing Using 2iQ’s Insider Transaction Data
RavenPack is a leading provider of data analytics solutions to the financial industry. Leveraging nearly 20 years of research, it helps organizations generate actionable insights from unstructured data such as news, social media, earnings call transcripts, and company filings.
Recently, RavenPack used 2iQ’s insider transaction data in a research study focused on enhancing systematic credit strategies. The study involved incorporating real-time analytics from RavenPack’s Edge news, earnings call transcripts, and 2iQ’s insider transactions – which offer complementary sources of alpha – to demonstrate how the risk-adjusted performance of systematic credit investing strategies can be significantly enhanced.
Here’s a look at how RavenPack used 2iQ’s data, and the results of the research study.
Enhancing Credit Strategies with Insider Transaction Data
In its study, RavenPack used three main sentiment indicators to enhance the returns of systematic credit strategies. These were:
Earnings News. This typically conveys hard information from earnings reports that is relatively easy to interpret and consume.
Transcripts. This requires NLP-techniques to interpret sentiment and linguistic tone from earnings conference calls and better understand operational efficiency, management quality, and capital structures.
Earnings Intelligence. As an additional overlay, earnings-related information was combined with the relevant quarterly insider transaction signals, aggregated between the consecutive earnings announcements.
RavenPack used these indicators to tilt the long-only U.S. investment-grade benchmark based on senior, unsecured, and liquid bonds over 2015-2022.
Insider Transactions Lead to Outperformance
As for the results of the study, RavenPack found that, when evaluated individually, Earnings News and Transcripts demonstrated complementary performance. Earnings News strategy performed well over the short term, with annualized returns of 105 basis points in excess of the annual investment-grade benchmark for an effective holding period of two days, compared to 14 basis points for 10 days. With Transcripts, annualized excess returns were the highest at the one-week horizon (58 basis points compared to 27 basis points for News).
Notably, the combined Earnings Intelligence strategy – which used insider transaction data – outperformed the individual signals from Earnings News and Transcripts across all horizons while decaying at a slower rate than News. RavenPack found that the Earnings Intelligence strategy steadily generated benchmark-adjusted Sharpe Ratios of nearly 0.60 at the three-month effective holding period (compared to 0.40 for Earnings News), while adjusted Sharpe Ratios for Transcripts improved from 0.25 to 0.50 as the holding period increased from two weeks to three months.
In summary, RavenPack demonstrated that when combined with other sources of data, insider transaction data can be effective at enhancing systematic credit strategies. These results have meaningful implications for fixed income investors.
Those interested in finding out more about how RavenPack used 2iQ’s insider transaction data to enhance credit strategies can find additional information here.