New research leverages News-Driven Insights for Credit Analysis

April 5, 2024

The research incorporates news insights on 120 credit-related events, proving effective in both short and longer-term investment strategies.

RavenPack Credit News signals allow investors to draw insights from news articles related to over 120 credit-related events. The signals will soon be available as pre-built factors, while also allowing for customization to suit individual investment strategies.

The research involved credit event studies and portfolio construction across various trading scenarios. Backtesting results demonstrate the framework's versatility and effectiveness in capturing alpha:

  • Broad Alpha Generation: The signals capture alpha across various credit universes (U.S. Investment-Grade & High-Yield). They analyze events like analyst ratings, credit rating changes, earnings announcements, price targets, and stock price movements. This effectiveness applies to holding periods ranging from daily to monthly, while accounting for bond characteristics.

  • Strong Risk-Adjusted Returns: When used to trade on news around analyst rating changes, the approach achieves Information Ratios of 0.8 and 1.1 for U.S. investment-grade and high-yield universes, respectively. This holds true for a holding period of about one week with a sizable portfolio.

  • Complementary Alpha Sources: Different event types can generate uncorrelated alpha. The framework allows investors to combine these individual signals for a more comprehensive approach.

Figure. Total returns include transaction price per unit of value, accrued interest, and coupon paid, with excess return compare with a benchmark composed of bonds with similar characteristics of maturity, credit rating, and liquidity.

The research will soon be available as a family of factors, offering even more flexibility and customization for credit investment strategies.



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Credit News Insights

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RavenPack Credit News signal provide easy access to news-based insights on 120+ credit events.