About a-team Marketing Services
The knowledge platform for the financial technology industry

A-Team Insight Blogs

S&P Valuation and Risk Strategies Develops New Benchmark Scoring Methodology to Evaluate Corporate Bonds

Subscribe to our newsletter

S&P Valuation and Risk Strategies, an independent and analytically separate business unit within Standard & Poor’s that provides users with market intelligence and analytic insight for risk driven investment analysis, announced the launch of a new evaluation benchmark on S&P’s Global Credit Portal investor analytics platform. The new Risk-to-Price scoring methodology is intended to help corporate bond investors determine how well they are being compensated, through yield, for the risks they are taking.

Risk-to-Price incorporates cross-asset aspects of a corporate bond into ranking securities on a relative basis, intending to capture both credit and market risk. The Risk-to-Price methodology models the behaviour of option-adjusted spreads in conjunction with the probability of default and the volatility of the bond. The result is a unique, cross-asset analytic for corporate bonds. The higher the Risk-to-Price score, the better the securities are projected to compensate their owners relative to underlying market and credit risks.

This scoring system allows the Risk-to-Price universe of corporate bonds to be segmented into quartiles by region, with the higher scores designated “Quartile 1” and the lowest scores designated “Quartile 4.” Debt issues scored in Quartile 1 are projected to offer investors the best yield for the amount of default and market risk they are taking. The offering scores approximately 6,000 U.S. and European debt issues. In addition to the daily scores, commentary is published as the R2P team observes anomalies across the corporate credit space, to give perspective on these securities.

“The Risk-to-Price score allows fixed income investors to gain a more granular perspective than ever before on how well they are being compensated for the risks they are exposed to in their portfolios,” said Michael Thompson, managing director, S&P Valuation and Risk Strategies. “We developed the methodology in direct response to the credit crisis to give investors a common vocabulary for communicating and understanding market and credit risk components of their holdings; we believe it will soon become a standard benchmark in the credit evaluation process.”

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: Building a Semantic Layer for Your Enterprise Data Estate

The democratisation of data has encouraged engineers to think about how to make their data estates more accessible and useable for non-technical business end-users. Translating intention into data action requires careful configuration that enables consumers to mine insight, analytics and value without having to use precise technical terminology. Data engineers achieve this through semantic layers,...

BLOG

BBH Subsidiary Braid Seeks to Fill Data Transformation Hole for Financial Institutions

As data is distributed throughout an enterprise, it has to be integrated with a variety of technologies in order to bring efficiencies to different workflows. This can create a lot of manual overhead, particularly in organisations with fragmented legacy tech systems. While bolt-on point solutions exist, they tend to be custom-built for particular use cases...

EVENT

TradingTech Summit London

Now in its 16th year, the TradingTech Summit London brings together senior leadership across capital markets trading technology and market data. Join us to deep dive into key opportunities and challenges driving technological transformation across sell-side and buy-side firms.

GUIDE

AI in Capital Markets Handbook 2026

AI adoption in capital markets has moved into a more disciplined phase. The priority is now controlled deployment: where AI can be used safely, where it can deliver measurable value, and how outputs can be governed, monitored and evidenced. The 2026 edition of the AI in Capital Markets Handbook examines how AI is being applied...