This article was written by Jerome Barkate, Nakul Nair, Zane Van Dusen, and Scott Coulter.
We are witnessing a remarkable period in the credit markets. Following years of accommodative monetary policies, central banks across the globe are raising interest rates at record pace to address surging inflation concerns. As a result, credit spreads are widening, refinancing costs are soaring, and the banking sector has experienced significant turmoil with major failures and collapses, intensifying counterparty risk concerns.
These factors have amplified the importance of a proactive credit risk management strategy built on a foundation of reliable data and robust credit risk models. Credit risk analysis is a critical undertaking for financial institutions and investors alike so they can evaluate the probability of default, assess potential losses, and pivot as needed.
Different perspectives: DRSK & MIPD
To facilitate proactive credit risk management, Bloomberg offers two distinct methodologies for calculating default probabilities.
The first is Bloomberg’s Market Implied Probability of Default (MIPD) product. MIPD utilizes a transparent data driven methodology to transform the high-quality fixed income pricing data from Bloomberg’s evaluated pricing service (BVAL) into credit metrics, including default probabilities and implied credit default swap (CDS) spreads. These metrics offer a daily snapshot of the market sentiment for an issuer’s creditworthiness and can quickly capture the impact of issuer-specific news and broader market events for the 36,000+ companies and sovereigns globally that issue bonds.
MIPD’s credit metrics are closely aligned to signals found in news data and often provide leading indicators ahead of a major news event. This is driven by the fact that most company news is not significant enough to generate many headlines until an event is so severe that news organizations believe it will appeal to a broader audience. Meanwhile, bond market investors who closely follow a specific list of names are pricing in risks as soon as they emerge but are not incentivized to overreact. By capturing bond investors’ pricing behaviour, MIPD is an appealing alternative to news sentiment data and can illuminate potential major credit events ahead mass-market awareness.
The second methodology is Bloomberg’s Company Default Risk (DRSK) model. DRSK takes a hybrid approach by incorporating both market and scrubbed fundamentals inputs. This model combines the timeliness of a market-derived model with the coverage of a fundamentals-based approach. Consequently, DRSK provides a more stable assessment of risk especially during periods of extreme market volatility and presents an alternative to traditional methods by incorporating both perspectives in its methodology. DRSK’s hybrid methodology combined with Bloomberg’s vast database of company fundamentals and equity market data enables the model to provide credit risk data for over 87,000+ public companies and 433,000+ private companies.
Essentially, DRSK offers a risk profile driven by both equity market dynamics and fundamentals, whereas MIPD provides a primarily bond market-driven outlook.
A holistic approach to credit risk management
In today’s challenging credit risk environment, we repeatedly hear from clients that the more credit risk data and the greater number of perspectives on an entity’s credit risk, the better.
In most cases, DRSK and MIPD data is used in combination with other credit measures like CDS spreads, internal models, traditional credit ratings, and even ESG factors. This allows risk managers to paint a more comprehensive, holistic picture of the credit profile of the issuers they need to monitor.
For example, the scorecard below combines DRSK and MIPD credit metrics along with equity volatility, ESG scores, and fundamental inputs. By normalizing different risk measures and weighting them, we can obtain an overall risk score of an issuer that goes beyond classic default risk. Weights used below are provided as an illustration, investors can customize as needed.
Go beyond managing risk, identify potential alpha
DRSK and MIPD data can be useful beyond managing risk, they can also identify potential investment opportunities through the mispricing of risk. By combining these two measures, investors can identify discrepancies between the market’s perception of an issuer’s credit risk and its fundamental financial health.
For example, when Credit Suisse was swiftly acquired by UBS, their Additional Tier 1 (AT1) bonds experienced extreme price dislocation. These bonds, born in the aftermath of the Great Financial Crisis, are subordinated to other debts but viewed as senior to equity. This conventional wisdom was turned on its head in March when the Swiss regulator triggered a write down of these bonds while still allowing equity holders to recoup some of their investment.
This sent shockwaves through the European AT1 bond market. Yields on these bonds skyrocketed and pundits prophesized the downfall of the asset class. In the illustration below, we show how MIPD and DRSK can be used together to identify risks and opportunities in the AT1 issuers space in the aftermath of these events.
By comparing the MIPD probability of default to the more fundamental-driven DRSK number, we get an indication of over or underpricing of credit risk. The banks with low DRSK probability of defaults (PDs) and high MIPD PDs (shown in the blue dotted box) are worth exploring as investment opportunities. These bonds are trading a large spread to the risk free rate (as implied by the high MIPD PDs) despite having rather solid fundamentals (as evidenced by the DRSK PDs). The data implies that the market is overpricing their credit risk.
Conversely, for those banks with high DRSK PDs and low MIPD PDs (in the orange dotted box), the market is underpricing the risk implied by their fundamentals. Therefore, these present poorer compensation for their level of risk and should be avoided.
Two is better than one
Analyzing credit risk by combining market-driven and fundamental data can provide a more comprehensive and effective way for managing credit risk. By using both measures, investors and financial institutions can gain valuable insights into an issuer’s creditworthiness and make more informed investment decisions.
Find out more
MIPD is a premium Enterprise Data solution that is available to Bloomberg Data License clients, as well as on the Bloomberg Terminal through a new dedicated screen accessed via MIPD<GO>, W<GO> and via the Excel API. The solution includes implied probability of default for over 36,000 issuers and multiple sectors across the term structure from 1 to 20 years.
Bloomberg’s DRSK models (DRSK <GO>) use scrubbed fundamental data and cutting-edge quantitative models to provide transparent and timely quantitative estimates of an issuer’s default probabilities, default risk and 5-year CDS spread. Bloomberg Data License and MARS Credit Risk allows you to leverage the high-quality data provided by the Bloomberg Professional® service, but in your enterprise applications.
Bloomberg
Source link
