Measuring How Politics Shapes Portfolios
The model predicts that political uncertainty reduces the potential benefits from government interventions.
Measuring How Politics Shapes PortfoliosIn US debt markets, the most common way to measure risk is by using credit spreads—the difference in yield between the benchmark 10-year Treasury note and a bond or index of similar maturity. Credit spreads change in response to shifts in the markets and the economy. In general, spreads widen when investors demand a higher yield to compensate for perceived greater risk, and narrow when perceived risk falls.
For years, researchers have grappled with what causes credit spreads to change. Johns Hopkins’s Christopher L. Culp, Yoshio Nozawa of the Federal Reserve Board, and Chicago Booth’s Pietro Veronesi have devised a way to measure and study this risk—by using made-up companies.
This approach reveals, among other things, that the primary element driving corporate spreads is a premium for tail and idiosyncratic asset risks. In other words, bond buyers are demanding moreto take risks that are rare (such as hard-to-predict ‘black swan’ events) or particular to a specific company—and bond sellers and issuers are paying that premium.
Identifying the risks that drive credit spreads presents researchers with several challenges: credit markets aren’t as transparent as public-equity markets, corporate bonds are often illiquid securities, and each corporation has its own endogenous risk that’s hard to separate from the macroeconomic risk that the researchers want to measure.
The model predicts that political uncertainty reduces the potential benefits from government interventions.
Measuring How Politics Shapes PortfoliosIf there’s one thing most Americans can probably agree on about the financial crisis that began in 2008, it’s that US credit rating agencies made a bad situation worse.
Is There a Better Way to Spot Risky Investments?To address these challenges, Culp, Nozawa, and Veronesi created a set of “pseudo firms”—fictitious companies that have entirely transparent, if made-up, balance sheets that can be monitored and studied. Theoretically, there could be an unlimited number of pseudo firms in different industries, with various mixtures of assets and liabilities, and with different amounts of leverage. The researchers track their universe of pseudo firms on the Credit Risk Laboratory, a website where they regularly update the data.
The pseudo firms can issue pseudo bonds. And while the value of pseudo bonds is driven by the same macroeconomic forces that affect the value of real bonds, researchers can use pseudo bonds to control for the quirks of the bond market and company-specific circumstances. For example, instead of looking at real corporate bonds to get a picture of credit risk—and seeing prices affected by, say, a particular company’s high leverage or recent credit downgrade—they can look to pseudo bonds, which strip away these factors.
To calculate how outside forces are affecting the fake issuers, the researchers derive the value of a pseudo bond from the value of a put option and a risk-free bond with similar characteristics. Building on an insight by MIT’s Robert C. Merton, they argue that corporate debt is basically risk-free debt minus the value of a short put option on the traded securities of pseudo firms. A put option is an option contract giving the owner the right, but not the obligation, to sell a specified amount of an underlying security at a specified price within a specified time. A short put option means, then, selling a put option and receiving the premium, which is kept if the stock rises above the designated strike price before the option expires. So a 10-year bond issued by, say, General Motors would be equivalent to a 10-year Treasury bond minus the market value of a short put option, which gives the buyer the right to sell General Motors stock.
Imagine a pseudo firm that holds a stock portfolio that is largely S&P 500 companies. “Although the pseudo firm is fictitious, we can nonetheless observe the values of its assets and debt from traded securities and thus we have a fully observable balance sheet,” the researchers write. They can use Treasury bond prices and the value of puts on the S&P Dow Jones indices to estimate the price of the pseudo bond, and they can use put options at different strike prices and expiration dates to extrapolate the impact certain external events, such as upcoming elections, could have on pseudo bonds—and by extension, real ones.
Or imagine a pseudo energy company that holds predominantly oil assets. The researchers could calculate the market value of a put option on oil futures, and then use this value and Treasury prices to back out the price of the pseudo company’s bonds.
The methodology the researchers devise allows them to make several general observations about credit spreads. They find that just like corporate spreads, pseudo-bond spreads vary with the economy, and wider spreads predict lower economic growth. But they also find that the primary factors driving credit spreads are the risk premia associated with rare negative events and those associated with particular circumstances and events at individual companies. Thus the risk of a pipeline break, for example, may be low—but that risk will have a sizeable impact on an oil company’s bond prices.
If research using 2021 and 2022 data is any indication, the odds are good.
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