PodcastOdd LotsCarolin Pflueger

Why Treasuries Became Risky Again

The discussion links financial-market strength to geopolitical influence and examines how expectations about Fed policy shape yields. It traces the changing risks of Treasuries, from inflation-driven losses in earlier decades to their post-2000 role as a stock hedge, and considers how rising bond-stock correlation has weakened that protection. The guest argues that policy credibility and the perceived safety of Treasuries are important to bond pricing, while hosts also discuss US-China yield differences and the cost of US industrialization.

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Key Takeaways

The guest links military strength to financial advantages, pointing to Britain’s deep bond market and low borrowing rates before the Napoleonic Wars and the US’s similar position in the second half of the twentieth century. She says strong borrowing capacity can reinforce itself when lower perceived risk reduces financing costs and supports investment, while a shift in hegemony through market pricing rather than war remains hypothetical.

The guest describes a forward-looking policy reaction function that connects expected inflation to policy-rate forecasts—for example, 2% expected inflation with a 4% rate forecast, or 4% inflation with a 6% rate forecast. Her team estimated the perceived rule using forecasts from 30 to 50 Blue Chip forecasters, and she says market reactions can also be estimated by relating yield changes to inflation news; the Fed’s late-2011 guidance illustrates how rate forecasts can converge.

The guest says forecasters expected rates to remain near zero even with inflation at 6% in 2021, and that a May 2021 inflation surprise of almost half a percentage point did not move the two-year rate when forecasts were clustered near zero. She says the perceived inflation response rose from zero to one between early 2022 and late 2023, after the Fed began acting.

The guest says the perceived policy response to output tends to steepen during tightening cycles, when central bank chairs emphasize data dependence, and flatten during often-sudden easing cycles. She argues that pricing a more gradual policy approach can help keep bonds bond-like and, if a soft landing is priced in, may mean stocks need not fall alongside bonds; both depend on confidence in central-bank action.

The guest contrasts the inflation-driven bond risks of the 1970s through 1990s—including stagflation that could hurt both stocks and nominal bonds—with post-2000 demand-driven recessions that tended to involve lower inflation. She says a return to 1980s-style risky bond markets would require inflationary shocks, such as oil-price shocks or lost fiscal credibility, combined with a Fed willing or forced to accept a recession; she characterizes 2021–2022 as combining supply shocks with more inertial monetary policy.

GEO-POLITICS

Financial Power — The guest links military strength to financial advantages, citing the UK’s deep bond market and low borrowing rates before the Napoleonic Wars. She argues that military and financial advantages are interlinked, and says the US held a similar position in the second half of the twentieth century.

“A famous example or maybe the most famous example of this would also be The UK…”—

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TECHNOLOGY

E-Rickshaw Network — India’s e-rickshaws are often built in sheds, garages, and makeshift workshops rather than large factories. This supports a micro-economy of parts sellers across cities.

“More and more of them have electric motors easing life for drivers the prevalence of these vehicles makes India's transition to EVs unlike that of most other places the e…”—

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ECONOMY

Yields After Hikes — A host observes that Treasury yields continued to rise after a Fed rate hike, leaving open whether the hike was having its intended effect of dampening financial conditions.

“And the other thing that happened since Jackson Hole is we had a Fed rate hike. We had Fed rate. Yeah. And yet yields continue to soar…”—

Forward-Looking Policy — The guest describes a forward-looking policy reaction function, similar to but distinct from a traditional Taylor rule. It focuses on expectations over the next few quarters or, at most, the next couple of years. In her example, a 2% inflation expectation corresponds to a 4% policy-rate forecast, while 4% inflation corresponds to 6%. When the reaction function is understood, incoming data can help move policy rates in the Fed’s intended direction.

“So as a numerical example, if forecasters expect 2% inflation, they might forecast a 4% policy rate. If they expect 4% inflation, they might expect a 6% policy rate…”—

Estimating Policy Rules — The guest says her team estimated the perceived policy rule using Blue Chip forecasters’ Fed funds rate forecasts and their inflation and output assumptions. The data covered 30 to 50 forecasters and forecast horizons of up to six quarters.

“And so we use this data from the blue chip of financial forecasters, asks, which what is your forecast for the Fed funds rate?…”—

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MARKETS

30-Year Yield High — A host says the 30-year rate had risen for several weeks to 5.592%, its highest level since 2002.

“Oh my gosh. The thirty year rate, by the way Yeah. So it's it's just straight up the last few weeks. But it…”—

Inflation Surprise — The guest says a May 2021 inflation surprise of almost half a percentage point, described as a 6% annualized surprise component, did not move the two-year rate. Forecasts were clustered near zero.

“And you saw that, for example, in May 2021. That was a particularly positive inflation surprise. That was an inflation surprise of almost half a percent…”—

Historical Bond Risk — The guest says Treasury bonds were viewed as risky during the 1970s, 1980s, and 1990s, when inflation risk premiums were prominent. Stagflation could hurt both nominal bonds and stocks, while post-2000 demand-driven recessions tended to involve lower inflation.

“So there were periods, especially during the seventies, eighties and nineties, when Treasury bonds were viewed as quite risky…”—

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Important Disclaimers

Not Investment Advice: For education only — not financial, tax or legal advice.

AI-Generated: Made by AI from source transcripts and may contain errors.

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