Limits of Inferring Hyperinflation Risk from Sovereign Default Markets
Summary
The document explores whether sovereign default probabilities, potentially inferred from credit default swap prices, can help estimate a country's probability of hyperinflation. Its central response is that markets in countries with substantial hyperinflation risk may be too shallow to provide reliable, direct signals. For Argentina, it notes the absence of local-currency inflation swaps and peso-denominated bonds, while dollar-settled CDS would not directly reflect peso inflation.
Currency forwards might offer indirect evidence if inflation pressure drove the currency sharply lower, but restricted exchange-rate markets can make observed prices unrepresentative; access to unofficial forward rates would be a limitation. Even market-implied risk-neutral probabilities would need conversion before being treated as real-world probabilities. The document mentions Cagan's work on monetary dynamics and a proposed simulator, but gives no validated model, dataset, or empirical estimates. It therefore identifies data and interpretation hurdles rather than a ready conversion function.
Key ideas
- Dollar-settled sovereign CDS may not directly reveal local-currency hyperinflation risk.
- Thin markets can limit the availability and reliability of inflation-linked instruments and local-currency bonds.
- Currency forwards may provide indirect signals, but controls can make quoted rates unrepresentative.
- Market-implied risk-neutral probabilities require adjustment before interpretation as real-world probabilities.
- The document points to monetary research and simulation as possible directions but provides no validated estimator.
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Full text
# Probability of Hyperinflation as a function of Probability of Soverign Default # Probability of Hyperinflation as a function of Probability of Soverign Default I'm looking for some academic research on modeling risk of hyperinflation. Specifically, I'm interested in modeling the probability of hyperinflation over some time interval (e.g., probability of hyperinflation in Argentina within the next year). I'm familiar with numerous macroeconomic models which are related to inflation, but I'm looking for something a bit different. Clearly sovereign default hyperinflation are related, but I'd like to estimate some function to convert between the two. For example, we can infer probability of default from CDS rates. Then, I'd like to use that to determine probability of hyperinflation. Are there any problems with attempting to approach this problem using this method? Any references or guidance would be appreciated. FWIW, my technical background in mathematics, stats, finance is relatively advanced. i.e., don't be discouraged from sharing any references using stochastic calculus, vector autoregression, etc. Thanks! ## Answer by Kiwiakos (score 2, accepted) https://quant.stackexchange.com/a/14197 I think the problem is that, for countries with a sizeable risk of hyperinflation, you will not have deep and mature markets to extract market expectations from. Argentina is a good example. Hyperinflation is just 'very big inflation', but you don't have inflation swaps in ARS. The CDS that you mention will pay in USD, and are therefore immune to ARS inflation. There are no quanto CDS on Argentina, as far as I know. You might want to extract information synthetically using bonds, but all Argentinean bonds are in USD, nobody wants Peso-denominated bonds. Perhaps you can look at the FX forward curve, as hyperinflation would cause ARS to collapse, but the market is not free-floating. Unless you have access to black market forward rates. And even if you did, then you have to convert the risk neutral probabilities into actual ones. Edit: There is academic research on the monetary aspects of hyperinflation, for example Cagan's 1956 paper in Milton Friedman's book. More refernces on Cagan's wiki page. ## Answer by Vincent Cate (score 1) https://quant.stackexchange.com/a/14201 I wrote a hyperinflation simulator. With enough data and enough work I think it would be possible to tune the constants so that it did a reasonable job of matching real world hyperinflation evolution. With that you could then predict which countries were most at risk. http://howfiatdies.blogspot.com/2013/03/simulating-hyperinflation.html
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