Long-Run Risk is the Worst-Case Scenario: Ambiguity Aversion and Non-Parametric Estimation of the Endowment Process
We study an agent who is unsure of the dynamics of consumption growth. She estimates her consumption process non-parametrically to place minimal restrictions on dynamics. We analytically show that the worst-case model that she uses for pricing, given a penalty on deviations from the point estimate, is a model with long-run risks. This result cannot in general be matched in a fixed model with only parameter uncertainty. With a single parameter determining risk preferences, the model generates high and volatile risk premia and matches R2s from return forecasting regressions, even though risk ...
Stress Testing with Misspecified Models
Stress testing has become an important component of macroprudential regulation yet its goals and implementation are still being debated, reflecting the difficulty of designing such frameworks in the context of enormous model uncertainty. We illustrate methods for responding to possible misspecifications in models used for assessing bank vulnerabilities. We show how ?exponential tilting? allows the incorporation of external judgment, captured in moment conditions, into a forecasting model as a partial correction for misspecification. We also make use of methods from robust control to seek the ...
Doubts and Variability: A Robust Perspective on Exotic Consumption Series
In order for consumption based asset pricing models to reconcile data on returns with that on consumption, researchers have resorted to augmenting the consumption series in exotic ways. When an agent?s consumption series is subject to changes in volatility, we show that concerns for model misspecification can induce fears of both disasters and long run risk. We appeal to this pessimistic view to explain why introducing stochastic volatility in the presence of model uncertainty helps generate a more plausible unconditional market price of risk and time variation in the conditional market price ...
What determines the frequency domain properties of a stochastic process? How much risk comes from high frequencies, business cycle frequencies or low frequency swings? If these properties are under the influence of an agent, who is compensated by a principal according to the distribution of risk across frequencies, then the nature of this contracting problem will affect the spectral properties of the endogenous outcome. We imagine two thought experiments: in the first, the principal (or ?regulator?) is myopic with regard to certain frequencies?he is characterized by a filter?and the agent ...
Robust stress testing
In recent years, stress testing has become an important component of financial and macro-prudential regulation. Despite the general consensus that such testing has been useful in many dimensions, the techniques of stress testing are still being honed and debated. This paper contributes to this debate in proposing the use of robust forecasting analysis to identify and construct adverse scenarios that are naturally interpretable as stress tests. These scenarios emerge from a particular pessimistic twist to a benchmark forecasting model, referred to as a ?worst case distribution?. This offers ...
De-leveraging or de-risking? How banks cope with loss
Using detailed bank balance sheet data obtained under the United States? stress testing programs we examine how a shock to banks? net worth affects their portfolio decisions. We focus on the supply of credit (the bank lending channel) and the ultimate effect on borrowers (the credit channel), but also examine how the shock affects banks? overall risk profile and security holdings. Our shock is derived from variation across banks in their loan exposure to industries adversely affected by the precipitous oil price declines of 2014. For corporate lending, we find significant evidence of a bank ...
Worst-case scenarios and asset prices
Investors have a hard time accounting for uncertainty when calculating how much risk they are willing to bear. They can use economic models to project future earnings, but many models are misspecified along important dimensions. One method investors appear to use to protect against particularly damaging errors in their model is by projecting worst-case scenarios. The responses to such pessimistic predictions provide insights that can explain many of the puzzles about asset prices.
Are wages useful in forecasting price inflation?
Labor costs constitute a substantial share of business expenses, and it is natural to expect wages to be an important determinant of prices. However, research suggests that wages do not contain much useful information for forecasting price inflation that is not available from other indicators. Therefore, one should not infer too much from recent wage data regarding the future path of inflation.
Trend Job Growth: Where's Normal?
With the U.S. labor market at or near maximum employment, assessing trend job growth has become increasingly important. This ?breakeven? rate, which is the pace of job growth needed to maintain a healthy labor market, depends primarily on growth in the labor force. Estimates that account for population aging and potential labor force participation trends suggest that trend growth ranges between about 50,000 and 110,000 jobs per month. Actual job growth has been well above this pace, implying that it can slow substantially in the future without undermining labor market health.
How Do Banks Cope with Loss?
When lenders experience unexpected losses, the supply of credit to borrowers can be disrupted. Researchers and policymakers have long sought estimates of how the availability of loans changes following a shock. The sudden oil price decline in 2014 offers an opportunity to observe precisely how affected lenders altered their portfolios. Banks that were involved with oil and gas producers cut back on some types of lending?consistent with traditional views of bank behavior. However, they expanded other types of lending and asset holdings with a bias towards less risky securities.