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Working Paper
Financial and Macroeconomic Data Through the Lens of a Nonlinear Dynamic Factor Model
Through the lens of a nonlinear dynamic factor model, we study the role of exogenous shocks and internal propagation forces in driving the fluctuations of macroeconomic and financial data. The proposed model 1) allows for nonlinear dynamics in the state and measurement equations; 2) can generate asymmetric, state-dependent, and size-dependent responses of observables to shocks; and 3) can produce time-varying volatility and asymmetric tail risks in predictive distributions. We find evidence in favor of nonlinear dynamics in two important U.S. applications. The first uses interest rate data to ...
Working Paper
Macroeconomic and Financial Risks: A Tale of Mean and Volatility
We study the joint conditional distribution of GDP growth and corporate credit spreads using a stochastic volatility VAR. Our estimates display significant cyclical co-movement in uncertainty (the volatility implied by the conditional distributions), and risk (the probability of tail events) between the two variables. We also find that the interaction between two shocks--a main business cycle shock as in Angeletos et al. (2020) and a main financial shock--is crucial to account for the variation in uncertainty and risk, especially around crises. Our results highlight the importance of using ...
Working Paper
Dynamic Factor Copula Models with Estimated Cluster Assignments
This paper proposes a dynamic multi-factor copula for use in high dimensional time series applications. A novel feature of our model is that the assignment of individual variables to groups is estimated from the data, rather than being pre-assigned using SIC industry codes, market capitalization ranks, or other ad hoc methods. We adapt the k-means clustering algorithm for use in our application and show that it has excellent finite-sample properties. Applying the new model to returns on 110 US equities, we find around 20 clusters to be optimal. In out-of-sample forecasts, we find that a model ...
Working Paper
Financial and Macroeconomic Data Through the Lens of a Nonlinear Dynamic Factor Model
Through the lens of a nonlinear dynamic factor model, we study the role of exogenous shocks and internal propagation forces in driving the fluctuations of macroeconomic and financial data. The proposed model 1) allows for nonlinear dynamics in the state and measurement equations; 2) can generate asymmetric, state-dependent, and size-dependent responses of observables to shocks; and 3) can produce time-varying volatility and asymmetric tail risks in predictive distributions. We find evidence in favor of nonlinear dynamics in two important U.S. applications. The first uses interest rate data to ...
Working Paper
Are the Largest Banking Organizations Operationally More Risky?
This study demonstrates that, among large U.S. bank holding companies (BHCs), the largest ones are exposed to more operational risk. Specifically, they have higher operational losses per dollar of total assets, a result largely driven by the BHCs' failure to meet professional obligations to clients and/or faulty product design. Operational risk at the largest U.S. institutions is also found to: (i) be particularly persistent, (ii) have a counter-cyclical component (higher losses occur during economic downturns) and (iii) materialize through more frequent tail-risk events. We illustrate two ...
Working Paper
Capital Flows in Risky Times: Risk-On / Risk-Off and Emerging Market Tail Risk
This paper characterizes the implications of risk-on/risk-off shocks for emerging market capital flows and returns. We document that these shocks have important implications not only for the median of emerging markets flows and returns but also for the left tail. Further, while there are some differences in the effects across bond vs. equity markets and flows vs. asset returns, the effects associated with the worst realizations are generally larger than on the median realization. We apply our methodology to the COVID-19 shock to examine the pattern of flow and return realizations: the sizable ...
Report
Asset Pricing with Endogenously Uninsurable Tail Risk
This paper studies asset pricing in a setting in which idiosyncratic risk in human capital is not fully insurable. Firms use long-term contracts to provide insurance to workers, but neither side can commit to these contracts; furthermore, worker-firm relationships have endogenous durations owing to costly and unobservable effort. Uninsured tail risk in labor earnings arises as a part of an optimal risk-sharing scheme. In the general equilibrium, exposure to the resulting tail risk generates higher risk premia, more volatile returns, and variations in expected returns across firms. Model ...