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Working Paper
Time-varying Volatility and the Power Law Distribution of Stock Returns
While many studies find that the tail distribution of high frequency stock returns follow a power law, there are only a few explanations for this finding. This study presents evidence that time-varying volatility can account for the power law property of high frequency stock returns. The power law coefficients obtained by estimating a conditional normal model with nonparametric volatility show a striking correspondence to the power law coefficients estimated from returns data for stocks in the Dow Jones index. A cross-sectional regression of the data coefficients on the model-implied ...
Report
Time-Varying Structural Vector Autoregressions and Monetary Policy: a Corrigendum
This note corrects a mistake in the estimation algorithm of the time-varying structural vector autoregression model of Primiceri (2005) and shows how to correctly apply the procedure of Kim, Shephard, and Chib (1998) to the estimation of VAR, DSGE, factor, and unobserved components models with stochastic volatility. Relative to Primiceri (2005), the main difference in the new algorithm is the ordering of the various Markov Chain Monte Carlo steps, with each individual step remaining the same.
Working Paper
Precautionary Volatility and Asset Prices
Many theories of asset prices assume time-varying uncertainty in order to generate time-varying risk premia. This paper generates time-varying uncertainty endogenously, through precautionary saving dynamics. Precautionary motives prescribe that, in bad times, next period's consumption should be very sensitive to news. This time-varying sensitivity results in time-varying consumption volatility. Production makes this channel visible, and external habit preferences amplify it. An estimated model featuring this channel quantitatively accounts for excess return and dividend predictability ...
Report
Measuring the Natural Rate of Interest after COVID-19
We modify the Laubach-Williams and Holston-Laubach-Williams models of the natural rate of interest to account for time-varying volatility and a persistent COVID supply shock during the pandemic. Resulting estimates of the natural rate of interest in the United States, Canada, and the Euro Area at the end of 2022 are close to their respective levels estimated directly before the pandemic; that is, we do not find evidence that the era of historically low estimated natural rates of interest has ended. In contrast, estimates of the natural rate of output have declined relative to those projected ...
Report
Announcement-Specific Decompositions of Unconventional Monetary Policy Shocks and Their Macroeconomic Effects
I propose to identify announcement-specific decompositions of asset price changes into monetary policy shocks exploiting heteroskedasticity in intraday data. This approach accommodates both changes in the nature of shocks and the state of the economy across announcements, allowing me to explicitly compare shocks across announcements. I compute decompositions with respect to Fed Funds, forward guidance, asset purchase, and Fed information shocks for 2007-19. Only a handful of announcements spark significant shocks. Both forward guidance and asset purchase shocks lower corporate yields and ...
Working Paper
Managing Capital Flows in the Presence of External Risks
We introduce external risks, in the form of shocks to the level and volatility of world interest rates, into a small open economy model subject to the risk of sudden stops?large recessions together with abrupt reversals in capital inflows| and characterize optimal macroprudential policy in response to these shocks. In the model, collateral constraints create a pecuniary externality that leads to "overborrowing" and sudden stops that arise when the constraints bind. The typical sudden stop generated by the model replicates existing empirical evidence for emerging market economies: Low and ...
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Identifying shocks via time-varying volatility
An n-variable structural vector auto-regression (SVAR) can be identified (up to shock order) from the evolution of the residual covariance across time if the structural shocks exhibit heteroskedasticity (Rigobon (2003), Sentana and Fiorentini (2001)). However, the path of residual covariances can only be recovered from the data under specific parametric assumptions on the variance process. I propose a new identification argument that identifies the SVAR up to shock orderings using the autocovariance structure of second moments of the residuals, implied by an arbitrary stochastic process for ...