Tractable Rare Disaster Probability and Options-Pricing
We derive an option-pricing formula from recursive preference and estimate rare disaster probability. The new options-pricing formula applies to far-out-of-the money put options on the stock market when disaster risk dominates, the size distribution of disasters follows a power law, and the economy has a representative agent with Epstein-Zin utility. The formula conforms with options data on the S&P 500 index from 1983-2018 and for analogous indices for other countries. The disaster probability, inferred from monthly fixed effects, is highly correlated across countries, peaks during the ...
A Life-Cycle Model with Individual Volatility Dynamics
This article solves a heterogeneous-agents, life-cycle model with idiosyncratic, time-varying volatility. Volatility is modeled based on an ARCH specification. I compare the life-cycle behavior of savings and consumption in a model with idiosyncratic volatility versus typical models with constant income risk. Idiosyncratic volatility generates a larger incentive to save precautionarily and, as a result, a lower consumption inequality.
Capital Controls and the Global Financial Cycle
Capital flows into emerging markets are volatile and associated with risks. A common prescription is to impose counter-cyclical capital controls that tighten during economic booms to mitigate future sudden-stop dynamics, but it has been challenging to document such patterns in the data. Instead, we show that emerging markets tighten their capital controls in response to volatility in international financial markets and elevated risk aversion. We develop a model in which this behavior arises from a desire to manipulate the risk premium. When investors are more risk-averse or markets are ...
Interest Rate Volatility and Sudden Stops : An Empirical Investigation
Using a multi-country regime-switching vector autoregressive (VAR) model we document the existence of two regimes in the volatility of interest rates at which emerging economies borrow from international financial markets, and study the statistical relationship of such regimes with episodes of sudden stops. Periods of high volatility tend to be persistent and are associated with high interest rates, the occurrence of sudden stops in external financing, and large declines in economic activity. Most strikingly, we show that regime switches drive the countercyclicality of interest rates in ...
Taxonomy of Global Risk, Uncertainty, and Volatility Measures
A large number of measures for monitoring risk and uncertainty surrounding macroeconomic and financial outcomes have been proposed in the literature, and these measures are frequently used by market participants, policy makers, and researchers in their analyses. However, risk and uncertainty measures differ across multiple dimensions, including the method of calculation, the underlying outcome (that is, the asset price or macroeconomic variable), and the horizon at which they are calculated. Therefore, in this paper, we review the literature on global risk, uncertainty, and volatility ...
What is Certain about Uncertainty?
Researchers, policymakers, and market participants have become increasingly focused on the effects of uncertainty and risk on financial market and economic outcomes. This paper provides a comprehensive survey of the many existing measures of risk, uncertainty, and volatility. It summarizes what these measures capture, how they are constructed, and their effects, paying particular attention to large uncertainty spikes, such as those appearing concurrently with the outbreak of COVID-19. The measures are divided into three types: (1) news-based, survey- based, and econometric; (2) asset market ...
When do low-frequency measures really measure transaction costs?
We compare popular measures of transaction costs based on daily data with their high-frequency data-based counterparts. We find that for U.S. equities and major foreign exchange rates, (i) the measures based on daily data are highly upward biased and imprecise; (ii) the bias is a function of volatility; and (iii) it is primarily volatility that drives the dynamics of these liquidity proxies both in the cross section as well as over time. We corroborate our results in carefully designed simulations and show that such distortions arise when the true transaction costs are small relative to ...
Uncertainty and Growth Disasters
This paper documents several stylized facts on the real effects of economic uncertainty. First, higher uncertainty is associated with a more dispersed and negatively skewed distribution of output growth. Second, the response of economic growth to an increase in uncertainty is highly nonlinear and asymmetric. Third, higher asset volatility magnifies the negative impact of uncertainty on growth. We develop and estimate an analytically tractable model in which rapid adoption of new technology may raise economic uncertainty which causes measured productivity to decline. The equilibrium growth ...
Price Setting and Volatility: Evidence from Oil Price Volatility Shocks
How do changes in aggregate volatility alter the impulse response of output to monetary policy? To analyze this question, I study whether individual prices in Producer Price Index micro data are more likely to change and to move in the same direction when aggregate volatility is high, which would increase aggregate price exibility and reduce the effectiveness of monetary policy. Taking advantage of plausibly exogenous oil price volatility shocks and heterogeneity in oil usage across industries, I find that price changes are more dispersed and less frequent, implying that prices are less ...
Spectral Backtests of Forecast Distributions with Application to Risk Management
We study a class of backtests for forecast distributions in which the test statistic is a spectral transformation that weights exceedance events by a function of the modeled probability level. The choice of the kernel function makes explicit the user's priorities for model performance. The class of spectral backtests includes tests of unconditional coverage and tests of conditional coverage. We show how the class embeds a wide variety of backtests in the existing literature, and propose novel variants as well. In an empirical application, we backtest forecast distributions for the overnight ...