What Do Financial Conditions Tell Us about Risks to GDP Growth?
The economic fallout from the COVID-19 pandemic has been sharp. Real U.S. GDP growth in the first quarter of 2020 (advance estimate) was -4.8 percent at an annual rate, the worst since the global financial crisis in 2008. Most forecasters predict much weaker growth in the second quarter, ranging widely from an annual rate of -15 percent to -50 percent as the economy pauses to allow for social distancing. Although growth is expected to begin its rebound in the third quarter absent a second wave of the pandemic, the speed of the recovery is highly uncertain. In this post, we estimate the risks ...
Simple and reliable way to compute option-based risk-neutral distributions
This paper describes a method for computing risk-neutral density functions based on the option-implied volatility smile. Its aim is to reduce complexity and provide cookbook-style guidance through the estimation process. The technique is robust and avoids violations of option no-arbitrage restrictions that can lead to negative probabilities and other implausible results. I give examples for equities, foreign exchange, and long-term interest rates.
Assessing financial stability: the Capital and Loss Assessment under Stress Scenarios (CLASS) model
The CLASS model is a top-down capital stress testing framework that uses public data, simple econometric models, and auxiliary assumptions to project the effect of macroeconomic scenarios on U.S. banking firms. Through the lens of the model, we find that the total banking system capital shortfall under stressful macroeconomic conditions began to rise four years before the financial crisis, peaking in the fourth quarter of 2008. The capital gap has since fallen sharply, and is now significantly below pre-crisis levels. In the cross section, banking firms estimated to be most sensitive to ...
Changing risk-return profiles
We show that realized volatility, especially the realized volatility of financial sector stock returns, has strong predictive content for the future distribution of market returns. This is a robust feature of the last century of U.S. data and, most importantly, can be exploited in real time. Current realized volatility has the most information content on the uncertainty of future returns, whereas it has only limited content about the location of the future return distribution. When volatility is low, the predicted distribution of returns is less dispersed and probabilistic forecasts are ...
The equity risk premium: a review of models
We estimate the equity risk premium (ERP) by combining information from twenty models. The ERP in 2012 and 2013 reached heightened levels?of around 12 percent?not seen since the 1970s. We conclude that the high ERP was caused by unusually low Treasury yields.
Option-implied term structures
This paper proposes a nonparametric sieve regression framework for pricing the term structure of option spanning portfolios. The framework delivers closed-form, nonparametric option pricing and hedging formulas through basis function expansions that grow with the sample size. Novel confidence intervals quantify term structure estimation uncertainty. The framework is applied to estimating the term structure of variance risk premia and finds that a short-run component dominates market excess return predictability. This finding is inconsistent with existing asset pricing models that seek to ...
Risk-neutral systemic risk indicators
This paper describes a set of indicators of systemic risk computed from current market prices of equity and equity index options. It displays results from a prototype version, computed daily from January 2006 to January 2013. The indicators represent a systemic risk event as the realization of an extreme loss on a portfolio of large-intermediary equities. The technique for computing them combines risk-neutral return distributions with implied return correlations drawn from option prices, tying together the single-firm return distributions via a copula to simulate the joint distribution and ...
Intraday market making with overnight inventory costs
The U.S. Treasury market is highly intermediated by nonbank principal trading ﬁrms (PTFs). Limited capital forces PTFs to end the trading day roughly ﬂat. We construct a continuous time market making model to analyze the trade-oﬀ faced by a proﬁt-maximizing ﬁrm with overnight inventory costs, and develop closed-form representations of the optimal price policy functions. Our model reveals that bid-ask spreads widen as the end of the trading day approaches, and that increases in order arrival rates do not always lead to higher price volatility. Our empirical analysis shows that ...
Variable Annuities: Underlying Risks and Sensitivities
This paper presents a quantitative model designed to understand the sensitivity of variable annuity (VA) contracts to market and actuarial assumptions and how these sensitivities make them a potentially important source of risk to insurance companies during times of stress. VA contracts often include long dated guarantees of market performance that expose the insurer to multiple nondiversifiable risks. Our modeling framework employs a Monte Carlo simulation of asset returns and policyholder behavior to derive fair prices for variable annuities in a risk neutral framework and to estimate ...
Mandatory Disclosure and Financial Contagion
This paper analyzes the welfare implications of mandatory disclosure of losses at financial institutions when it is common knowledge that some banks have incurred losses but not which ones. We develop a model that features contagion, meaning that banks not hit by shocks may still suffer losses because of their exposure to banks that are. In addition, we assume banks can profitably invest funds provided by outsiders, but will divert these funds if their equity is low. Investors thus value knowing which banks were hit by shocks to assess the equity of the banks they invest in. We find that when ...