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 ...
Global price of risk and stabilization policies
We estimate a highly significant price of risk that forecasts global stock and bond returns as a nonlinear function of the CBOE Volatility Index (VIX). We show that countries? exposure to the global price of risk is related to macroeconomic risks as measured by output, credit, and inflation volatility, the magnitude of financial crises, and stock and bond market downside risk. Higher exposure to the global price of risk corresponds to both higher output volatility and higher output growth. We document that the transmission of the global price of risk to macroeconomic outcomes is mitigated by ...
We study how the risks to future liquidity flow across corporate bond, Treasury, and stock markets. We document distribution ?flight-to-safety? effects: a deterioration in the liquidity of high-yield corporate bonds forecasts an increase in the average liquidity of Treasury securities and a decrease in uncertainty about the liquidity of investment-grade corporate bonds. While the liquidity of Treasury securities both affects and is affected by the liquidity in the other two markets, corporate bond and equity market liquidity appear to be largely divorced from each other. Finally, we show that ...
Nonlinearity and flight to safety in the risk-return trade-off for stocks and bonds
We document a highly significant, strongly nonlinear dependence of stock and bond returns on past equity market volatility as measured by the VIX. We propose a new estimator for the shape of the nonlinear forecasting relationship that exploits additional variation in the cross section of returns. The nonlinearities are mirror images for stocks and bonds, revealing flight to safety: expected returns increase for stocks when volatility increases from moderate to high levels, while they decline for Treasury securities. These findings provide support for dynamic asset pricing theories where the ...
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 ...