Tyler Muir

Financial Crises and Risk Premia

I analyze the behavior of risk premia in financial crises, wars, and recessions in an international panel spanning over 140 years and 14 countries. I document that expected returns, or risk premia, increase substantially in financial crises, but not in the other episodes. Asset prices decline in all episodes, but the decline in financial crises is substantially larger than the decline in fundamentals so that expected returns going forward are large. However, drops in consumption and consumption volatility are fairly similar across financial crises and recessions and are largest during wars, so asset pricing models based on aggregate consumption have trouble matching these facts. Comparing crises to “deep” recessions strengthens these findings further. By disentangling financial crises from other bad macroeconomic times, the results suggest that financial crises are particularly important to understanding why risk premia vary. I discuss implications for theory more broadly and discuss both rational and behavioral models that are consistent with the facts. Theories where asset prices are related to the health of the financial sector appear particularly promising.

Aggregate Issuance and Savings Waves

We document the fact that at both the aggregate and the firm level, corporations tend to simultaneously raise external finance and accumulate liquid assets. For all but the very largest firms, the aggregate correlation between external finance raised and liquidity accumulation is 0.6, and the average firm level correlation is 0.2. This seems puzzling if internal and external finance are substitutes and external finance is costly. In fact, static pecking order intuition predicts that firms will first draw down liquid balances and only then issue external finance. On the other hand, if one believes that the cost of external finance varies over time, then the fact that there appear to be aggregate waves of issuance and savings activity may not be surprising. We show that a simple dynamic model with constant costs of external finance can easily match the observed positive correlation between liquidity accumulation and external finance. We compare the results of this simple model to those from a model which features a shock to the cost of external finance.

Volatility-Managed Portfolios

We show that the price of risk and quantity of risk are negatively correlated in the time-series for benchmark factors in equities and currencies. Managed portfolios that increase factor exposures when volatility is low and decrease exposure when volatility is high thus produce positive alphas and increase factor Sharpe ratios. We also find volatility timing to be more beneficial to a mean variance investor than expected return timing by a fairly wide margin. These portfolio timing strategies are simple to implement in real time and are contrary to conventional wisdom because volatility tends to be high at the beginning of recessions and crises when selling is often viewed as a mistake. The facts are potentially puzzling because they imply that effective risk aversion would have to be low when volatility is high, and vice versa. ∗Yale School of Management. We thank Nick Barberis and Jon Ingersoll for comments. We also thank Ken French and Adrien Verdelhan for making data publicly available.Managed portfolios that take less risk when volatility is high produce large alphas, substantially increase factor Sharpe ratios, and produce large utility gains for mean-variance investors. We document this for the market, value, momentum, profitability, return on equity, and investment factors in equities, as well as the currency carry trade. Volatility timing increases Sharpe ratios because changes in factor volatilities are not offset by proportional changes in expected returns. Our strategy is contrary to conventional wisdom because it takes relatively less risk in recessions and crises yet still earns high average returns. This rules out typical risk-based explanations and is a challenge to structural models of time-varying expected returns.

The Cost of Capital of the Financial Sector

Standard factor pricing models do not capture the common time series or cross sectional variation in average returns of financial stocks well. We propose a five factor asset pricing model that complements the standard Fama-French (1993) three factor model with a financial sector ROE factor (FROE) and the spread between the financial sector and the market return (SPREAD). This five factor model helps to alleviate the pricing anomalies for financial sector stocks and also performs well for nonfinancial sector stocks when compared to the Fama-French (2014) five factor or the Hou, Xue, Zhang (2014) four factor models. We find the aggregate expected return to financial sector equities to correlate negatively with aggregate financial sector ROE, which is puzzling, as ROE is commonly used as a measure of the cost of capital in the financial sector.

Should Long-Term Investors Time Volatility?

A long-term investor who ignores variation in volatility gives up the equivalent of 2.4% of wealth per year. This result holds for a wide range of parameters that are consistent with US stock market data, and it is robust to estimation uncertainty. We propose and test a new channel, the volatility composition channel, for how investment horizon interacts with volatility timing. Investors respond substantially less to volatility variation if the amount of mean reversion in returns disproportionally increases with volatility and also if mean reversion happens quickly. We find that these conditions are unlikely to hold in the data.

Intermediary Leverage and the Cross-Section of Expected Returns

I find that an assets expected return is largely explained by its covariance with intermediary leverage for a broad cross-section of returns. A one-factor leverage model performs as well as standard multi-factor models on most dimensions and in particular helps explain the 30 Industry and 10 Momentum portfolios. I consider two alternative views of how intermediary leverage is informative for asset prices: (1) the market segmentation view in which intermediaries are the agents relevant for pricing and leverage measures their marginal value of wealth and (2) the reflection of risk premia view in which consumers are the agents relevant for pricing and leverage reflects time-varying risk aversion. I find support for both views.