Professor of Finance, London School of Economics

The Quanto Theory of Exchange Rates (with Lukas Kremens), July, 2017

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*Best Paper Award, IF2017 Annual Conference in International Finance*

We present a new, theoretically motivated, forecasting variable for exchange rates that is based on the prices of quanto index contracts, and show via panel regressions that the quanto forecast variable is a statistically and economically significant predictor of currency appreciation. We also test the quanto variable’s ability to forecast differential currency appreciation out of sample, and find that it outperforms predictions based on uncovered interest parity, on purchasing power parity, and on a random walk.

What is the Expected Return on a Stock? (with Christian Wagner), November, 2016

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*The Wharton School‒WRDS Best Paper Award in Empirical Finance, WFA 2017*

*Honorable Mention, AQR Insight Award 2017*

We derive a formula that expresses the expected return on a stock in terms of the risk-neutral variance of the market and the stock’s excess risk-neutral variance relative to the average stock. These components can be computed from index and stock option prices; the formula has no free parameters. We test the theory in-sample by running panel regressions of stock returns onto risk-neutral variances. The formula performs well at 6-month and 1-year forecasting horizons, and our predictors drive out beta, size, book-to-market, and momentum. Out-of-sample, we find that the formula outperforms a range of competitors in forecasting individual stock returns. Our results suggest that there is considerably more variation in expected returns, both over time and across stocks, than has previously been acknowledged.

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We study the behavior of the

NBER Working Paper 17564

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I explore the behavior of asset prices and the exchange rate in a two-country world. When the large country has bad news, the relative price of the small country’s output declines. As a result, the small country’s bonds are risky, and uncovered interest parity fails, with positive excess returns available to investors who borrow at the large country’s interest rate and lend at the small country’s interest rate. I use a diagrammatic approach to derive these and other results in a calibration-free way. How Much Do Financial Markets Matter? Cole–Obstfeld Revisited, November, 2010

Cole and Obstfeld (1991) asked, “How much do financial markets matter?” Emphasizing the importance of intratemporal relative price adjustment as a risk-sharing mechanism that operates even in the absence of financial asset trade, their answer was: not much. I revisit their question and find that in calibrations featuring rare disasters that generate reasonable risk premia without implausibly high risk aversion, the cost of shutting down trade in financial assets is on the order of 3 to 20 per cent of wealth. Simple Variance Swaps, January, 2013

NBER Working Paper 16884

Note: this paper is largely subsumed by

The events of 2008‒9 disrupted volatility derivatives markets and caused the single-name variance swap market to dry up completely; it has never recovered. This paper introduces the

Online Appendix

Data: SVIX2.xls epbound.xls crashprob.xls

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I derive a lower bound on the equity premium in terms of a volatility index, SVIX, that can be calculated from index option prices. The bound implies that the equity premium is extremely volatile and that it rose above 20% at the height of the crisis in 2008. The time-series average of the lower bound is about 5%, suggesting that the bound may be approximately tight. I run predictive regressions and find that this hypothesis is not rejected by the data, so I use the SVIX index as a proxy for the equity premium and argue that the high equity premia available at times of stress largely reflect high expected returns over the very short run. I also provide a measure of the probability of a market crash, and introduce simple variance swaps, tradable contracts based on SVIX that are robust alternatives to variance swaps. Averting Catastrophes: The Strange Economics of Scylla and Charybdis (with Robert Pindyck),

Faced with numerous potential catastrophes—nuclear and bioterrorism, mega-viruses, climate change, and others—which should society attempt to avert? A policy to avert one catastrophe considered in isolation might be evaluated in cost-benefit terms. But because society faces multiple catastrophes, simple cost-benefit analysis fails: even if the benefit of averting each one exceeds the cost, we should not necessarily avert them all. We explore the policy interdependence of catastrophic events, and develop a rule for determining which catastrophes should be averted and which should not. The Lucas Orchard,

Supplemental Material

This paper investigates the behavior of asset prices in an endowment economy in which a representative agent with power utility consumes the dividends of multiple assets. The assets are Lucas trees; a collection of Lucas trees is a Lucas orchard. The model generates return correlations that vary endogenously, spiking at times of disaster. Since disasters spread across assets, the model generates large risk premia even for assets with stable cashflows. Very small assets may comove endogenously and hence earn positive risk premia even if their cashflows are independent of the rest of the economy. I provide conditions under which the variation in a small asset’s price-dividend ratio can be attributed almost entirely to variation in its risk premium.

Consumption-Based Asset Pricing with Higher Cumulants, *Review of Economic Studies (2013), 80:2:745‒773*

Online Appendix

I extend the Epstein–Zin-lognormal consumption-based asset-pricing model to allow for general i.i.d. consumption growth. Information about the higher moments—equivalently, cumulants—of consumption growth is encoded in the *cumulant-generating function*. I use the framework to analyze economies with rare disasters, and argue that the importance of such disasters is a double-edged sword: parameters that govern the frequency and sizes of rare disasters are critically important for asset pricing, but extremely hard to calibrate. I show how to sidestep this issue by using observable asset prices to make inferences without having to estimate higher moments of the underlying consumption process. Extensions of the model allow consumption to diverge from dividends, and for non-i.i.d. consumption growth.

Online Appendix

I show that the pricing of a broad class of long-dated assets is driven by the possibility of extraordinarily bad news. This result does not depend on any assumptions about the existence of disasters, nor does it only apply to assets that hedge bad outcomes; indeed, it even applies to long-dated claims on the

We use equity index options to quantify the distribution of consumption growth disasters. The challenge lies in connecting the risk-neutral distribution of equity returns implied by options to the true distribution of consumption growth estimated from macroeconomic data. We attack the problem from three perspectives. First, we compare pricing kernels constructed from macro-finance and option-pricing models. Second, we compare option prices derived from a macro-finance model to those we observe. Third, we compare the distribution of consumption growth derived from option prices using a macro-finance model to estimates based on macroeconomic data. All three perspectives suggest that options imply smaller probabilities of extreme outcomes than have been estimated from international macroeconomic data. The third comparison yields a viable alternative calibration of the distribution of consumption growth that matches the equity premium, option prices, and the sample moments of US consumption growth. Disasters and the Welfare Cost of Uncertainty,