Published and Forthcoming Papers

Excess Volatility: Beyond Discount Rates (with S. Giglio)
Quarterly Journal of Economics, Conditionally accepted
We document a form of excess volatility that is irreconcilable with standard models of prices, and in particular cannot be explained by variation in the discount rates of rational agents.
→ Finalist for 2016 AQR Insight Award

Intermediary Asset Pricing: New Evidence from Many Asset Classes (with Z. He and A. Manela)
Journal of Financial Economics, Forthcoming
→ Link to "Intermediary Asset Pricing" data
 TooSystemicToFail: What Option Markets Imply About SectorWide Government Guarantees (with H. Lustig and S. Van Nieuwerburgh)
American Economic Review, Forthcoming
→ Winner of the Glucksman Prize
→ Winner Best Paper on Financial Institutions and Markets at 2012 WFA Annual Meeting
→ Article in Business & Economy Magazine
→ Coverage at FT.com
→ Coverage at NYTimes.com
→ NBER slides  The Price of Political Uncertainty: Theory and Evidence from the Option Market (with L. Pastor and P. Veronesi)
Journal of Finance, Forthcoming
 The Common Factor in Idiosyncratic Volatility: Quantitative Asset Pricing Implications (with B. Herskovic, H. Lustig and S. Van Nieuwerburgh)
Journal of Financial Economics, Forthcoming
 Systemic Risk and the Macroeconomy: An Empirical Evaluation (with S. Giglio and S. Pruitt)
Journal of Financial Economics, (Lead Article)
Systemic Risk Measures Data Files
→ Winner of 2015 Roger F. Murray QGroup Prize
→ Coverage at VoxEU
→ Coverage at MoneyAndBanking.com  The ThreePass Regression Filter: A New Approach to Forecasting with Many Predictors (with S. Pruitt)
Journal of Econometrics, Forthcoming
→ Separate web appendix
 Tail Risk and Asset Prices (with H. Jiang) Review of Financial Studies, October 2014, 27(10): p.28412871
→ Lead article
→ Editor's Choice article, RFS Executive Editor blog post  The Dynamic Power Law Model, Extremes, December 2014 17(4) p.557583
 Shaping Liquidity: On the Causal Effects of Voluntary Disclosure (with K. Balakrishnan, M. Billings and A. Ljungqvist)
Journal of Finance, October 2014 69(5) p.22372278
 Market Expectations in the Cross Section of Present Values (with S. Pruitt)
Journal of Finance, October 2013 68(5) p.17211756
→ Lead article
→ Winner 2012 AQR Insight Award
→ Winner 2011 Q Group Award  Testing Asymmetric Information Asset Pricing Models (with A. Ljungqvist)
Review of Financial Studies, May 2012, 25(5), p.13661413
→ Coverage at SeekingAlpha.com
 Dynamic Equicorrelation (with R. Engle)Journal of Business and Economic Statistics, April 2012, 30(2), p.212228
 A Practical Guide to Volatility Forecasting (with C. Brownlees and R. Engle)Journal of Risk, Winter 2011/2012, 14(2), p.322
Working Papers

Some Characteristics are Risk Exposures, and the Rest are Irrelevant (with S. Pruitt and Y. Su)
New asset pricing tests of characteristicbased "anomalies." If the characteristics/expected return relationship is driven by compensation for exposure to latent risk factors, IPCA will identify the corresponding latent factors. If no such factors exist, IPCA infers that the characteristic effect is compensation without risk and allocates it to an anomaly intercept. Three IPCA factors explain the cross section of average returns significantly more accurately than existing factor models and produce anomaly intercepts that are statistically zero. Among a large collection of characteristics explored in the literature, only seven are statistically significant and are responsible for all of the model?s accuracy.

Instrumented Principal Component Analysis (with S. Pruitt and Y. Su)
Econometric development of the IPCA method used in ''Some Characteristics are Risk Exposures, and the Rest are Irrelevant''

Forecasting the Distribution of Option Returns (with R. Israelov)
Uncertainty about the future option return has two sources: Changes in the position and shape of the implied volatility surface that shift option values (holding moneyness and maturity fixed), and changes in the underlying price which alter an option's location on the surface and thus its value (holding the surface fixed). We estimate a joint time series model of the spot price and volatility surface and use this to construct an ex ante characterization of the option return distribution via bootstrap. Our ''ORB'' (option return bootstrap) model accurately forecasts means, variances, and extreme quantiles of S&P 500 index conditional option return distributions across a wide range of strikes and maturities.

Measuring Technological Innovation over the Long Run (with D. Papanikolaou, A. Seru, and M. Taddy)
We use textual analysis to create new indicators of patent quality, which are available for the entire universe of patents issued by the USPTO over the 1840 to 2010 period. Our measure of patent quality is predictive of future citations and correlates strongly with measures of market value.

Text as Data (with M. Gentzkow and M. Taddy)
We provide an introduction to the use of text as an input to economic research. We discuss the features that make text different from other forms of data, offer a practical overview of relevant statistical methods, and survey a variety of applications.
 Credit Implied Volatility (with G. Manzo and D. Palhares), Preliminary draft
We introduce the concept of a credit implied volatility surface. It is inverted from CDS spreads to provides a relative measure of CDS value across "moneyness" (leverage) and time to maturity, and offers simple diagnostic tests of candidate credit pricing models.
 Firm Volatility in Granular Networks (with H. Lustig and S. Van Nieuwerburgh)
The firm size distribution and firm volatility distribution are intimately linked. When the size distribution becomes more dispersed, economic activity is concentrated among a smaller number of large firms, and the typical firm becomes less diversified. This effect is stronger for small firms since they have fewer customers to diversify shocks to begin with. As a result, firmlevel volatility possesses an approximate factor structure in which the concentration of the economywide firm size distribution serves as the factor. We document a range of new empirical facts regarding firm size and firm volatility.
 Tail Risk and Hedge Fund Returns (with H. Jiang)
We document large, persistent exposures of hedge funds to downside tail risk. For instance, the hardest hit hedge funds in the 1998 crisis also suffered predictably worse returns than their peers in 20072008. Using the conditional tail risk factor derived by Kelly (2012), we find that tail risk is a key driver of hedge fund returns in both the timeseries and crosssection. A positive one standard deviation shock to tail risk is associated with a contemporaneous decline of 2.88% per year in the value of the aggregate hedge fund portfolio. In the crosssection, funds that lose value during high tail risk episodes earn average annual returns more than 6% higher than funds that are tail riskhedged.
(Some of the above papers were part of my PhD dissertation at NYUStern, available here.)
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