Faculty & Research

Bryan T. Kelly

Assistant Professor of Finance

Phone :
773 702-8359
Address :
5807 South Woodlawn Avenue
Chicago, IL 60637

Bryan T. Kelly joined Chicago Booth in 2010 as Assistant Professor of Finance after earning his PhD and MPhil in finance at New York University's Leonard N. Stern School of Business. His research interests include theoretical and empirical asset pricing; models of tail risk, volatility and correlation dynamics; and asymmetric information in asset markets. He is a faculty research fellow at the NBER and an associate editor of the Journal of Financial Econometrics. Kelly is the recipient of the 2012 AQR Insight Award, and has received various other research awards including the JPMorgan Best Paper Award from the WFA, the Q-group Research Award, the Arnold Zellner Award (honorable mention), the David M. Graifman award for best dissertation in finance at NYU Stern, the Herman E. Kroos award for best dissertation across disciplines at NYU Stern, and the Shmuel Kandel Prize, and various research grants.

Prior to his doctoral studies, Kelly worked in Morgan Stanley's investment banking division and in the sales and trading division of UBS. He holds an M.A. in economics from University of California, San Diego and an A.B. in economics (with honors) from the University of Chicago.

Kelly teaches Investments at Booth, and previously taught the undergraduate Foundations of Financial Markets course at Stern, for which he received a commendation for teaching excellence.

 

2013 - 2014 Course Schedule

Number Name Quarter
35000 Investments 2014 (Winter)
35600 Seminar: Finance 2013 (Fall)

REVISION: The Common Factor in Idiosyncratic Volatility: Quantitative Asset Pricing Implications
Date Posted: Apr  19, 2014
We show that firms' idiosyncratic volatility obeys a strong factor structure and that shocks to the common factor in idiosyncratic volatility (CIV) are priced. Stocks in the lowest CIV-beta quintile earn average returns 6.4% per year higher than those in the highest quintile. We provide evidence that the CIV factor is correlated with income risk faced by households. These three facts are consistent with a canonical incomplete markets heterogeneous-agent model. In the model, CIV is a priced state variable because an increase in idiosyncratic firm volatility raises the typical investor's marginal utility when markets are incomplete. The calibrated model matches the high degree of comovement in idiosyncratic volatilities, the CIV-beta return spread, and several other asset price moments.

REVISION: The Price of Political Uncertainty: Theory and Evidence from the Option Market
Date Posted: Apr  02, 2014
We empirically analyze the pricing of political uncertainty, guided by a theoretical model of government policy choice. After deriving the model's predictions for option prices, we test those predictions in an international sample of national elections and global summits. We find that political uncertainty is priced in the option market in ways predicted by the theory. Options whose lives span political events tend to be more expensive. Such options provide valuable protection against the risk associated with political events, including not only price risk but also variance and tail risks. This protection is more valuable in a weaker economy as well as amid higher political uncertainty.

New: The Price of Political Uncertainty: Theory and Evidence from the Option Market
Date Posted: Jan  13, 2014
We empirically analyze the pricing of political uncertainty, guided by a theoretical model of government policy choice. After deriving the model’s predictions for option prices, we test those predictions in an international sample of national elections and global summits. We find that political uncertainty is priced in the option market in ways predicted by the theory. Options whose lives span political events tend to be more expensive. Such options provide valuable protection against the risk associated with political events, including not only price risk but also variance and tail risks. This protection is more valuable in a weaker economy as well as amid higher political uncertainty.

REVISION: Tail Risk and Asset Prices
Date Posted: Jan  11, 2014
We propose a new measure of time-varying tail risk that is directly estimable from the cross section of returns. We exploit firm-level price crashes every month to identify common fluctuations in tail risk across stocks. Our tail measure is significantly correlated with tail risk measures extracted from S&P 500 index options, but is available for a longer sample since it is calculated from equity data. We show that tail risk has strong predictive power for aggregate market returns: A one standard deviation increase in tail risk forecasts an increase in excess market returns of 4.5% over the following year. Cross-sectionally, stocks with high loadings on past tail risk earn an annual three-factor alpha 5.4% higher than stocks with low tail risk loadings. These findings are consistent with asset pricing theories that relate equity risk premia to rare disasters or other forms of tail risk.

REVISION: Too-Systemic-To-Fail: What Option Markets Imply About Sector-Wide Government Guarantees
Date Posted: Dec  20, 2013
We examine the pricing of financial crash insurance during the 2007-2009 financial crisis in U.S. option markets. A large amount of aggregate tail risk is missing from the price of financial sector crash insurance during the financial crisis. The difference in costs of out-of-the-money put options for individual banks and puts on the financial sector index increases fourfold from its pre-crisis 2003-2007 level. We provide evidence that a collective government guarantee for the financial sector, which lowers index put prices far more than those of individual banks, explains the divergence in the basket-index put spread.

REVISION: Too-Systemic-To-Fail: What Option Markets Imply About Sector-Wide Government Guarantees
Date Posted: Dec  20, 2013
We examine the pricing of financial crash insurance during the 2007-2009 financial crisis in U.S. option markets. A large amount of aggregate tail risk is missing from the price of financial sector crash insurance during the financial crisis. The difference in costs of out-of-the-money put options for individual banks and puts on the financial sector index increases fourfold from its pre-crisis 2003-2007 level. We provide evidence that a collective government guarantee for the financial sector, which lowers index put prices far more than those of individual banks, explains the divergence in the basket-index put spread.

REVISION: Systemic Risk and the Macroeconomy: An Empirical Evaluation
Date Posted: Nov  15, 2013
We propose an empirical criterion for evaluating systemic risk measures based on their ability to predict quantiles of future macroeconomic shocks. We construct 17 measures of systemic risk in the US and Europe spanning several decades. We propose dimension reduction estimators for constructing systemic risk indexes from the cross section of measures and prove their consistency in a factor model setting. Empirically, systemic risk indexes provide significant predictive information for the lower tail of future macroeconomic shocks, even out-of-sample.

REVISION: Firm Volatility in Granular Networks
Date Posted: Oct  15, 2013
We propose a model of firm volatility based on customer-supplier connectedness. We assume that customers' growth rate shocks influence the growth rates of their suppliers, larger suppliers have more customers, and the strength of a customer-supplier link depends on the size of the customer firm. When the size distribution becomes more dispersed, economic activity is concentrated among a smaller number of firms, the typical supplier becomes less diversified and its volatility increases. The model is consistent with a set of new stylized facts. At the macro level, the firm volatility distribution is driven by firm size dispersion; the latter explains common movements in firm-level total and residual volatility. At the micro level, we show that the concentration of customer networks is an important determinant of firm-level volatility.

REVISION: Shaping Liquidity: On the Causal Effects of Voluntary Disclosure
Date Posted: Aug  25, 2013
Can managers influence the liquidity of their firms’ shares? We use plausibly exogenous variation in the supply of public information to show that firms actively shape their information environments by voluntarily disclosing more information than regulations mandate and that such efforts improve liquidity. Firms respond to an exogenous loss of public information by providing more timely and informative earnings guidance. Responses appear motivated by a desire to reduce information asymmetries

REVISION: Shaping Liquidity: On the Causal Effects of Voluntary Disclosure
Date Posted: Aug  25, 2013
Can managers influence the liquidity of their firms’ shares? We use plausibly exogenous variation in the supply of public information to show that firms actively shape their information environments by voluntarily disclosing more information than regulations mandate and that such efforts improve liquidity. Firms respond to an exogenous loss of public information by providing more timely and informative earnings guidance. Responses appear motivated by a desire to reduce information asymmetries

REVISION: Shaping Liquidity: On the Causal Effects of Voluntary Disclosure
Date Posted: Aug  25, 2013
Can managers influence the liquidity of their firms’ shares? We use plausibly exogenous variation in the supply of public information to show that firms actively shape their information environments by voluntarily disclosing more information than regulations mandate and that such efforts improve liquidity. Firms respond to an exogenous loss of public information by providing more timely and informative earnings guidance. Responses appear motivated by a desire to reduce information asymmetries

REVISION: Shaping Liquidity: On the Causal Effects of Voluntary Disclosure
Date Posted: Aug  25, 2013
Can managers influence the liquidity of their firms’ shares? We use plausibly exogenous variation in the supply of public information to show that firms actively shape their information environments by voluntarily disclosing more information than regulations mandate and that such efforts improve liquidity. Firms respond to an exogenous loss of public information by providing more timely and informative earnings guidance. Responses appear motivated by a desire to reduce information asymmetries

REVISION: Tail Risk and Hedge Fund Returns
Date Posted: Nov  20, 2012
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 2007-2008. 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 time-series and cross-section. A positive one standard deviation shock to tail risk is associated with a contemporaneous decline of 2.88% per year in the

REVISION: Market Expectations in the Cross Section of Present Values
Date Posted: Sep  11, 2012
Returns and cash flow growth for the aggregate U.S. stock market are highly and robustly predictable. Using a single factor extracted from the cross section of book- to-market ratios, we find an out-of-sample return forecasting R-squared as high as 13% at the annual frequency (0.9% monthly). We document similar out-of-sample predictability for returns on value, size, momentum and industry-sorted portfolios. We present a model linking aggregate market expectations to disaggregated valuation ratio

REVISION: The Three-Pass Regression Filter: A New Approach to Forecasting Using Many Predictors
Date Posted: Jun  13, 2012
We forecast a single time series using many predictor variables with a new estimator called the three-pass regression filter (3PRF). It is calculated in closed form and conveniently represented as a set of ordinary least squares regressions. 3PRF forecasts converge to the infeasible best forecast when both the time dimension and cross section dimension become large. This requires only specifying the number of relevant factors driving the forecast target, regardless of the total number of common

REVISION: Too-Systemic-To-Fail: What Option Markets Imply About Sector-Wide Government Guarantees
Date Posted: Mar  23, 2012
A conspicuous amount of aggregate tail risk is missing from the price of financial sector crash insurance during the 2007-2009 crisis. The difference in costs of out-of-the-money put options for individual banks, and puts on the financial sector index, increases four fold from its pre-crisis level. At the same time, correlations among bank stocks surge, suggesting the high put spread cannot be attributed to a relative increase in idiosyncratic risk. We show that this phenomenon is uniqueto the f

REVISION: Dynamic Equicorrelation
Date Posted: Feb  07, 2012
A new covariance matrix estimator is proposed under the assumption that at every time period all pairwise correlations are equal. This assumption, which is pragmatically applied in various areas of finance, makes it possible to estimate arbitrarily large covariance matrices with ease. The model, called DECO, involves first adjusting for individual volatilities and then estimating correlations. A quasi-maximum likelihood result shows that DECO provides consistent parameter estimates even when the

REVISION: A Practical Guide to Volatility Forecasting through Calm and Storm
Date Posted: Sep  07, 2011
We present a volatility forecasting comparative study within the ARCH class of models. Our goal is to identify successful predictive models over multiple horizons and to investigate how predictive ability is influenced by choices for estimation window length, innovation distribution, and frequency of parameter re-estimation. Test assets include a range of domestic and international equity indices and exchange rates. We find that model rankings are insensitive to forecast horizon and suggestions

REVISION: Testing Asymmetric-Information Asset Pricing Models
Date Posted: Jul  18, 2011
Modern asset pricing theory is based on the assumption that investors have heterogeneous information. We provide direct evidence of the importance of information asymmetry for asset prices and investor demands using three natural experiments that capture plausibly exogenous variation in information asymmetry on a stock-by-stock basis for a large set of U.S. companies. Consistent with predictions derived from an asymmetric-information rational expectations model with multiple assets and multiple

REVISION: Testing Asymmetric-Information Asset Pricing Models
Date Posted: Jul  16, 2011
Modern asset pricing theory is based on the assumption that investors have heterogeneous information. We provide direct evidence of the importance of information asymmetry for asset prices and investor demands using three natural experiments that capture plausibly exogenous variation in information asymmetry on a stock-by-stock basis for a large set of U.S. companies. Consistent with predictions derived from an asymmetric-information rational expectations model with multiple assets and multiple

New: Testing Asymmetric-Information Asset Pricing Models
Date Posted: Feb  18, 2009
Theoretical asset pricing models routinely assume that investors have heterogeneous information. We provide direct evidence of the importance of information asymmetry for asset prices and investor demands using plausibly exogenous variation in the supply of information caused by the closure or restructuring of brokerage firms' research operations. Consistent with predictions derived from a Grossman and Stiglitz-type model, share prices and uninformed investors' demands fall as information asymme

New: The Value of Research
Date Posted: Dec  29, 2008
We estimate the value added by sell-side equity research analysts and explore the links between analyst research, informational efficiency, and asset prices. We identify the value of research from exogenous changes in analyst coverage. On announcement that a stock has lost all coverage, share prices fall by around 110 basis points or $8.4 million on average. The share pricereaction is attenuated the more analysts continue to cover the stock, suggesting that there are diminishing returns to cover


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