When Are Outside Directors Effective? (with John G. Matsusaka and Oguzhan Ozbas), 2010

Journal of Financial Economics 96, 195-214

This paper uses recent regulations that have required some companies to increase the number of outside directors on their boards to generate estimates of the effect of board independence on performance that are largely free from endogeneity problems. Our main finding is that the effectiveness of outside directors depends on the cost of acquiring information about the firm: when the cost of acquiring information is low, performance increases when outsiders are added to the board, and when the cost of information is high, performance worsens when outsiders are added to the board. The estimates provide some of the cleanest estimates to date that board independence matters, and the finding that board effectiveness depends on information cost supports a nascent theoretical literature emphasizing information asymmetry. We also find that firms compose their boards as if they understand that outsider effectiveness varies with information costs.

 Costly External Finance, Corporate Investment, and the Subprime Mortgage Credit Crisis (with Oguzhan Ozbas and Berk Sensoy), 2010

Journal of Financial Economics 97, 418-435

We study the effect of the financial crisis that began in August 2007 on corporate investment. The crisis represents an unexplored negative shock to the supply of external finance for non-financial firms. We find that corporate investment declines significantly following the onset of the crisis, controlling for firm fixed effects and time-varying measures of investment opportunities. Consistent with a causal effect of a supply shock, the decline is greatest for firms that have low cash reserves or high net short-term debt, are financially constrained, or operate in industries dependent on external finance. To address concerns about the endogeneity of firms’ finances to changes in investment opportunities, we measure these financial positions as much as four years prior to the crisis and confirm that we do not find similar results following placebo crises in the summers of 2003-2006. We also do not find similar results following the negative demand shock caused by the events of September 11. These effects weaken considerably beginning in the third quarter of 2008, when the demand-side effects of the crisis became apparent, suggesting that supply constraints may no longer have been binding. Additional analysis suggests an important precautionary savings motive for seemingly excess cash that has not been emphasized in the literature.

Disagreement, Portfolio Optimization and Excess Volatility (with Moshe Levy), 2010

Journal of Financial and Quantitative Analysis 45, 623-640

A central task facing investors who believe in market efficiency is that of portfolio optimization. As it is far from obvious how to best estimate the ex-ante expected returns and covariances, it is quite plausible that investors would hold different beliefs regarding these parameters, and that the degree of disagreement about the parameters may change over time. Levy, Levy and Benita (2006) have shown that in the portfolio context disagreement regarding the expected returns does not affect asset prices. In this paper we study the pricing effects of disagreement regarding return variances. We show that disagreement about variances has systematic and significant pricing effects. Even if the average belief about the variance is constant, tiny fluctuations in the disagreement about the variance lead to substantial price fluctuations. This result may offer an explanation for the excess volatility puzzle: small changes in the degree of disagreement are very likely to occur, and they induce relatively large price changes. Yet, the changes in disagreement may be hard to directly detect empirically, leading to apparent “excess volatility”. 

Cash Flow Hedging and Liquidity Choices (with David Disatnik and Breno Schmidt), 2011

Using unique, hand-collected data, this paper investigates how corporations combine the use of derivative hedging, cash holdings, and bank lines of credit to manage cash flow risks. Consistent with a precautionary saving motive, we find that (i) cash flow hedging derivatives and/or lines of credit serve as substitutes for cash, and (ii) the sensitivity of cash to cash flow volatility is significantly lower for firms that use either derivative hedging, lines of credit, or both. We highlight an important and largely unexplored interaction between cash flow hedging and the use of credit lines: Hedging pushes firms to substitute cash for lines of credit, since it reduces the risk of violating financial covenants. We also investigate the determinants of cash flow hedging. The use of cash flow hedging is highly related to industry, and is concentrated in industries exposed to foreign currency and commodity price risks. We also show that the relation between hedging, cash, and lines of credit is mainly concentrated in financially constrained firms. Overall, our findings shed new light on the joint determination of corporate policies to manage cash flow risks.

 The Dynamics of Cash (with Amy Dittmar), 2011

Little is known about how firms manage cash policy over time. This paper fills this gap by examining if and how firms manage cash toward a target cash ratio. Estimating partial adjustment models of cash, we find that firms actively adjust their cash toward a target; however, the speed of adjustment is slow and there is large dispersion in the speed of adjustment across firms. We investigate the causes for this and find evidence consistent with the presence of adjustment costs. We also examine the implications of these results for previous interpretations of cross-sectional results. To do this, we simulate firms’ cash paths allowing for costly adjustment and find that the emerging patterns question the interpretation of some of the standard results in the empirical cash literature.

Safer Ratios, Riskier Portfolios: Banks’ Response to Government Aid (with Denis Sosyura), 2011

We study the effect of government assistance on bank risk taking. Using hand-collected data on bank applications for government capital, we control for the selection of fund recipients and investigate the effect of both application approvals and denials. To distinguish banks’ risk-taking behavior from changes in economic conditions, we also control for the volume and quality of credit demand based on micro-level data on home mortgages and corporate loans. Our difference-in-difference analysis indicates that after the bailout, bailed banks approve riskier loans and shift investment portfolios toward riskier securities. However, this shift in risk occurs mostly within the same asset class and, therefore, has little effect on the closely-monitored capitalization levels. Consequently, bailed banks appear safer according to the capitalization requirements, but show a significant increase in market-based measures of risk. Overall, our evidence suggests that banks’ response to capital requirements may erode their efficacy in risk regulation.

Portfolio Optimization and the Distribution of Firm Size (with Moshe Levy), 2010

In the context of portfolio optimization, a firm’s market capitalization reflects the optimal portfolio weight of the firm, and is determined by the return parameters. The empirical distribution of firms’ market capitalizations is in excellent agreement with the lognormal distribution. This distribution is very skewed: the largest firms are about 1000 times larger than the median firm. The empirical distribution of average returns is not nearly as skewed: the maximal average return is only about 6 times larger than the median average return. Can the empirical firm size distribution be consistent with mean-variance portfolio optimization with realistic return parameters? We show that the expected returns implied by the empirical firm size distribution and portfolio optimization are actually in very good agreement with the empirical average returns. Moreover, the portfolio optimization framework can provide a constructive explanation for the exact lognormal functional form empirically observed. Thus, portfolio optimization is not only consistent with the empirical lognormal size distribution, it can actually explain it.