Hui Chen

A Unified Theory of Tobin's Q, Corporate Investment, Financing, and Risk Management

This paper proposes a simple homogeneous dynamic model of investment and corporate risk management for a financially constrained firm. Following Froot, Scharfstein, and Stein (1993), we define a corporations risk management as the coordination of investment and financing decisions. In our model, corporate risk management involves internal liquidity management, financial hedging, and investment. We determine a firms optimal cash, investment, asset sales, credit line, external equity finance, and payout policies as functions of the following key parameters: 1) the firms earnings growth and cash-flow risk; 2) the external cost of financing; 3) the firms liquidation value; 4) the opportunity cost of holding cash; 5) investment adjustment and asset sales costs; and 6) the return and covariance characteristics of hedging assets the firm can invest in. The optimal cash inventory policy takes the form of a double-barrier policy where i) cash is paid out to shareholders only when the cash-capital ratio hits an endogenous upper barrier, and ii) external funds are raised only when the firm has depleted its cash. In between the two barriers, the firm adjusts its capital expenditures, asset sales, and hedging policies. Several new insights emerge from our analysis. For example, we find an inverse relation between marginal Tobins q and investment when the firm draws on its credit line. We also find that financially constrained firms may have a lower equity beta in equilibrium because these firms tend to hold higher precautionary cash inventories.

Dynamic Asset Allocation with Ambiguous Return Predictability

We study an investors optimal consumption and portfolio choice problem when he confronts with two possibly misspecified submodels of stock returns: one with IID returns and the other with predictability. We adopt a generalized recursive ambiguity model to accommodate the investors aversion to model uncertainty. The investor deals with specification doubts by slanting his beliefs about submodels of returns pessimistically, causing his investment strategy to be more conservative than the Bayesian strategy. This effect is large for extreme values of the predictive variable. Unlike in the Bayesian framework, model uncertainty induces a hedging demand, which may cause the investor to decrease his stock allocations sharply and then increase with his prior probability of IID returns. Adopting suboptimal investment strategies by ignoring model uncertainty can lead to sizable welfare costs.

Systematic Risk, Debt Maturity, and the Term Structure of Credit Spreads

We document several facts about corporate debt maturity: (1) debt maturity is pro-cyclical; (2) higher-beta firms tend to have longer debt maturity; (3) shorter maturity amplifies the sensitivity of credit spreads to aggregate shocks. We build a dynamic capital structure model that explains these facts. In the model, leverage and maturity choices are highly interdependent, which reflects the tradeoffs of liquidity discounts of long-term debt, repayment risks of short-term debt, and the benefit of short-term debt as a commitment device for timely leverage adjustments. Additionally, the model quantifies the effects of maturity dynamics on the term structure of credit spreads.

Houses as ATMs? Mortgage Refinancing and Macroeconomic Uncertainty

We estimate a structural model of household liquidity management in the presence of long-term mortgages. Households face counter-cyclical idiosyncratic labor income uncertainty and borrowing constraints, which affect optimal choices of leverage, precautionary saving in liquid assets and illiquid home equity, debt repayment, mortgage refinancing, and default. Taking the observed historical path of house prices, aggregate income, and interest rates as given, the model quantitatively accounts for the run-up in household debt and consumption boom prior to the financial crisis, their subsequent collapse, and mild recovery following the Great Recession, especially among the most constrained households.

Macroeconomic Risk and Debt Overhang

– Since corporate debt tends to be riskier in recessions, transfers from equity holders to debt holders that accompany corporate decisions also tend to concentrate in recessions. Such systematic risk exposures of debt overhang have important implications for corporate investment and financing decisions, and for the ex ante costs of debt overhang. Using a calibrated dynamic capital structure model, we show that the costs of debt overhang become higher in the presence of macroeconomic risk. We also provide several new predictions on how the cyclicality of a firm’s assets in place and growth options affect its investment and capital structure decisions.

Measuring the 'Dark Matter' in Asset Pricing Models

We propose a new quantitative measure of model fragility, based on the tendency of a model to over-fit the data in sample with poor out-of-sample performance. We formally show that structural economic models are fragile when the cross-equation restrictions they impose on the baseline statistical model appear excessively informative about combinations of model parameters that are otherwise difficult to estimate. We develop an analytically tractable asymptotic approximation to our fragility measure which we use to identify the problematic parameter combinations. Using these asymptotic results, we diagnose fragility in asset pricing models with rare disasters and long-run consumption risk.

Demand for Crash Insurance, Intermediary Constraints, and Risk Premia in Financial Markets

We model the market for economic disaster insurance to examine the dynamic relation between the net demand by public investors and the disaster risk premium. In the model, when the probability of disasters rises, dealers become more constrained and averse to disaster risk, which reduces their risk sharing capacity, causing the equilibrium net public demand for disaster insurance to fall and the disaster risk premium to rise at the same time. Consistent with the model predictions, we nd that public demand for deep out-of-the-money put options on the market index has strong predictive power for future stock returns. Large net public buying of OTM puts is associated with low future returns, with an R 2 of 19% for the predictability regression of future 3-month returns. This predictive power of option demand is distinct from that of the standard predictive variables in the literature, is particularly strong during the recent nancial crisis, and it weakens as one moves to at-the-money and in-the-money options. We also provide evidence that low net public demand for disaster insurance is linked to deleveraging for security brokers and dealers.We propose a new measure of financial intermediary constraints based on how the intermediaries manage their tail risk exposures. Using a unique dataset for the trading activities in the market of deep out-of-the-money S&P 500 put options, we identify periods when the variations in the net amount of trading between financial intermediaries and public investors are likely to be mainly driven by shocks to intermediary constraints. We then infer tightness of intermediary constraints from the quantities of option trading during such periods. We show that a tightening of intermediary constraint according to our measure is associated with increasing option expensiveness, higher risk premia for a wide range of financial assets, deterioration in funding liquidity, and deleveraging of broker-dealers.