آشفتگی مالی و مدیریت ریسک شرکت : نظریه و شواهد
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Financial Economics, Volume 87, Issue 3, March 2008, Pages 706–739
This paper extends the current theoretical models of corporate risk-management in the presence of financial distress costs and tests the model's predictions using a comprehensive data set. I show that the shareholders optimally engage in ex-post (i.e., after the debt issuance) risk-management activities even without a pre-commitment to do so. The model predicts a positive (negative) relation between leverage and hedging for moderately (highly) leveraged firms. Consistent with the theory, empirically I find a non-monotonic relation between leverage and hedging. Further, the effect of leverage on hedging is higher for firms in highly concentrated industries.
This paper develops and tests a theory of corporate risk management in the presence of financial distress costs. The existing literature shows that hedging can lead to firm value maximization by limiting deadweight losses of bankruptcy (see Smith and Stulz, 1985).1 These models justify only ex-ante risk-management behavior on the part of the firm; ex-post, shareholders of a levered firm may not find it optimal to engage in hedging activities due to their risk-shifting incentives (Jensen and Meckling, 1976).2 I extend the current literature by explaining the ex-post risk-management motivation of the firm.3 I provide a simple model that generates new cross-sectional predictions by relating firm characteristics such as leverage, financial distress costs, and project maturity to risk-management incentives. I test the key predictions of the model with hedging data of COMPUSTAT-CRSP firms meeting some reasonable sample selection criteria for fiscal years 1996–1997. The empirical study presents the first large-sample evidence on the determinants of the extent of firms’ hedging activities and provides new findings. The key assumption underlying my theory is the distinction between financial distress and insolvency. I assume that apart from the solvent and the insolvent states, a firm faces an intermediate state called financial distress. Financial Distress is defined as a low cash-flow state in which the firm incurs losses without being insolvent. The notion that financial distress is a different state from insolvency has some precedence in the literature. Titman (1984) uses a similar assumption to study the effect of capital structure on a firm's liquidation decisions. There are three important sources of financial distress costs. First, a financially distressed firm may lose customers, valuable suppliers, and key employees.4Opler and Titman (1994) provide empirical evidence that financially distressed firms lose significant market share to their healthy counterparts in industry downturns. Using data from the supermarket industry, (Chevalier, 1995a and Chevalier, 1995b) finds evidence that debt weakens the competitive position of a firm. Second, a financially distressed firm is more likely to violate its debt covenants5 or miss coupon/principal payments without being insolvent.6 These violations impose deadweight losses in the form of financial penalties, accelerated debt repayment, operational inflexibility, and managerial time and resources spent on negotiations with the lenders.7 Finally, a financially distressed firm may have to forgo positive NPV projects due to costly external financing, as in Froot, Scharfstein, and Stein (1993). In this paper I focus on the first of these costs, i.e., the product market-related costs of financial distress. I develop a dynamic model of a firm that issues equity capital and zero-coupon bonds to invest in a risky asset. The firm makes an initial investment with the consent of its bondholders. At a later date, shareholders can modify the firm's investment risk by replacing the existing asset with a new one. The firm's asset value evolves according to a stochastic process. The firm is in financial distress if the asset value falls below some lower threshold during its life. In this state, the firm loses market share to its competitors and therefore is unable to realize its full upside potential, even when the industry condition improves at a later date. Insolvency occurs on the maturity date if terminal firm value is below the face value of debt, in which case debtholders gain control of the firm. Shareholders’ final payoffs depend on the terminal asset value as well as on the path taken by the firm's asset over its life.8 The optimal level of ex-post investment risk, from the shareholders’ perspective, is determined by the trade-off between the costs of financial distress and value associated with the limited liability of the firm's equity.9 Unlike in the risk-shifting models such as Jensen and Meckling (1976), equity value is not always an increasing function of firm risk in my model. While a high risk project increases the value of equity's limited liability, it also imposes a cost on shareholders by increasing the expected cost of financial distress. Due to these losses, the shareholders find it optimal to implement a risk-management strategy ex-post even in the absence of an explicit pre-commitment to do so. The optimal investment risk in my model depends on firm leverage, the financial distress boundary, the time horizon of the project, and the costs of financial distress. As in the extant models (Smith and Stulz, 1985), I show that a firm with high leverage has a higher incentive to engage in hedging activities. However, the risk-management incentives disappear for firms with extremely high leverage. The incentive to hedge arises from the product market-related financial distress costs and these costs are more likely to be present when a firm is vulnerable to losing market share to its competitors. Empirical studies by Opler and Titman (1994) and Chevalier, 1995a and Chevalier, 1995b show that debt weakens the competitive position of a firm in its industry. Further, the adverse consequences of leverage are more pronounced in concentrated industries. Motivated by these studies my model argues that industry concentration provides a good proxy for financial distress costs. Highly leveraged firms in concentrated industries are more likely to experience a deterioration in their competitive position in the event of financial distress i.e., are expected to incur higher financial distress costs. Thus, the model predicts a stronger hedging incentive for highly levered firms in concentrated industries. The model shows that hedging incentives increase with project maturity because the likelihood of experiencing financial distress as well as the expected loss of default increases with the life of the asset. Risk-management motivation in my model arises from costs incurred by the firm in states in which the firm hits the financial distress barrier but remains solvent on the maturity date. If there are no financial distress costs, risk-management incentives disappear. On the other hand, if these costs are very high, the distinction between financial distress and insolvency diminishes along with any ex-post risk-management motivations. Intermediate levels of losses create risk-management incentives within the firm. Therefore, my model predicts a U-shaped relation between financial distress costs and hedging. The predictions of my model have important implications for the empirical research. To test the existing theories, empirical studies regress some measure of financial distress (typically leverage) on firms’ risk-management activities. If firms with extreme distress are less likely to hedge, these models may be misspecified. The bias can be particularly severe in small-sample studies. It is not surprising that existing empirical studies find mixed evidence in support of the distress cost-based theories of hedging.10 I contribute to the empirical risk-management literature by analyzing foreign currency and commodity risk-management activities of a comprehensive sample of nonfinancial firms. Since data on firms’ hedging activities (by means of derivatives) are not readily available, empirical studies in this area are based on small samples or investigate only the yes–no decision to hedge.11 This has created two major challenges. First, our current understanding is mostly based on analyses that treat firms with different hedging intensities as similar, which limits our ability to investigate firms’ hedging motivations. Second, we have been able to gain only limited insight into the effect of industry-specific factors on hedging decisions. I test the predictions of my model with data on the extent of hedging of more than 2,000 firms for the fiscal year 1996–1997. Due to the large sample size drawn from different industries, I provide new empirical evidence relating industry structure to hedging decisions. Consistent with the theory, I find strong evidence that firms with higher leverage hedge more, although the hedging incentives disappear for firms with very high leverage. Also in line with my theory, I find that financially distressed firms in highly concentrated industries hedge more. My empirical results are robust to alternative proxies of financial distress (such as leverage, industry-adjusted leverage and Altman Z-score), alternative ways of measuring the hedging activities (yes–no decision to hedge and total notional amount of hedging) and various controls for nonderivative-based hedging strategies. Further for a subsample of 200 manufacturing firms, I obtain data on the firms’ hedging activities for fiscal years 1997–1998 and 1998–1999 and show that the basic results remain similar for a regression model involving changes in hedging activities. While firms with a moderate increase in leverage increase their hedging activities, firms with an extreme increase in leverage decrease their hedging positions. As long as firms do not frequently change their operational hedging strategies (such as opening plants in foreign countries to hedge their foreign currency risk), the analysis based on change regressions provides a robust control for nonderivative-based hedging strategies of the firm. The change regressions also allow me to partially disentangle the effects of ex-ante and ex-post hedging incentives. The rest of the paper is organized as follows. In Section 2, I provide the model description. Section 3 analyzes the optimal risk-management policy of the firm. The empirical tests are provided in Section 4, and Section 5 concludes the paper. Without any loss in continuity, readers mostly interested in the empirical part of the paper can skip to Section 3.1, which provides a self-contained summary of the key features of the theoretical model.
نتیجه گیری انگلیسی
This paper develops a theory of corporate risk management in the presence of financial distress costs. By distinguishing “financial distress” from “insolvency”, I provide a justification for the ex-post risk-management behavior of the firm. Due to financial distress costs, the shareholders engage in ex-post risk-management activities even without a pre-commitment to do so. The theory is based on a trade-off between shareholders’ risk-shifting incentives due to equity's limited liability and their risk-avoidance incentives due to financial distress costs. I obtain a closed-form solution for the optimal level of investment risk based on this trade-off. The model generates several testable predictions. It predicts a nonmonotonic relation between leverage and hedging and a U-shaped relation between financial distress costs and hedging. Financially distressed firms in highly concentrated industries are predicted to have higher hedging incentives. I test the key predictions of my model with one of the most comprehensive samples used in the literature. I model a firm's leverage and hedging in an endogenous framework using a sample of more than 2,000 nonfinancial firms. I find evidence in support of a positive relation between leverage and foreign currency and commodity hedging. Consistent with the theory, this relation becomes negative for firms with very high leverage. Financially distressed firms in highly concentrated industries hedge more. Finally, I show that the key results remain similar for a dynamic analysis based on a change regression for a smaller subset of firms.