Kevin Aretz

Common Factors in Default Risk Across Countries and Industries

Global economic crises appear to strongly affect corporate bankruptcy rates. However, several prior studies indicate that changes in default risk are strongly negatively related to equity returns, which in turn depend predominately on country-specific factors. This suggests that country effects – and not global effects – should dominate changes in default risk. To analyse this issue, we decompose changes in default risk, changes in the fundamental determinants of default risk and equity returns into global, country and industry effects. We proxy for default risk through Merton (1974) default risk estimates and CDS rates. Our evidence reveals that changes in default risk always depend most strongly on global and industry effects. However, the magnitude of country effects in equity returns correlates positively with economic stability, rendering it dependent on the sample period. Our results have implications for the management of credit-sensitive securities.

Why Hedge? Rationales for Corporate Hedging and Value Implications

Purpose - In the presence of capital market imperfections, risk management at the enterprise level is apt to increase the firms value to shareholders by reducing costs associated with agency conflicts, external financing, financial distress, and taxes. The purpose of this paper is to provide an accessible and comprehensive account of these rationales for corporate risk management and to give a short overview of the empirical support found in the literature. Design/methodology/approach - The paper outlines the main theories suggesting that corporate risk management can enhance shareholder value and briefly reviews the empirical evidence on these theories. Findings - When there are imperfections in capital markets, corporate hedging can enhance shareholder value through its impact on agency costs, costly external financing, direct and indirect costs of bankruptcy, as well as taxes. More specifically, corporate hedging can alleviate underinvestment and asset substitution problems by reducing the volatility of cash flows, and it can accommodate the risk aversion of undiversified managers and increase the effectiveness of managerial incentive structures through eliminating unsystematic risk. Lower volatility of cash flows also leads to lower bankruptcy costs. Moreover, corporate hedging can also align the availability of internal resources with the need for investment funds, helping firms to avoid costly external financing. Finally, corporate risk management can reduce the corporate tax burden in the presence of convex tax schedules. While there is empirical support for these rationales of hedging at the firm level, the evidence is only modestly supportive, suggesting alternative explanations. Originality/value - The discussed theories and the empirical evidence are described in an accessible way, in part by using numerical examples.

Some implications of a quartic loss function

Motivated by a central banker with a symmetric but non-quadratic loss function, we show in this note that the approximations of two plausible loss functions of this type will include a quartic term. For skewed distributions, we establish that such a loss function implies a systematic inflation bias even when the bank targets the natural rate. Moreover, we show that the weights in an optimal combination of forecasts will differ from that under quadratic loss. We illustrate these differences using simulated data and data from the Livingston Surveys of Professional Forecasters.

Do Stock Returns Really Decrease with Default Risk? New International Evidence

This study constructs a unique dataset of bankruptcy filings for a large sample of non-U.S. firms in 14 developed markets and sheds new light on the cross-sectional relation between default risk and stock returns. Using the flexible approach of Campbell et al. (2008) to estimate default risk probabilities, this is the first study to offer conclusive evidence supporting the existence of an economically and statistically significant positive default risk premium in international markets. This finding is robust to different portfolio weighting schemes, data filters, sample periods and holding period definitions, and holds using both in-sample estimates of default probabilities during the period 1992-2010 and out-of-sample estimates during the period 2000-2010. We also show that the magnitude of the default risk premium is contingent upon a series of firm characteristics.

Which Variables Determine the Accuracy of Default Probabilities Implied by Structural Models

We argue that the Merton (1974) model’s relatively high ability to forecast bankruptcy stems from its ability to capture either the chance of net worth dropping below an externally-imposed threshold or of an economic insolvency. Using unique bankruptcy data from fifteen countries, our evidence suggests that model-implied default risk estimates are more informative if a firm’s net worth is constrained by covenants. In contrast, we only find weak evidence that model assumptions presumed to be important for capturing economic insolvency risk matter. Finally, asset liquidity and the efficiency of the variables used in calibration also relate to forecasting power.

Do Stock Market Investors Really Care About the Skewness of Long-Ahead Returns?

We use density forecasts derived from recursively estimated quantile regressions to calculate a forecast of the physical skewness of an assets future return distribution. The forecast is unbiased and efficient, and it can easily be adapted to forecast the skewness of returns calculated over any conceivable return interval. Using Neubergers (2012) realized physical skewness, we show that our quantile regression skewness forecast outperforms other variables proposed in the literature. Despite this, it does not condition the cross-section of future stock returns, neither independently nor when combined with other forecasts. Overall, we cast doubt on whether stock markets price expected stock skewness.We use density forecasts derived from recursively estimated quantile regressions to calculate a forecast of the physical skewness of an assets future return distribution. The forecast is unbiased and efficient, and it can easily be adapted to forecast the skewness of returns calculated over any conceivable return interval. Using Neubergers (2012) realized physical skewness, we show that our quantile regression skewness forecast outperforms other variables proposed in the literature. Despite this, it does not condition the cross-section of future stock returns, neither independently nor when combined with other forecasts. Overall, we cast doubt on whether stock markets price expected stock skewness.

In the Path of the Storm: Does Financial Distress Cause Non-Financial Firms to Risk-Shift?

We use a new proxy capturing manager-initiated changes to firm risk together with a unique identification strategy to study whether financial distress causes non-financial firms to risk-shift. We derive the proxy from an application of modern portfolio theory to operating-segment data and use hurricanes as distress risk instrument. Distress risk shocks lead moderately distressed firms to risk-shift. Risk-shifting is facilitated by closing low-risk segments and raises failure rates. Further evidence suggests that creditor control keeps highly distressed firms from risk-shifting. Despite its importance, we are first to empirically show that agency problems of debt cause non-financial firms to risk-shift.

Real Options Models of the Firm, Capacity Overhang, and the Cross-Section of Stock Returns

A model of the firm incorporating investment decisions and capacity utilization decisions explains stock-level momentum- and long-term reversal-effects. Assuming sufficiently irreversible investments, the model predicts that momentum winners have close to optimal capacity, whereas momentum losers have slightly more installed capacity than is optimal. Nevertheless, both produce at full capacity. An implication is that momentum losers are less risky than momentum winners. Long-term losers have greater excess capacity and produce below full capacity, whereas long-term winners have optimal capacity and operate at full capacity. An implication is that long-term losers are riskier than long-term winners. Empirical tests support the predictions.

Do Stock Markets Price Expected Stock Skewness? New Evidence from Quantile Regression Skewness Forecasts

We use density forecasts derived from recursively estimated quantile regressions to calculate a forecast of the physical skewness of an assets future return distribution. The forecast is unbiased and efficient, and it can easily be adapted to forecast the skewness of returns calculated over any conceivable return interval. Using Neubergers (2012) realized physical skewness, we show that our quantile regression skewness forecast outperforms other variables proposed in the literature. Despite this, it does not condition the cross-section of future stock returns, neither independently nor when combined with other forecasts. Overall, we cast doubt on whether stock markets price expected stock skewness.We use density forecasts derived from recursively estimated quantile regressions to calculate a forecast of the physical skewness of an assets future return distribution. The forecast is unbiased and efficient, and it can easily be adapted to forecast the skewness of returns calculated over any conceivable return interval. Using Neubergers (2012) realized physical skewness, we show that our quantile regression skewness forecast outperforms other variables proposed in the literature. Despite this, it does not condition the cross-section of future stock returns, neither independently nor when combined with other forecasts. Overall, we cast doubt on whether stock markets price expected stock skewness.

Moneyness, Total, Systematic, and Idiosyncratic Volatility, and the Cross-Section of European Option Returns

We use a stochastic discount factor model to show that the expected returns of European options are not unambiguously positively or negatively related to their underlying asset’s volatility, a conclusion strikingly different from those derived in the prior literature. Higher idiosyncratic volatility always lowers (raises) expected call (put) returns through increasing the chance of non-zero option payoffs in high (low) stochastic discount factor states. Higher systematic volatility can raise or lower the expected call or put return since it produces both the above option-payoff effect, but also an oppositely-signed effect arising through a higher underlying asset risk. The strike price modulates the strengths of the oppositely-signed effects and thus determines the signs of both the effects of systematic volatility and of total volatility on expected option returns. Single-stock call option data strongly confirm the testable implications of our European option pricing theory.