We examine the accuracy and contribution of the Merton distance to default (DD) model, which is based on Merton's (1974) bond pricing model. We compare the model to a “naive” alternative, which uses the functional form suggested by the Merton model but does not solve the model for an implied probability of default. We find that the naive predictor performs slightly better in hazard models and in out-of-sample forecasts than both the Merton DD model and a reduced-form model that uses the same inputs. Several other forecasting variables are also important predictors, and fitted values from an expanded hazard model outperform Merton DD default probabilities out of sample. Implied default probabilities from credit default swaps and corporate bond yield spreads are only weakly correlated with Merton DD probabilities after adjusting for agency ratings and bond characteristics. We conclude that while the Merton DD model does not produce a sufficient statistic for the probability of default, its functional form is useful for forecasting defaults.

https://www.jstor.org/stable/pdfplus/40056852.pdf

Forecasting Default with the Merton Distance to Default Model

The other side of value: The gross profitability premium.

Investor Psychology and Security Market Under- and Overreactions

Motivated from investment-based asset pricing, we propose a new factor model that consists of the market factor, a size factor, an investment factor, and a return-on-equity factor The new model [i] outperforms the Carhart (1997) four-factor model in pricing portfolios formed on earnings surprise, idiosyncratic volatility, financial distress, equity issues, as well as on investment and return-on-equity; [ii] performs similarly as the Carhart model in pricing portfolios on momentum as well as on size and book-to-market; but [iii] underperforms in pricing the total accrual deciles Our model's performance, combined with its clear economic intuition, suggests that it can serve as a new workhorse model for academic research and investment management practice

Digesting Anomalies: An Investment Approach

An empirical q-factor model consisting of the market factor, a size factor, an investment factor, and a profitability factor largely summarizes the cross section of average stock returns. A comprehensive examination of nearly 80 anomalies reveals that about one-half of the anomalies are insignificant in the broad cross section. More importantly, with a few exceptions, the q-factor model's performance is at least comparable to, and in many cases better than that of the Fama-French (1993) 3-factor model and the Carhart (1997) 4-factor model in capturing the remaining significant anomalies.

/pdf/digesting-anomalies-an-investment-approach-3oub45mmsf.pdf

This paper explores the determinants of corporate failure and the pricing of financially distressed stocks using US data over the period 1963 to 2003. Firms with higher leverage, lower profitability, lower market capitalization, lower past stock returns, more volatile past stock returns, lower cash holdings, higher market-book ratios, and lower prices per share are more likely to file for bankruptcy, be delisted, or receive a D rating. When predicting failure at longer horizons, the most persistent firm characteristics, market capitalization, the market-book ratio, and equity volatility become relatively more significant. Our model captures much of the time variation in the aggregate failure rate. Since 1981, financially distressed stocks have delivered anomalously low returns. They have lower returns but much higher standard deviations, market betas, and loadings on value and small-cap risk factors than stocks with a low risk of failure. These patterns hold in all size quintiles but are particularly strong in smaller stocks. They are inconsistent with the conjecture that the value and size effects are compensation for the risk of financial distress.

https://papers.ssrn.com/sol3/Delivery.cfm/nber_w12362.pdf?abstractid=917567&mirid=1

In Search of Distress Risk

This paper explores the determinants of corporate failure and the pricing of financially distressed stocks whose failure probability, estimated from a dynamic logit model using accounting and market variables, is high. Since 1981, financially distressed stocks have delivered anomalously low returns. They have lower returns but much higher standard deviations, market betas, and loadings on value and small-cap risk factors than stocks with low failure risk. These patterns are more pronounced for stocks with possible informational or arbitrage-related frictions. They are inconsistent with the conjecture that the value and size effects are compensation for the risk of financial distress. THE CONCEPT OF FINANCIAL DISTRESS has been invoked in the asset pricing literature to explain otherwise anomalous patterns in the cross-section of stock returns (Chan and Chen (1991) and Fama and French (1996)). The idea is that certain companies have an elevated probability that they will fail to meet their financial obligations; the stocks of these financially distressed companies tend to move together, so their risk cannot be diversified away; and investors charge a premium for bearing such risk. 1 The premium for distress risk may not be captured by the standard Capital Asset Pricing Model (CAPM) if corporate failures

/pdf/in-search-of-distress-risk-1nbpnxwcsk.pdf

This paper investigates the effects of macroeconomic fundamentals on emerging market sovereign credit spreads. We find that the volatility of terms of trade in particular has a statistically and economically significant effect on spreads. This is robust to instrumenting terms of trade with a country-specific commodity price index. Our measures of country fundamentals have substantial explanatory power, even controlling for global factors and credit ratings. We also estimate default probabilities in a hazard model and find that model implied spreads capture a significant part of the variation in observed spreads out-of-sample. The fit is better for lower credit quality borrowers.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID1492705_code93882.pdf?abstractid=687499&mirid=1&type=2

Determinants of Sovereign Risk: Macroeconomic Fundamentals and the Pricing of Sovereign Debt

/pdf/determinants-of-sovereign-risk-macroeconomic-fundamentals-1tyxsumrao.pdf

Jens Hilscher

Papers

In Search of Distress Risk

In Search of Distress Risk

In Search of Distress Risk

Determinants of Sovereign Risk: Macroeconomic Fundamentals and the Pricing of Sovereign Debt

Determinants of Sovereign Risk: Macroeconomic Fundamentals and the Pricing of Sovereign Debt