Knowledge that Transforms

Investors' learning of the state of future real fundamentals from current inflation leads to macroeconomic state dependence of asset valuations and solvency ratios of firms within given rating categories. Since credit spreads are convex functions of solvency ratios, average spreads are higher than spreads at average solvency ratios. Macroeconomic shocks carry risk premiums so that expected default losses are more sensitive to changes in the price of risk than are credit spreads. By incorporating state dependence and increasing the price of risk, the econometrician obtains high credit spreads while maintaining average default losses at historical levels—the credit spreads puzzle. The Author 2007. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: [email protected]., Oxford University Press.

Information advantage and entry deterrence incentives are investigated as they affect lending outcomes and competitive structure of the U.S. residential mortgage market. In the model, when assessing a loan applicant, the incumbent monopoly lender employs a proprietary screening technology to produce a privately observed estimate of loan credit quality. When faced with potential competitive entry, the incumbent signals poor credit quality by charging high prices to higher-quality borrowers. Market structure and loan pricing strategy are derived endogenously, where the incumbent deters entry first by segmenting consumers into prime and sub-prime loan markets and second by charging prime market borrowers a uniform rate that is higher than the risk-based monopoly rate. Empirical implications of the model are identified, and evidence is presented that is consistent with predictions.

We examine how well several institutional- and firm-level factors explain firms’ perceptions of property rights protection. The institutional theories we investigate account for approximately 50% of the country-level variation, indicating that current research addresses first-order factors. Firm-level characteristics, such as legal organization and ownership structure, are comparable with institutional factors in explaining variations in property rights protection. A country’s legal origin predicts property rights variation better than its religion, ethnic fractionalization, or natural endowments. However, these results are driven by the inclusion of former Socialist economies in the sample. When we exclude the former Socialist economies, legal origin explains considerably less than ethnic fractionalization does.

We use a standard single-agent model to conduct a simple consumption growth accounting exercise.

We analyze the impact of emerging-market sovereign bonds on emerging-market corporate bonds by examining their spanning enhancement, price discovery, and issuance effects. We find that the effect of spanning enhancement is positive and large; over one-fifth of the information in corporate yield spreads is traced to innovations in sovereign bonds; and most of these effects are due to discovery and spanning of systematic risks. Further, issuance of sovereign bonds, controlling for endogeneity of market-timing decisions, lowers corporate yield and bid-ask spreads. Our results indicate that sovereign securities act as benchmarks and suggest they promote a vibrant corporate bond market.

We present a rational general equilibrium model that highlights the fact that relative wealth concerns can play a role in explaining financial bubbles. We consider a finite-horizon overlapping generations model in which agents care only about their consumption. Though the horizon is finite, competition over future investment opportunities makes agents' utilities dependent on the wealth of their cohort and induces relative wealth concerns. Agents herd into risky securities and drive down their expected return. Even though the bubble is likely to burst and lead to a substantial loss, agents' relative wealth concerns make them afraid to trade against the crowd.

This article develops a Kalman filter model to track dynamic mutual fund factor loadings. It then uses the estimates to analyze whether managers with market-timing ability can be identified ex ante. The primary findings are as follows: (i) Ordinary least squares (OLS) timing models produce false positives (nonzero alphas) at too high a rate with either daily or monthly data. In contrast, the Kalman filter model produces them at approximately the correct rate with monthly data; (ii) In monthly data, though the OLS models fail to detect any timing among fund managers, the Kalman filter does; (iii) The alpha and beta forecasts from the Kalman model are more accurate than those from the OLS timing models; (iv) The Kalman filter model tracks most fund alphas and betas better than OLS models that employ macroeconomic variables in addition to fund returns.

1 We solve a model with incomplete markets and heterogeneous agents that generates a large equity premium, while simultaneously matching stock market participation and indi-vidual asset holdings. The high risk premium is driven by incomplete risk sharing among stockholders, which results from the combination of aggregate uncertainty, borrowing con-straints and a (realistically) calibrated life-cycle earnings profile subject to idiosyncratic shocks. We show that it is challenging to simultaneously match asset pricing moments and individual portfolio decisions, while limited participation has a negligible impact on the risk premium, contrary to the results of models where it is imposed exogenously.

We propose a new method for pricing options based on GARCH models with filtered historical innovations. In an incomplete market framework, we allow for different distributions of historical and pricing return dynamics enhancing the model flexibility to fit market option prices. An extensive empirical analysis based on S&P 500 index options shows that our model outperforms other competing GARCH pricing models and ad hoc Black-Scholes models. We show that the flexible change of measure, the asymmetric GARCH volatility and the nonparametric innovation distribution induce the accurate pricing performance of our model. Using a nonparametric approach, we obtain decreasing state price densities per unit probability as suggested by economic theory and corroborating our GARCH pricing model. Implied volatility smiles appear to be explained by asymmetric volatility and negative skewness of filtered historical innovations.

Aggregate stock prices, relative to virtually any indicator of fundamental value, soared to unprecedented levels in the 1990s. Even today, after the market declines since 2000, they remain well above historical norms. Why? We consider one particular explanation: a fall in macroeconomicrisk, or the volatility of the aggregate economy. Empirically, we find a strong correlation between low-frequency movements in macroeconomic volatility and low-frequency movements in the stock market. To model this phenomenon, we estimate a two-state regime switching model for the volatility and mean of consumption growth, and find evidence of a shift to substantially lower consumption volatility at the beginning of the 1990s. We then use these estimates from postwar data to calibrate a rational asset pricing model with regime switches in both the mean and standard deviation of consumption growth. Plausible parameterizations of the model are found to account for a significant portion of the run-up in asset valuation ratios observed in the late 1990s.