[Nonlinearity is an important consideration in many problems of finance and economics, such as pricing securities and solving equilibrium models. This article provides analytical treatment of a general class of nonlinear transforms for processes with tractable conditional characteristic functions. We extend existing results on characteristic function-based transforms to a substantially wider class of nonlinear functions while maintaining low dimensionality by avoiding the need to compute the density function. We illustrate the applications of the generalized transform in pricing defaultable bonds with stochastic recovery. We also use the method to analytically solve a class of general equilibrium models with multiple goods and apply this model to study the effects of time-varying labor income risk on the equity premium.]

[Risks of rare economic disasters can have a large impact on asset prices. At the same time, difficulties in inference regarding both the likelihood and severity of disasters, as well as agency problems, can lead to significant disagreements among investors about disaster risk. We show that such disagreements generate strong risk-sharing motives, such that just a small number of optimists in the economy will significantly reduce the disaster risk premium. Our model highlights the "latent" nature of disaster risk. The disaster risk premium will likely be low and smooth during normal times but increases dramatically when the risk-sharing capacity of the optimists is reduced, e.g., following a disaster. The model also helps reconcile the difference in the amount of disaster risk implied by financial markets and international macroeconomic data, and provides caution to the approach of extracting disaster probabilities from asset prices, which will disproportionately reflect the beliefs of a small group of optimists. Finally, our model predicts an inverse U-shaped relation between the equity premium and the size of the disaster insurance market.]

[In any canonical Gaussian dynamic term structure model (GDTSM), the conditional forecasts of the pricing factors are invariant to the imposition of no-arbitrage restrictions. This invariance is maintained even in the presence of a variety of restrictions on the factor structure of bond yields. To establish these results, we develop a novel canonical GDTSM in which the pricing factors are observable portfolios of yields. For our normalization, standard maximum likelihood algorithms converge to the global optimum almost instantaneously. We present empirical estimates and out-of-sample forecasts for several GDTSMs using data on U.S. Treasury bond yields.]

In any canonical Gaussian dynamic term structure model (GDTSM), the conditional forecasts of the pricing factors are invariant to the imposition of no-arbitrage restrictions. This invariance is maintained even in the presence of a variety of restrictions on the factor structure of bond yields. To establish these results, we develop a novel canonical GDTSM in which the pricing factors are observable portfolios of yields. For our normalization, standard maximum likelihood algorithms converge to the global optimum almost instantaneously. We present empirical estimates and out-of-sample forecasts for several GDTSMs using data on U.S. Treasury bond yields. The Author 2011. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: [email protected]., Oxford University Press.

This paper provides theory and evidence that a low-dimensional term structure model can simultaneously price bonds and related options. It shows that a component of volatility risk largely unrelated to the shape of the yield curve is a determinant of expected excess returns for holding long maturity bonds. It also finds evidence for this return relationship both in the model and directly in the data through regression analysis. The paper also identifies a link between corporate earnings performance and interest rate volatility, providing a channel driving interest rate volatility. The structure of risk in the model that gives rise to these features of volatility is distinct from that inherent in recent models with unspanned stochastic volatility.

Nonlinearity is an important consideration in many problems of finance and economics, such as pricing securities and solving equilibrium models. This article provides analytical treatment of a general class of nonlinear transforms for processes with tractable conditional characteristic functions. We extend existing results on characteristic function-based transforms to a substantially wider class of nonlinear functions while maintaining low dimensionality by avoiding the need to compute the density function. We illustrate the applications of the generalized transform in pricing defaultable bonds with stochastic recovery. We also use the method to analytically solve a class of general equilibrium models with multiple goods and apply this model to study the effects of time-varying labor income risk on the equity premium.

This paper explores the implications of filtering and no-arbitrage for the maximum likelihood estimates of the entire conditional distribution of the risk factors and bond yields in Gaussian macro-finance term structure model (MTSM) when all yields are priced imperfectly. For typical yield curves and macro-variables studied in this literature, the estimated joint distribution within a canonical MTSM is nearly identical to the estimate from an economic-model-free factor vector-autoregression (factor-VAR), even when measurement errors are large. It follows that a canonical MTSM offers no new insights into economic questions regarding the historical distribution of the macro risk factors and yields, over and above what is learned from a factor-VAR. These results are rotation-invariant and, therefore, apply to many of the specifications in the literature.

We study the implications of inflation heterogeneity for individuals and firms through the lens of accounting research, applying measurement frameworks to the national accounting measurement of inflation. We first examine the systematic exposure of individuals in low‐income households to higher inflation relative to those in high‐income households. We show that this “inflation gap” is linked with future rising inequality in the form of widening gaps in healthcare insurance, education, homeownership, and credit card debt, as well as in a higher frequency of property crimes. We also provide an economic mechanism connecting the inflation gap with rising inequality, empirically demonstrating the role of basic goods in reducing the ability of individuals in the low‐income group to attain the social and economic implications that we study. In addition, we show a channel that connects the inflation gap to firms' profitability. Indeed, consistent with the inflation gap disadvantaging low‐income households mainly through basic goods, the inflation gap fluctuations are especially strongly connected to the profitability of firms operating in the energy and consumer staples sectors. Finally, we find that market power plays a role in this connection, where this link is even stronger for firms with high market power. Taking its findings together, the paper shows that differential inflation pressures have major implications for household well‐being and corporate profitability.

This paper quantifies how variation in economic activity and inflation in the United States influences the market prices of level, slope, and curvature risks in Treasury markets. We develop a novel arbitrage‐free dynamic term structure model in which bond investment decisions are influenced by output and inflation risks that are unspanned by (imperfectly correlated with) information about the shape of the yield curve. Our model reveals that, between 1985 and 2007, these risks accounted for a large portion of the variation in forward terms premiums, and there was pronounced cyclical variation in the market prices of level and slope risks.