Term structure estimation without using latent factors

A combination of observed and unobserved (latent) factors capture term structure dynamics. Information about these dynamics is extracted from observed factors without specifying or estimating any of the parameters associated with latent factors. Estimation is equivalent to fitting the moment conditions of a set of regressions, where no-arbitrage imposes cross equation restrictions on the coefficients. The methodology is applied to the dynamics of inflation and yields. Outside of the disinflationary period of 1979 through 1983, short-term rates move one for one with expected inflation, while bond risk premia are insensitive to inflation.

What's good for GM...? Using auto industry stock returns to forecast business cycles and test the Q-theory of investment

Business cycles ; General Motors Corporation ; Investments

Forecasting with the term structure: The role of no-arbitrage restrictions

No-arbitrage term structure models impose cross-sectional restrictions among yields and can be used to impose dynamic restrictions on risk compensation. This paper evaluates the importance of these restrictions when using the term structure to forecast future bond yields. It concludes that no cross-sectional restrictions are helpful, because cross-sectional properties of yields are easy to infer with high precision. Dynamic restrictions are useful, but can be imposed without relying on the no-arbitrage structure. In practice, the most important dynamic restriction is that the first principal component of Treasury yields follows a random walk. A simple model built around this assumption produces out-of-sample forecasts that are more accurate than those of a variety of alternative dynamic models.

Information in (and not in) the term structure

Standard approaches to building and estimating dynamic term structure models rely on the assumption that yields can serve as the factors. However, the assumption is neither theoretically necessary nor empirically supported. This paper documents that almost half of the variation in bond risk premia cannot be detected using the cross section of yields. Fluctuations in this hidden component have strong forecast power for both future short-term interest rates and excess bond returns. They are also negatively correlated with aggregate economic activity, but macroeconomic variables explain only a small fraction of variation in the hidden factor.

Sharpe ratios in term structure models

Conditional maximum Sharpe ratios implied by fully flexible four-factor and five-factor Gaussian term structure models are astronomically high. Estimation of term structure models subject to a constraint on their Sharpe ratios uncovers properties that hold for a wide range of Sharpe ratios. These robust properties include (a) an inverse relation between a bond????s maturity and its average Sharpe ratio; (b) between 15 and 20 percent of annual excess returns to bonds are predictable; and (c) variations in expected excess bond returns are driven by two factors. These factors operate at different frequencies. Nonrobust features include the mean level of the term structure. Unconstrained models imply that investors anticipated much of the decline of interest rates in the 1990s. Constrained models disagree.

From Geometric Intuition to Arithmetical Rigor: Teaching Analysis with Bolzano’s Original Text

In this paper I argue for the value of reading primary historical texts in mathematics courses. In particular, I show how close readings of Bolzano’s 1817 paper on the Intermediate Value Theorem in an introductory analysis course helps students understand the working use of fundamental analytic concepts and problems. I further argue that the philosophical purpose of reading primary texts is the “desedimentation” of knowledge, a process through which students come to understand the origins of mathematical concepts as solutions to historical problems

The Maryland House and Garden Pilgrimage as a Preservation Force in Maryland (1930-1994)

The Maryland House and Garden Pilgrimage (MHGP) is an organization which stages a series of house tours across Maryland during the first few weeks of May each year. While the MHGP\u27s by-laws define the organization as a fund raiser for preservation projects, the organization has a much broader impact on Maryland\u27s preservation community. After a discussion of the history of architectural tourism and of the MHGP, this thesis examines the impact of the MHGP, identifies trends in the annual tours, and speculates about the possible causes and solutions to these problems. Quantitative data gleaned from the records of the MHGP has been used to support the analyses. The final analysis reveals that the MHGP plays an important role in educating the public as well as raising money, and can continue its long history of success with a few organization changes

Term premia and interest rate forecasts in affine models

I find that the standard class of affine models produces poor forecasts of future changes in Treasury yields. Better forecasts are generated by assuming that yields follow random walks. The failure of these models is driven by one of their key features: the compensation that investors receive for facing risk is a multiple of the variance of the risk. This means that risk compensation cannot vary independently of interest rate volatility. I also describe and empirically estimate a class of models that is broader than the standard affine class. These 'essentially affine' models retain the tractability of the usual models, but allow the compensation for interest rate risk to vary independently of interest rate volatility. This additional flexibility proves useful in forming accurate forecasts of future yields.Government securities ; Econometric models ; Forecasting

Asymmetric cross-sectional dispersion in stock returns: evidence and implications

This paper documents that daily stock returns of both firms and industries are more dispersed when the overall stock market rises than when it falls. This positive relation is conceptually distinct from - and appears unrelated to - asymmetric return correlations. I argue that the source of the relation is positive skewness in sector-specific return shocks. I use this asymmetric behavior to explain a previously-observed puzzle: aggregate trading volume tends to be higher on days when the stock market rises than when it falls. The idea proposed here is that trading is more active on days when the market rises because on those days there is more non-market news on which to trade. I find that empirically, the bulk of the relation between volume and the signed market return is explained by variations in non-market volatility.Stock market ; Econometric models