Liberty Bond rally (Detroit, Mich.)

In front of Detroit Opera House

Big adding machine showing total subscription, Liberty Bond rally (Detroit, Mich.)

Detroit's quota $55,494,413--$4,939,400 oversubscribed one...

Liberty bond rally (Detroit, Mich.)

Michigan Avenue at Woodward Avenue

The Federalist, on the new Constitution, written in 1788,

Mode of access: Internet.

Spencer Kellogg Brown, his life in Kansas and his death as a spy, 1842-1863 : as disclosed in his diary.

Mode of access: Internet.

Mrs. Delany (Mary Granville) a memoir, 1700-1788;

Mode of access: Internet.

Main currents in nineteenth century literature /

Vols. I, II and V translated by Diana White and Mary Morison; vols. III, IV ad VI, by Mary Morison.

Mexico and Texas in 1842

El mapa publicado por George Folsom en Nueva York representa con detalle los fenómenos geográficos como costas, hidrografía, orografía, poblaciones, limites administrativos y toponimia del territorio nacional.

The chess player / by George Walker; to which are added the three games played at one and the same time by Philidor; sixty openings, mates and situations, by W. S. Kenny, with remarks, anecdotes, &c. &c., and an explanation of the round chess board.

Mode of access: Internet.

Determinants of listed property trust bond ratings : Australian evidence

Using artificial neural networks (ANN) and ordinal regression (OR) as alternative methods to predict LPT bond ratings, we examine the role that various financial and industry variables have on Listed Property Trust (LPT) bond ratings issued by Standard and Poor’s from 1999-2006. Our study shows that both OR and ANN provide robust alternatives to rating LPT bonds and that there are no significant differences in results between the two full models. OR results show that of the financial variables used in our models, debt coverage and financial leverage ratios have the most profound effect on LPT bond ratings. Further, ANN results show that 73.0% of LPT bond rating is attributable to financial variables and 23.0% to industry-based variables with office LPT sector accounting for 2.6%, retail LPT 10.9% and stapled management structure 13.5%.

Why common factors in international bond returns are not so common

This paper analyzes the common factor structure of US, German, and Japanese Government bond returns. Unlike previous studies, we formally take into account the presence of country-specific factors when estimating common factors. We show that the classical approach of running a principal component analysis on a multi-country dataset of bond returns captures both local and common influences and therefore tends to pick too many factors. We conclude that US bond returns share only one common factor with German and Japanese bond returns. This single common factor is associated most notably with changes in the level of domestic term structures. We show that accounting for country-specific factors improves the performance of domestic and international hedging strategies.