Principal component and second generation wavelet analysis of Treasury yield curve evolution

Prices of U.S. Treasury securities vary over time and across maturities. When the market in Treasurys is sufficiently complete and frictionless, these prices may be modeled by a function time and maturity. A cross-section of this function for time held fixed is called the yield curve; the aggregate of these sections is the evolution of the yield curve. This dissertation studies aspects of this evolution. ^ There are two complementary approaches to the study of yield curve evolution here. The first is principal components analysis; the second is wavelet analysis. In both approaches both the time and maturity variables are discretized. In principal components analysis the vectors of yield curve shifts are viewed as observations of a multivariate normal distribution. The resulting covariance matrix is diagonalized; the resulting eigenvalues and eigenvectors (the principal components) are used to draw inferences about the yield curve evolution. ^ In wavelet analysis, the vectors of shifts are resolved into hierarchies of localized fundamental shifts (wavelets) that leave specified global properties invariant (average change and duration change). The hierarchies relate to the degree of localization with movements restricted to a single maturity at the base and general movements at the apex. Second generation wavelet techniques allow better adaptation of the model to economic observables. Statistically, the wavelet approach is inherently nonparametric while the wavelets themselves are better adapted to describing a complete market. ^ Principal components analysis provides information on the dimension of the yield curve process. While there is no clear demarkation between operative factors and noise, the top six principal components pick up 99% of total interest rate variation 95% of the time. An economically justified basis of this process is hard to find; for example a simple linear model will not suffice for the first principal component and the shape of this component is nonstationary. ^ Wavelet analysis works more directly with yield curve observations than principal components analysis. In fact the complete process from bond data to multiresolution is presented, including the dedicated Perl programs and the details of the portfolio metrics and specially adapted wavelet construction. The result is more robust statistics which provide balance to the more fragile principal components analysis. ^

Changes in mass and nutrient content of wood during decomposition in a south Florida mangrove forest

1. Large pools of dead wood in mangrove forests following disturbances such as hurricanes may influence nutrient fluxes. We hypothesized that decomposition of wood of mangroves from Florida, USA (Avicennia germinans, Laguncularia racemosa and Rhizophora mangle), and the consequent nutrient dynamics, would depend on species, location in the forest relative to freshwater and marine influences and whether the wood was standing, lying on the sediment surface or buried. 2. Wood disks (8–10 cm diameter, 1 cm thick) from each species were set to decompose at sites along the Shark River, either buried in the sediment, on the soil surface or in the air (above both the soil surface and high tide elevation). 3. A simple exponential model described the decay of wood in the air, and neither species nor site had any effect on the decay coefficient during the first 13 months of decomposition. 4. Over 28 months of decomposition, buried and surface disks decomposed following a two-component model, with labile and refractory components. Avicennia germinans had the largest labile component (18 ± 2% of dry weight), while Laguncularia racemosa had the lowest (10 ± 2%). Labile components decayed at rates of 0.37–23.71% month−1, while refractory components decayed at rates of 0.001–0.033% month−1. Disks decomposing on the soil surface had higher decay rates than buried disks, but both were higher than disks in the air. All species had similar decay rates of the labile and refractory components, but A. germinans exhibited faster overall decay because of a higher proportion of labile components. 5. Nitrogen content generally increased in buried and surface disks, but there was little change in N content of disks in the air over the 2-year study. Between 17% and 68% of total phosphorus in wood leached out during the first 2 months of decomposition, with buried disks having the greater losses, P remaining constant or increasing slightly thereafter. 6. Newly deposited wood from living trees was a short-term source of N for the ecosystem but, by the end of 2 years, had become a net sink. Wood, however, remained a source of P for the ecosystem. 7. As in other forested ecosystems, coarse woody debris can have a significant impact on carbon and nutrient dynamics in mangrove forests. The prevalence of disturbances, such as hurricanes, that can deposit large amounts of wood on the forest floor accentuates the importance of downed wood in these forests.

Possible climate change impacts on the hydrological and vegetative character of Everglades National Park, Florida

The increasing threat of global climate change is predicted to have immense influences on ecosystems worldwide, but could be particularly severe to vulnerable wetland environments such as the Everglades. This work investigates the impact global climate change could have on the hydrologic and vegetative makeup of Everglades National Park (ENP) under forecasted emissions scenarios. Using a simple stochastic model of aboveground water levels driven by a fluctuating rainfall input, we link across ENP a location's mean depth and percent time of inundation to the predicted changes in precipitation from climate change. Changes in the hydrologic makeup of ENP are then related to changes in vegetation community composition through the use of relationships developed between two publically available datasets. Results show that under increasing emissions scenarios mean annual precipitation was forecasted to decrease across ENP leading to a marked hydrologic change across the region. Namely, areas were predicted to be shallower in average depth of standing water and inundated less of the time. These hydrologic changes in turn lead to a shift in ENP's vegetative makeup, with xeric vegetative communities becoming more numerous and hydric vegetative communities becoming scarcer. Noticeably, the most widespread of vegetative communities, sawgrass, decreases in abundance under increasing emissions scenarios. These results are an important indicator of the effects climate change may have on the Everglades region and raise important management implications for those seeking to restore this area to its historical hydrologic and vegetative condition.