The United States Department of Agriculture has issued statistics on prices received by farmers since 1866. Beginning in 1924, prices received were collected as of the middle of the month instead of the first of the month. In this research analysis both univariate and transfer function...

This dissertation consists of two parts. The first part introduces a neural network approach that is used to forecast the conditional probability density function of asset returns. The model is unified with the idea of Arbitrage Pricing Theory (APT). In the second part, an algorithm called...

Under the normal conditions of construction contracts, the client is obliged to pay the contractor in monthly instalments. The amount of each instalment is based on the value of construction work actually produced in the previous month and forecasts are needed in advance of the likely value of...

Studies of the value relevance of accounting number in capital market research are consistent with the simple view that, in equilibrium, book values are equal to or have some long-term relationship with market values, and that market returns are related to book returns. This dissertation...

Time series forecasting is an important area of forecasting in which past observations of the same variable are collected and analyzed to develop a model describing the underlying relationship. The model is then used to extrapolate the time series into the future. This modeling approach is...

The study of intraindividual variability pervades empirical inquiry in virtually all subdisciplines of psychology. The statistical analysis of multivariate time-series data - a central product of intraindividual investigations - requires special modeling techniques. The dynamic factor model...

In this dissertation three essays were presented. In the first two essays we measure theconsumer welfare changes caused by U.S. meat price changes. In the third essay thedynamic structure of international gasoline prices using the time series methodology isinvestigated.In chapter II, we...

This paper provides a significant numerical evidence for out-of-sample forecasting ability of linear Gaussian interest rate models with unobservable underlying factors. We calibrate one, two and three factor linear Gaussian models using the Kalman filter on two different bond yield data sets and...

The objective of this thesis is to estimate the natural gas component of the All Urban Consumer Price Index (CP-U) using time series forecasting models. Being able to accurately predict future CPI-U values is important because it allows portfolio managers and financial institutions to properly...

Hochdimensionale Regressionsprobleme, die sich dynamisch entwickeln, sind in zahlreichen Bereichen der Wissenschaft anzutreffen. Die Dynamik eines solchen komplexen Systems wird typischerweise mittels der Zeitreiheneigenschaften einer geringen Anzahl von Faktoren analysiert. Diese Faktoren...