Return to search

Applications of Time Series in Finance and Macroeconomics

This dissertation contains three applications of time series in finance and macroeconomics. The first essay compares the cumulative returns for stocks and bonds at
investment horizons from one to ten years by using a test for spatial dominance.
Spatial dominance is a variation of stochastic dominance for nonstationary variables.
The results suggest that for investment horizons of one year, bonds spatially dominate
stocks. In contrast, for investment horizons longer than five years, stocks spatially
dominate bonds. This result is consistent with the advice given by practitioners
to long term investors of allocating a higher proportion of stocks in their portfolio
decisions.
The second essay presents a method that allows testing of whether or not an
asset stochastically dominates the other when the time horizon is uncertain. In this
setup, the expected utility depends on the distribution of the value of the asset as
well as the distribution of the time horizon, which together form the weighted spatial
distribution. The testing procedure is based on the Kolmogorov Smirnov distance
between the empirical weighted spatial distributions. An empirical application is
presented assuming that the event of exit time follows an independent Poisson process
with constant intensity.
The last essay applies a dynamic factor model to generate out-of-sample forecasts for the inflation rate in Mexico. Factor models are useful to summarize the
information contained in large datasets. We evaluate the role of using a wide range of
macroeconomic variables to forecast inflation, with particular interest on the importance of using the consumer price index disaggregated data. The data set contains 54
macroeconomic series and 243 consumer price subcomponents from 1988 to 2008. The
results indicate that factor models outperform the benchmark autoregressive model at
horizons of one, two, four and six quarters. It is also found that using disaggregated
price data improves forecasting performance.

Identiferoai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2010-05-7803
Date2010 May 1900
CreatorsIbarra Ramirez, Raul
ContributorsJansen, Dennis W.
Source SetsTexas A and M University
Languageen_US
Detected LanguageEnglish
Typethesis, text
Formatapplication/pdf

Page generated in 0.0026 seconds