Περίληψη
The present dissertation is oriented towards the empirical application of certain
models and econometric techniques drawn from recent developments in the
financial econometric literature. The aims of this project are targeted a) in testing the
proposed financial models to financial data sets, b) in enriching and strengthen the
analysis by inducing new aspects into the proposed methodologies, and finally c) in
producing inferences and comparing the outcomes with other results existing in
many related empirical applications.
Each chapter in the present dissertation corresponds a different section of applied
econometrics and therefore three empirical projects are carried out. Those are : a)
the estimation and test of the joint conditional CAPM model introduced by Morelli
(2011), b) the detection of fractional cointegrating relations using the variance ratio
approach introduced by Nielsen (2010), and finally c) a comparative analysis of
different volatility models, aiming a) th ...
The present dissertation is oriented towards the empirical application of certain
models and econometric techniques drawn from recent developments in the
financial econometric literature. The aims of this project are targeted a) in testing the
proposed financial models to financial data sets, b) in enriching and strengthen the
analysis by inducing new aspects into the proposed methodologies, and finally c) in
producing inferences and comparing the outcomes with other results existing in
many related empirical applications.
Each chapter in the present dissertation corresponds a different section of applied
econometrics and therefore three empirical projects are carried out. Those are : a)
the estimation and test of the joint conditional CAPM model introduced by Morelli
(2011), b) the detection of fractional cointegrating relations using the variance ratio
approach introduced by Nielsen (2010), and finally c) a comparative analysis of
different volatility models, aiming a) the comparison of their volatility forecasting
potentials under various forecasting horizons, and b) the detection of possible
statistically significant volatility - return relations. Specifically :
Chapter 1 follows the approach of Morelli (2011) and carries over the estimation and
test of the joint conditional CAPM model. The analysis uses the monthly returns of
the 25 Fama-French portfolios in the period from July 1926 to June 2008 to evolve
in two phases. The first part of the analysis through the application of four different
methodologies estimates corresponding versions of the time varying beta
coefficients series, while the second based on those latter estimates tests the
statistical significance of the beta - return relation, especially when the last is
conditioned upon the sign of excess market returns.
Note that the above methodologies correspond a) the volatility approach, where conditional covariances and variances that define the notion of conditional beta are
modeled as ARCH, GARCH, FIGARCH and FIEGARCH processes, b) the
recursive OLS approach, and c) the Kalman filter analysis, where two different
assumptions have been applied on the definition of the state equation. Those are a)
the random walk approach and the b) AR(1) alternative.
In spite of differences existing in all four versions of the estimated time varying beta
coefficients series, results in all four procedures reject the conditional and the joint
conditional CAPM versions, while results appear robust either when the analysis
examine the full sample case or two equal sub-samples.
The key feature of chapters 2 and 3 evolves around the idea of long memory that is
detected both in cointegrating relations and volatility return series. From the initial
work of Granger (1981) to nowadays there has been an increasing amount of
evidence supporting the presence of long memory in different financial and
macroeconomic series, with the list including data over exchange rates, interest
rates, indexes of production, consumption, unemployment, estimated series on
volatility and many others.
Chapter 2 uses daily data from the European interbank money market to examine
the term structure theory on four interest rates series. As it is well known
expectations hypothesis suggests the existence of long run equilibrium relations
among interest rates of different maturities. The relations imply the stationary nature
of spreads, while traditionally the theory is verified through cointegration analysis.
However, the restrictiveness of I(0)/I(1) dichotomy that is followed in traditional
cointegration analysis and the possibility that the time series in question may be
fractionally integrated, forces the present application to examine the cointegration
rank through fractionally integrated systems. Indeed chapter 2 follows the non parametric variance ratio test of Nielsen (2010) and applies such a fractional
analysis, while at the same time and for comparative reasons the chapter expands
with the estimation of parametric tests of Johansen (1998,1991) and the fractional
alternative of Breitung and Hassler (2002).
Although results on the cointegration rank differ significantly between parametric
and non parametric tests, however no specific outcome can be considered generally
true for the parametric alternatives, since both procedures end up with different
results when different lag augmentations are being applied. Finally the paper
proceeds with an informal comparison of the estimated and hypothesized
cointegrating space, given that the variance ratio procedure provides a consistent
estimator of the last.[...]
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