Diese Dissertation ist in drei Kapitel sowie eine Einleitung unterteilt. Die Einleitung führt in das Themengebiet ein, fasst die Kapitel zusammen und zeigt deren Zusammenhänge auf. Jedes Kapitel beschäftigt sich mit der Analyse von Finanzzeitreihen. Dabei wird insbesondere den „stylized...

In this paper, expected utility, defined by a Taylor series expansion around expected wealth, is maximized. The coefficient of relative risk aversion (CRRA) that is commensurate with a 100% investment in the risky asset is simulated. The following parameters are varied: the riskless return, the...

We derive a Gaussian approximation result for the maximum of a sum of high dimensional random vectors. Specifically, we establish conditions under which the distribution of the maximum is approximated by that of the maximum of a sum of the Gaussian random vectors with the same covariance...

We derive a central limit theorem for the maximum of a sum of high dimensional random vectors. More precisely, we establish condi- tions under which the distribution of the maximum is approximated by the maximum of a sum of the Gaussian random vectors with the same covariance matrices as the...

We develop a new direct approach to approximating suprema of general empirical processes by a sequence of suprema of Gaussian processes, without taking the route of approximating empirical processes themselves in the sup-norm. We prove an abstract approximation theorem that is applicable to a...

This paper extends the Bayesian Model Averaging framework to panel data models where the lagged dependent variable as well as endogenous variables appear as regressors. We propose a Limited Information Bayesian Model Averaging (LIBMA) methodology and then test it using simulated data. Simulation...

In this paper we derive the asymptotic behaviour of the survival function of both random sum and random maximum of log-normal risks. As for the case of finite sum and maximum investigated in Asmussen and Rojas-Nandayapa (2008) also for the more general setup of random sums and random maximum the...

We obtain two characterizations of the Gaussian distribution on a Hilbert space from samples of random size.

We derive forecast confidence bands using a Global Projection Model covering the United States, the euro area, and Japan. In the model, the price of oil is a stochastic process, interest rates have a zero floor, and bank lending tightening affects the United States. To calculate confidence...

This paper presents the design aspects and probabilistic approach for the generation reliability evaluation of an alternative resource: municipal waste water (MWW) based micro-hydro power plant (MHPP). Annual and daily flow duration curves have been obtained for design, installation,...

In this paper, we construct an intermediate distribution linking the Gaussian and the Cauchy distribution. We provide the probability density function and the corresponding characteristic function of the intermediate distribution. Because many kinds of distributions have no moment, we introduce...

There is strong evidence that interest rates and bond yield movements exhibit both stochastic volatility and unanticipated jumps. The presence of frequent jumps makes it natural to ask whether there is a premium for jump risk embedded in observed bond yields. This paper identifies a class of...

One approach to oil markets is to treat oil as an asset, besides its role as a commodity. Speculative and nonspeculative activity by investors in the derivatives markets could be responsible for a sizable increase in oil prices. This paper recognizes both the consumption and investment aspects...

We propose new measures of both risk and anticipated return that incorporate the effects of skewness and heavy tails from a financial return’s probability distribution. Our cosine-based analysis, which involves maximizing the marginal Shannon information associated with the Fourier transform...

Previous early-warning systems (EWSs) for currency crises have relied on models that require a priori dating of crises. This paper proposes an alternative EWS, based on a Markov-switching model, which identifies and characterizes crisis periods endogenously; this also allows the model to utilize...

A stochastic volatility model where volatility was driven solely by a latent variable called news was estimated for three stock indices. A Markov chain Monte Carlo algorithm was used for estimating Bayesian parameters and filtering volatilities. Volatility persistence being close to one was...

It has been found that the structure of complex network has significant influence on the condensation of particles and the equilibrium state of particles is dynamical. We study here the fluctuation of particles on each individual node at equilibrium status and find that the particle...

Within a unified theory for stocks and corporate bonds, based on dynamic optimization by investors, this paper derives analytical expressions for the momentary distributions of expected price, respectively known to approximate lognormal with systematic deviations (high peak, fat tail) and double...

The Normal Inverse Gaussian (NIG) distribution recently introduced by Barndorff-Nielsen (1997) is a promising alternative for modelling financial data exhibiting skewness and fat tails. In this paper we explore the Bayesian estimation of NIG-parameters by Markov Chain Monte Carlo Methods. --...

A Gaussian version of the iterative proportional fitting procedure (IFP-P) was applied by Speed and Kiiveri to solve the likelihood equations in graphical Gaussian models. The calculation of the maximum likelihood estimates can be seen as the problem to find a Gaussian distribution with...

The statistical properties of daily closing futures prices for nine commodities are studied. Two hypotheses are examined: Price changes are normally distributed, and prices follow a random walk process. Normality is tested by estimating kurtosis, the R/S statistic, and characteristic exponents....