A chaos theory and nonlinear dynamics approach to the analysis of financial series : a comparative study of Athens and London stock markets

This dissertation presents an effort to implement nonlinear dynamic tools adapted from chaos theory in financial applications. Chaos theory might be useful in explaining the dynamics of financial markets, since chaotic models are capable of exhibiting behaviour similar to that observed in empirical financial data. In this context, the scope of this research is to provide an insight into the role that nonlinearities and, in particular, chaos theory may play in explaining the dynamics of financial markets. From a theoretical point of view, the basic features of chaos theory, as well as, the rationales for bringing chaos theory to the attention of financial researchers are discussed. Empirically, the fundamental issue of determining whether chaos can be observed in financial time series is addressed. Regarding the latter, empirical literature has been controversial. A quite exhaustive analysis of the existing literature is provided, revealing the inadequacies in terms of methodology and the testing framework adopted, so far. A new "multiple testing" methodology is developed combining methods and techniques from the fields of both Natural Sciences and the Economics, most of which have not been applied to financial data before. A serious effort has been made to fill, as much as possible, the gap which results from the lack of a proper statistical framework for the chaotic methods. To achieve this the bootstrap methodology is adopted. The empirical part of this work focuses on the comparison of two markets with different levels of maturity; the Athens Stock Exchange (ASE), an emerging market, and London Stock Exchange (LSE). Our aim is to determine whether structural differences exist in these markets in terms of chaotic dynamics. In the empirical level we find nonlinearities in both markets by the use of the BDS test. R/S analysis reveals fractality and long term memory for the ASE series only. Chaotic methods, such as the correlation dimension (and related methods and techniques) and the largest Lyapunov exponent estimation, cannot rule out a chaotic explanation for the ASE market, but no such indication could be found for the LSE market. Noise filtering by the SVD method does not alter these findings. Alternative techniques based on nonlinear nearest neighbour forecasting methods, such as the "piecewise polynomial approximation" and the "simplex" methods, support our aforementioned conclusion concerning the ASE series. In all, our results suggest that, although nonlinearities are present, chaos is not a widespread phenomenon in financial markets and it is more likely to exist in less developed markets such as the ASE. Even then, chaos is strongly mixed with noise and the existence of low-dimensional chaos is highly unlikely. Finally, short-term forecasts trying to exploit the dependencies found in both markets seem to be of no economic importance after accounting for transaction costs, a result which supports further our conclusions about the limited scope and practical implications of chaos in Finance

Minoan pre-palatial sealstones in their economic and social context : a study based on the new material from Archanes-Phourni.

Sealstones are one of the most important types of artifacts discovered in the Aegean Bronze Age. Their practical use for recording and administrating purposes, their association with identity, prestige and social status, their possible religious or ritual connotations speak clearly for their importance and value. The fact that they are deposited, among other artifacts in tombs, accompanying their owners, demonstrate this value not only in life but also in death. Especially in the pre-palatial period in Crete a large number of seals have come to light, coming mostly from mixed contexts in the Mesara and Asterousia, in south Crete. The Minoan pre-palatial sealstones from Archanes-Phourni comprise an important corpus of artifacts for many reasons. They come from a site in the North of the island, in contrast to the majority of pre-palatial seals. The excavation and recording techniques used offer the opportunity to study the seals in their context, which is dated with relative certainty. The study of these seals, in comparison with the published ones from the south of the island, may offer significant information about important aspects of life in this period. The examination of materials, shapes, motifs, style groups and consumption patterns of seals may present us with useful insights about craft specialization and technology, internal and external exchange, economic organization and administration, religion and ritual, social differentiation and organization in the pre-palatial period. The study of this multiple and complex role of sealstones can offer us valuable information about the period before the first palaces

Long-term dependence in exchange rates

The extent to which exchange rates of four major currencies against the Greek Drachma exhibit long-term dependence is investigated using a R/S analysis testing framework. We show that both classic R/S analysis and the modified R/S statistic if enhanced by bootstrapping techniques can be proven very reliable tools to this end. Our findings support persistence and long-term dependence with non-periodic cycles for the Deutsche Mark and the French Franc series. In addition a noisy chaos explanation is favored over fractional Brownian motion. On the contrary, the US Dollar and British Pound were found to exhibit a much more random behavior and lack of any long-term structure

Molecular mimicry in the assembly of chromatin protein complexes

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KDM1A microenvironment, its oncogenic potential, and therapeutic significance

The lysine-specific histone demethylase 1A (KDM1A) was the first demethylase to challenge the concept of the irreversible nature of methylation marks. KDM1A, containing a flavin adenine dinucleotide (FAD)-dependent amine oxidase domain, demethylates histone 3 lysine 4 and histone 3 lysine 9 (H3K4me1/2 and H3K9me1/2). It has emerged as an epigenetic developmental regulator and was shown to be involved in carcinogenesis. The functional diversity of KDM1A originates from its complex structure and interactions with transcription factors, promoters, enhancers, oncoproteins, and tumor-associated genes (tumor suppressors and activators). In this review, we discuss the microenvironment of KDM1A in cancer progression that enables this protein to activate or repress target gene expression, thus making it an important epigenetic modifier that regulates the growth and differentiation potential of cells. A detailed analysis of the mechanisms underlying the interactions between KDM1A and the associated complexes will help to improve our understanding of epigenetic regulation, which may enable the discovery of more effective anticancer drugs

Nonlinear time-series analysis of the Greek exchange-rate market

Using concepts from the theory of chaos and nonlinear dynamical systems, a time-series analysis is performed on four major currencies against the Greek Drachma. The R/S analysis provided evidence for fractality due to noisy chaos in only two of the data series, while the BDS test showed that all four systems exhibit nonlinearity. Correlation dimension and related tests, as well as Lyapunov exponents, gave consistent results, which did not rule out the possibility of deterministic chaos for the two possibly fractal series, rejecting though the occurrence of a simple low-dimensional attractor, while the other two series seemed to have followed a behavior close to that of a random signal. SVD analysis, used to filter away noise, strongly supported the above findings and provided reliable evidence for the existence of an underlying system with a limited number of degrees-of-freedom only for those series found to exhibit fractality, while it revealed a noise domination over the remaining two. These results were further confirmed through a forecasting attempt using artificial neural networks

Well placement optimization in a given reservoir and production data history matching

Diploma Thesis ProjectSummarization: The current diploma thesis project focuses in utilizing the ECLIPSE reservoir simulation software to optimize the well placement processes in a given reservoir and the history matching processes of the simulation model data with the history data that accompany the simulation model. The optimization processes mentioned above will be conducted on the simulation model built for a block that is part of Gullfaks reservoir in the North Sea, Norway. PlanOpt and SimOpt are modules of ECLIPSE reservoir simulation software, PlanOpt is used to optimize the well placement processes and SimOpt is used to optimize the history matching processes of the simulation model data with the history data that accompany the simulation model. As far as well placement optimization is concerned, the already existing production wells of the simulation model will be discarded and by utilizing the well placement optimization software, PlanOpt, a less or equal number of production wells will be placed on the simulation model and will be scheduled to operate for the same simulation period that the initial simulation model is operating, aiming finally to achieve equal or higher cumulative oil production than the initial simulation model at the end of the simulation period. SimOpt will be used to reduce the mismatch between the production data of the simulation model and the real production data that were reported during the operation of the wells on the field. Several reservoir parameters will be set to vary within a range and at the end of the optimization processes SimOpt will calculate the values of the parameters chosen which produce the least possible mismatch between the real production data and the data resulted from the simulation model. Since there are different types production data that are going to be matched, a study will be conducted of whether the type of production data which are going to be matched in each different simulation run of SimOpt, affect the resulted matching at the end of each optimization run