This thesis introduces a novel theoretical option pricing ensemble framework to improve the bias and variance of option pricing models, especially those based on Levy Processes. In particular, we present a completely new, yet very general theoretical framework to calibrate and combine several option pricing models using ensemble methods. This framework has four main steps: general option pricing tasks, ensemble generation, ensemble pruning and ensemble integration. The modularity allows for a exible implementation in terms of asset classes, base models, pricing techniques and ensemble architecture.

Abstract This diploma thesis treats about the latest technologies in the field of self-service BI from Microsoft Corporation. The main goal of this work is to analyze the Microsoft self-service BI solutions, to describe the benefits and advantages of this technology and to show examples with real data in Microsoft self-services BI tools. To achieve the goal, the internet resources, recommended literature, and the software applications PowerPivot and PowerView (Excel 2013) are59 used. In its first part this thesis describes the basic characteristics and technology of classical BI solutions. The second part examines the actual self-service BI solution and its usability. And then analyzes the advantages and benefits compared to conventional technologies. Finally, in its last section describes self-service BI solutions, the DAX language used in PowerPivot and shows example reports with real data from banking sector. The key benefit of this diploma is the verification of the usability and advantages of self-service BI by using Microsoft self-service BI products and tools.

This thesis deals with the extension of Office application Microsoft Excel -- PowerPivot program. First, the thesis focuses on the topic of the actual Business Intelligence (BI) and compares the classical BI approach and self-service BI approach. In the first part are dis-cussed current trends in BI. The second and main part is focused to the PowerPivot. Grad-ually are mentioned benefits and news in PowerPivot on the examples compared to classical analysis in Excel. In the initial description of the features are also instructions for installing the program and its news in version 2013. An important chapter is focused to the DAX expressions and all the calculations that can be implemented in PowerPivot. Separate chapters are devoted to data import and connection with MS SharePoint Server. As an ex-ample, is introduced the calculation of the ABC analysis to classify products, used mainly in logistics. The last part deals with implementation of applications in PowerPivot for MBI model (Management of Business Informatics).

Ο σκοπός της παρούσας διπλωματικής εργασίας είναι η δημιουργία μιας μεθόδου για την εξαγωγή αποδοτικών και ερμηνεύσιμων επενδυτικών κανόνων με χρήση μεθόδων υπολογιστικής νοημοσύνης. Οι επενδυτικοί αυτοί κανόνες εξάγονται αυτόματα από το σύστημα και υποδεικνύουν τη στρατηγική που πρέπει να ακολουθήσει ένας χρήστης. Αποκαλύπτουν το συσχετισμό των εισόδων και παρέχουν πληροφορίες για κερδοφόρες επενδυτικές στρατηγικές. Η υπολογιστική νοημοσύνη (computational intelligence) αποτελεί παρακλάδι της τεχνητής νοημοσύνης το οποίο περιλαμβάνει τον σχεδιασμό και την ανάπτυξη θεωριών και μεθόδων, βασιζόμενη στην κατανόηση της βιολογίας και της προσπάθειας για εφαρμογή σε προβλήματα του πραγματικού κόσμου. Ένα σύστημα είναι υπολογιστικά ευφυές όταν: ασχολείται μόνο με αριθμητικά (χαμηλού επιπέδου) δεδομένα, έχει συστατικά αναγνώρισης προτύπων, δεν χρησιμοποιεί γνώσεις στην μορφή της τεχνητή νοημοσύνης και επιπλέον, εμφανίζει i) υπολογιστική προσαρμοστικότητα, ii) υπολογιστική ανοχή σε σφάλματα, iii) επιτάχυνση που προσεγγίζει την ανθρώπινη, και iv) τα ποσοστά σφάλματός του προσεγγίζουν την ανθρώπινη απόδοση. Οι αλγόριθμοι της υπολογιστικής νοημοσύνης αποτελούνται από μοντέλα που εκπαιδεύονται από τα παραδείγματα με την βοήθεια ενός δασκάλου (επιβλεπόμενη μάθηση) και μοντέλα τα οποία προσαρμόζονται μόνα τους (μη επιβλεπόμενη μάθηση). Το πρόβλημα στις παρούσες προσεγγίσεις για την πρόβλεψη οικονομικών δεικτών εντοπίζεται στην μη ερμηνευσιμότητα των αποτελεσμάτων. Ενώ υπάρχουν δυνατά υπολογιστικά μοντέλα, όπως οι γενετικοί αλγόριθμοι και οι μηχανές διανυσμάτων υποστήριξης, τα αποτελέσματα τους δεν είναι ερμηνεύσιμα. Από την άλλη τα μοντέλα της ασαφούς λογικής ενώ παρουσιάζουν ερμηνεύσιμα αποτελέσματα δεν έχουν την δύναμη να παράγουν αποδοτικούς κανόνες. Το μοντέλο που προτείνεται σε αυτή την εργασία συνδυάζει τις τρεις προαναφερθείσες μεθόδους ονομάζεται ESVM-Fuzzy Inference Trader. Το προτεινόμενο μοντέλο χρησιμοποιείται για την πρόβλεψη των δεικτών DAX και FTSE 100. Τα αποτελέσματα του ESVM Fuzzy Inference Trader ξεπέρασαν σε απόδοση τις παραδοσιακές μεθόδους καθώς και μια εξελιγμένη τεχνική μηχανικής μάθησης. / The purpose of the present thesis is to develop a method for extracting efficient and interpretable investment rules, using methods of Computational Intelligence. The investment rules are automatically extracted from the system and suggest the strategy to be followed by a user. They are revealing the correlation between inputs and provide information on profitable investment strategies. Computational intelligence (CI) constitutes a subbranch of Artificial Intelligence (AI) that includes the design and development of theories and methods with a sound biological understanding alongside their application to solve real world problems. A system is computationally intelligent when it deals with only numerical (low level) data, has pattern recognition components, does not use knowledge in the AI sense and additionally when it (begins to) exhibit i) computational adaptivity, ii) computational fault tolerance, iii) speed approaching human-like turn around and iv) error rates that approximate human performance. The CI algorithms consist of models that are trained from examples with the aid of a tutor (supervised learning) and models that are self-adapted (unsupervised learning) The problem in the current approaches for predicting economic indicators is the non-interpretability of results. While there are strong computational models, such as genetic algorithms and support vector machines their results are not interpretable. On the other hand fuzzy logic models create interpretable results, but lack the power to produce efficient rules. The model proposed in this paper combines the three previous methods is called ESVM-Fuzzy Inference Trader. The proposed model is used to predict the indices DAX and FTSE 100. The results of ESVM Fuzzy Inference Trader outperformed traditional methods as well as an advanced machine learning technique.

Thesis (doctoral)--Universität, Augsburg, 2004. / Includes bibliographical references and index (p. [215]-223) and index.

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In der Studie nach dem Dresdner Modell für die Analyse von Management-Kommunikation (DMAMK) werden Reden von Vorstandsvorsitzenden börsennotierter Gesellschaften und Familienunternehmen im Hinblick auf Verständlichkeit, rhetorische Fähigkeiten, ihre Übereinstimmung mit der Corporate Identity des Unternehmens und die Inszenierung des Auftritts analysiert. Unter der Leitung von Dr. Evelyn Koch werteten Studierende im Seminar „Managementkommunikation“ Unternehmenspräsentationen aus. Dr. Evelyn Koch, in deren Verantwortung der thematische Schwerpunkt der rhetorischen Gestaltung lag, wurde unterstützt von Prof. Dr. Alexander Lasch (Unternehmenskommunikation) und Dr. Regina Bergmann (Verständlichkeit). Die Studie wurde 2018 zum dritten Mal durchgeführt. Weitere Details finden Sie unter: https://www.gls-dresden.de/tag/dmamk/.

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Cortisol and dehydroepiandrosterone (DHEA) are steroids produced by the zona fasciculata (ZF) and reticularis (ZR), respectively, of the adrenal cortex. Both steroids are upregulated in response to adrenocorticotropic hormone (ACTH). Cortisol is a glucorticoid that is important in the regulation of inflammation and metabolism. DHEA is an adrenal androgen important in fetal growth and puberty but tends to decrease gradually after puberty in both men and women. DHEA has various effects on metabolism and immune function including inhibiting the effects of cortisol on some tissues. During the acute phase of stress, cortisol and DHEA rise due to an increase in ACTH released from the anterior pituitary. In contrast, during chronic stress, cortisol remains elevated but DHEA and ACTH levels decrease. Likewise, stress causes serum levels of IL-6 to increase. IL-6 increases cortisol release from the human and bovine adrenal cortex. IL-6 also decreases DHEA release from zona reticularis of the bovine adrenal gland. In humans the effect of IL-6 on DHEA production is still uncertain. To determine a possible mechanism of IL-6 on the zona fasciculata and reticularis, human H294R cells and bovine adrenal tissue were incubated in serum free medium containing IL-6, at various concentrations and incubation intervals. At the end of the incubation interval, mRNA or protein was extracted from the cells or tissue. Standard PCR, real time PCR, and western blot assays were used to determine the effects of IL-6 on the enzymes involved in cortisol and DHEA synthesis, steroidogenic factor-1 (SF-1), steroidogenic acute regulatory protein (StAR), and dosage sensitive sex reversal adrenal hypoplasia congenita critical region on the X chromosome, gene 1 (DAX-1). In human H295R cells and bovine zona fasciculata cells IL-6 caused an increase in SF-1, StAR, P450scc, 17α hydroxylase, 3β-hydroxysteroid dehydrogenase type 2 (3β HSD2), 21 hydroxylase, and 11β hydroxylase mRNA and protein. IL-6 caused DAX-1 mRNA and protein to decrease. These effects were manifest in a time dependent manner. Dose response treatments incubated for 60 min increased SF-1, StAR, P450scc, 17α hydroxylase, 3β HSD2, 21 hydroxylase, and 11β hydroxylase but there was not significant change between the different treatments of IL-6. The bovine zona reticularis stimulated with IL-6 showed a decrease in SF-1, StAR, P450scc, 17α hydroxylase, and 3β HSD2 with an increase in DAX-1 mRNA and protein. This response was manifest in a time dependent manner for both mRNA and protein, and the effect was dose-dependent for mRNA but not protein levels within the 60 min time period. These data provide a mechanism by which increased stress, physical or emotional, which increases IL-6 serum level, could increase cortisol and decrease DHEA. This would account for decreased immune function, increased blood pressure, and changes in metabolism.