Financial time series analysis : Chaos and neurodynamics approach

This work aims at combining the Chaos theory postulates and Artificial Neural Networks classification and predictive capability, in the field of financial time series prediction. Chaos theory, provides valuable qualitative and quantitative tools to decide on the predictability of a chaotic system. Quantitative measurements based on Chaos theory, are used, to decide a-priori whether a time series, or a portion of a time series is predictable, while Chaos theory based qualitative tools are used to provide further observations and analysis on the predictability, in cases where measurements provide negative answers. Phase space reconstruction is achieved by time delay embedding resulting in multiple embedded vectors. The cognitive approach suggested, is inspired by the capability of some chartists to predict the direction of an index by looking at the price time series. Thus, in this work, the calculation of the embedding dimension and the separation, in Takens‘ embedding theorem for phase space reconstruction, is not limited to False Nearest Neighbor, Differential Entropy or other specific method, rather, this work is interested in all embedding dimensions and separations that are regarded as different ways of looking at a time series by different chartists, based on their expectations. Prior to the prediction, the embedded vectors of the phase space are classified with Fuzzy-ART, then, for each class a back propagation Neural Network is trained to predict the last element of each vector, whereas all previous elements of a vector are used as features.

Talangfabriken : Om organisation av kunskap och kreativitet i skivindustrin

The purpose of this dissertation is to describe, explain and understand how record companies identify and develop new music and new talent. The analysis is carried out on three levels: individual, organizational and sector level. In a record company, this task formally goes to A&R (Artist and Repertoire). This dissertation takes its point of departure in how the capacity for discovering new talent can be understood in terms of knowledge, creativity and competence and how this capacity is affected in the meeting between the record company and the industry. The theoretical framework of the dissertation spans two sociological fields: the sociology of organizations and the sociology of knowledge. While it takes its organizational starting point in the Knowledge Company Approach, it employs a practice-based approach to discuss knowledge. I argue that within the Knowledge company approach there are two contrasting ways to understand knowledge; a distinction is made between knowledge- and creativity-intensive enterprises. The results show that the record industry’s polarized structure can be seen as a result of the Knowledge Company’s typical problems. The A&R’s work is described as including two phases, one intuitive and one analytical. The intuitive assessment is direct, unconscious and without reflection. This ability has been described as "intuition" and "gut feeling". The analytical phase adds analysis and reflection based on knowledge. The results from the interviews with A&R’s reveal the limit of formal and explicit knowledge not only in the choice of music but also in the marketing strategies. The overarching picture is one in which record companies move in a space characterized by tension between dichotomous forces – art and commercialism, creativity and knowledge, culture and economy, chaos and order, but where opposite poles are not mutually exclusive but complementary.