Forecasting price movements in betting exchanges using Cartesian Genetic Programming and ANN

Since the introduction of betting exchanges in 2000, there has been increased interest of ways to monetize on the new technology. Betting exchange markets are fairly similar to the financial markets in terms of their operation. Due to the lower market share and newer technology, there are very few tools available for automated trading for betting exchanges. The in-depth analysis of features available in commercial software demonstrates that there is no commercial software that natively supports machine learned strategy development. Furthermore, previously published academic software products are not publicly obtainable. Hence, this work concentrates on developing a full-stack solution from data capture, back-testing to automated Strategy Agent development for betting exchanges. Moreover, work also explores ways to forecast price movements within betting exchange using new machine learned trading strategies based on Artificial Neuron Networks (ANN) and Cartesian Genetic Programming (CGP). Automatically generated strategies can then be deployed on a server and require no human interaction. Data explored in this work were captured from 1st of January 2016 to 17th of May 2016 for all GB WIN Horse Racing markets (total of 204GB of data processing). Best found Strategy agent shows promising 83% Return on Investment (ROI) during simulated historical validation period of one month (15th of April 2016 to 16th of May 2016)

Forecasting Stock Exchange Data using Group Method of Data Handling Neural Network Approach

The increasing uncertainty of the natural world has motivated computer scientists to seek out the best approach to technological problems. Nature-inspired problem-solving approaches include meta-heuristic methods that are focused on evolutionary computation and swarm intelligence. One of these problems significantly impacting information is forecasting exchange index, which is a serious concern with the growth and decline of stock as there are many reports on loss of financial resources or profitability. When the exchange includes an extensive set of diverse stock, particular concepts and mechanisms for physical security, network security, encryption, and permissions should guarantee and predict its future needs. This study aimed to show it is efficient to use the group method of data handling (GMDH)-type neural networks and their application for the classification of numerical results. Such modeling serves to display the precision of GMDH-type neural networks. Following the US withdrawal from the Joint Comprehensive Plan of Action in April 2018, the behavior of the stock exchange data stream and commend algorithms has not been able to predict correctly and fit in the network satisfactorily. This paper demonstrated that Group Method Data Handling is most likely to improve inductive self-organizing approaches for addressing realistic severe problems such as the Iranian financial market crisis. A new trajectory would be used to verify the consistency of the obtained equations hence the models' validity

Funcionamiento del trading algorítmico en los mercados de capitales

Trabajo final (Licenciatura en Administración con orientación en Finanzas)Propósito: este trabajo tiene como finalidad exponer información acerca del trading algorítmico y su relación con el mercado de capitales, el análisis técnico y fundamental, los activos financieros y sus derivados para todo aquel interesado en interiorizarse en el mundo de las finanzas. Metodología: se realizó una revisión sistemática de literatura, relevando 572 artículos acerca del trading algorítmico, publicados en el periodo 2015-2022. En la búsqueda se aplicaron criterios de exclusión, quedando un total de 29 artículos. Su análisis pertinente permitió contestar las preguntas de investigación y desarrollar la temática elegida. Además, se efectuaron entrevistas semi-estructuradas a personas trabajando en la operatoria de trading. Conclusiones: El trading algorítmico posee ventajas excepcionales sobre el trading discrecional. Entre ellas se destaca la capacidad de procesamiento superior que tiene una computadora que simplifica toda operación y reduce los tiempos empleados y por otro lado, elimina el lado emocional de la toma de decisiones del proceso de inversión. Limitaciones: En el protocolo de investigación se estableció la condición de seleccionar solo artículos de libre acceso y aceptar únicamente los artículos que hayan sido redactados en inglés o el español. Los idiomas de los textos que fueron dejados de lado son francés, alemán, portugués y ucraniano. Originalidad-Valor: El valor del trabajo radica en que se aborda una temática novedosa en el campo de las finanzas por medio de dos metodologías que aportan por un lado información de calidad y con respaldo científico y por otro lado la experiencia y conocimientos de los profesionales entrevistados que actualmente trabajan con esta herramienta.Fil: Castro, Francisco Javier. Universidad Nacional de Córdoba. Facultad de Ciencias Económicas; Argentina.Fil: Gervasoni, Lucía Florencia. Universidad Nacional de Córdoba. Facultad de Ciencias Económicas; Argentina.Fil: Giannelli, Agostina Belén. Universidad Nacional de Córdoba. Facultad de Ciencias Económicas; Argentina.Fil: Vogel Dotta, María Sol. Universidad Nacional de Córdoba. Facultad de Ciencias Económicas; Argentina

OptPlatform: metaheuristic optimisation framework for solving complex real-world problems

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonWe optimise daily, whether that is planning a round trip that visits the most attractions within a given holiday budget or just taking a train instead of driving a car in a rush hour. Many problems, just like these, are solved by individuals as part of our daily schedule, and they are effortless and straightforward. If we now scale that to many individuals with many different schedules, like a school timetable, we get to a point where it is just not feasible or practical to solve by hand. In such instances, optimisation methods are used to obtain an optimal solution. In this thesis, a practical approach to optimisation has been taken by developing an optimisation platform with all the necessary tools to be used by practitioners who are not necessarily familiar with the subject of optimisation. First, a high-performance metaheuristic optimisation framework (MOF) called OptPlatform is implemented, and the versatility and performance are evaluated across multiple benchmarks and real-world optimisation problems. Results show that, compared to competing MOFs, the OptPlatform outperforms in both the solution quality and computation time. Second, the most suitable hardware platform for OptPlatform is determined by an in-depth analysis of Ant Colony Optimisation scaling across CPU, GPU and enterprise Xeon Phi. Contrary to the common benchmark problems used in the literature, the supply chain problem solved could not scale on GPUs. Third, a variety of metaheuristics are implemented into OptPlatform. Including, a new metaheuristic based on Imperialist Competitive Algorithm (ICA), called ICA with Independence and Constrained Assimilation (ICAwICA) is proposed. The ICAwICA was compared against two different types of benchmark problems, and results show the versatile application of the algorithm, matching and in some cases outperforming the custom-tuned approaches. Finally, essential MOF features like automatic algorithm selection and tuning, lacking on existing frameworks, are implemented in OptPlatform. Two novel approaches are proposed and compared to existing methods. Results indicate the superiority of the implemented tuning algorithms within constrained tuning budget environment

Sports betting: a new asset class to bet on

This dissertation has the aim to present a complete overview of the current features and activities related to the sports betting industry and to explain the reasons why it can be considered a new asset class to invest on. The first chapter explains the main features of both fixed-odds and exchange betting market, the second describes the activity of sport trading, while the third presents a deep investigation concerning the market efficiency. Chapter 4 shows the arbitrage opportunities implementable in this market, that come from the efficiency study of the previous chapter. Before the conclusion, a personal study about the value betting arbitrage opportunity is presented, confirming that abnormal returns are achievable