A digital service from FCT Publication
A Trading Agent Framework Using Plain Strategies & Machine Learning
| Summary: | The world of online sports betting exchange (trading) is growing every day and with that people are trying to improve their trading by using automated trading. In analogy to the financial markets the buy and sell operations are replaced by betting for and against (Back and Lay).This thesis describes a framework to be used to develop automated trading agents at Betfair sports markets using a Java programming interface. Betfair processes more than five million transactions (such as placing a bet) every day which is more than all European stock exchanges combined. Betfair is available 24 hours a day 7 days a week. For this thesis were developed two trading agents, DealerAgent and HorseLayAgent, accordingly with the presented framework. The agents mentioned above act on To Win horse racing markets in United Kingdom. They use plain strategies together with machine learning methods to improve the profit/loss results. The developed agents were submitted to viability tests using data from Betfair To Win horse racing markets from January, February and March of 2014. |
|---|---|
| Subject: | Engenharia electrotécnica, electrónica e informática Electrical engineering, Electronic engineering, Information engineering |
| Country: | Portugal |
| Document type: | master thesis |
| Access type: | Open |
| Associated institution: | Repositório Aberto da Universidade do Porto |
| Language: | English |
| Origin: | Repositório Aberto da Universidade do Porto |
Similar Items
Forecasting stock trends through Machine Learning
Machine Learning-based approaches for microbiome characterization in cancer
IoT and Machine Learning for Process Optimization in Agrofood Industry
Framework for Multi-Agent Simulation of User Behaviour in E-Commerce Sites
Learning from Demonstration using Hierarchical Reinforcement Learning for Robotic Skill transferability.
Predicting the Aesthetic Outcome of Breast Cancer Treatment using Deep Learning
Using Deep Reinforcement Learning Techniques to Optimize the Throughput of Wi-Fi Links
A Framework for Dataflow Orchestration in Lambda Architectures
Development of a Flexible Communication Framework to support Testing and Production of Automotive Products
Deep Learning for Market Forecasts
Sophisticated Agent Modeling: Language Design and Implementation for Large-Scale Simulation
Reinforcement learning for production scheduling applications
Whispered speech segmentation based on Deep Learning
Tool to Support Computer Architecture Teaching and Learning
Reinforcement Learning para Problemas de Otimização
Serious Game for learning about Software Architecture and Design
Multi-Robot Learning of High-Level Skills in RoboCup
Previsão de preços de mercado baseada em Deep Learning
Avaliação Automática de Programas em Contexto de E-learning
Deep Reinforcement Learning for Joint Cruise Control and Intelligent Data Acquisition in UAVs-Assisted Sensor Networks
Carotid Lumen Segmentation using a Neural Network Approach
Static transmission expansion planning using Heuristic and metaheuristic techniques
Using Causal Inference to Measure Residential Consumers Demand Response Elasticity
A market based active/reactive dispatch including transformer taps and reactor and capacitor banks using simulated annealing
Decentralized Application for E-Commerce Using Blockchain and Trusted Compute
Enhancing Forecasting using Read & Write Recurrent Neural Networks
Relative location of autonomous underwater vehicles using visual markers
Secure Underwater Delay-Tolerant Communications using Distributed Ledger Techniques
Published: (2027)
Published: (2027)
Exploring the potential of DRT for elderly urban mobility using big data
Digital Model of Reconfigurable Printed IoT Nodes using ns-3
Published: (2027)
Published: (2027)
Using fuzzy sets to evaluate the performance of complex system when parameters are uncertain
Optical Character Recognition of Alphanumeric Codes of Ceramic Bowls used in Lost-wax Casting
Enhancing ML Models for Solar Weather Forecasting using Clustering and Adversarial Anomaly Detection
Wireless Underwater Broadband and Long Range Communications using Underwater Drones as Data Mules
A design and simulation of a Brazilian bid based short-term electricity market
An Approach of a Research Tool based in a Shamanic Interface