Algorithmic Trading and Financial Forecasting Using Advanced Artificial Intelligence Methodologies

An Artificial Intelligence Approach to Financial Forecasting using Improved

Artificial Financial Markets with Adaptive Trading Agents

Motivation: In the last decade there has been a surge of interest within the finance community in describing equity markets through computational agent models [7]. At the same time, financial markets are an important application area within artificial intelligence for the fields of agent-based modeling and machine learning, since agent objectives and interactions tend to be more clearly defined...

Artificial Neural Networks in Financial Trading

IntroductIon Soft computing represents that area of computing adapted from the physical sciences. Artificial intelligence (AI) techniques within this realm attempt to solve problems by applying physical laws and processes. This style of computing is particularly tolerant of imprecision and uncertainty , making the approach attractive to those researching within " noisy " realms, where the signa...

Financial Time Series Forecasting Using Artificial Neural Networks

Financial and capital markets (especially stock markets) are considered high return investment fields, which in the same time are dominated by uncertainty and volatility. Stock market prediction tries to reduce this uncertainty and consequently the risk. As stock markets are influenced by many economical, political and even psychological factors, it is very difficult to forecast the movement of...

Forecasting Financial Time-Series using Artificial Market Models

We discuss the theoretical machinery involved in predicting financial market movements using an artificial market model which has been trained on real financial data. This approach to market prediction in particular, forecasting financial time-series by training a third-party or ‘black box’ game on the financial data itself – was discussed by Johnson et al. in [10] and [13] and was based on som...