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Articles 1 - 8 of 8
Full-Text Articles in Business
Designing Short Term Trading Systems With Artificial Neural Networks, Bruce Vanstone, Gavin Finnie, Tobias Hahn
Designing Short Term Trading Systems With Artificial Neural Networks, Bruce Vanstone, Gavin Finnie, Tobias Hahn
Tobias Hahn
There is a long established history of applying Artificial Neural Networks (ANNs) to financial data sets. In this paper, the authors demonstrate the use of this methodology to develop a financially viable, short-term trading system. When developing short-term systems, the authors typically site the neural network within an already existing non-neural trading system. This paper briefly reviews an existing medium-term long-only trading system, and then works through the Vanstone and Finnie methodology to create a short-term focused ANN which will enhance this trading strategy. The initial trading strategy and the ANN enhanced trading strategy are comprehensively benchmarked both in-sample and …
Do Initial Stop-Losses Stop Losses?, Bruce Vanstone
Do Initial Stop-Losses Stop Losses?, Bruce Vanstone
Bruce Vanstone
A great many traders use stop-loss rules in their everyday trading. In addition, during periods of high volatility, many traders attempt to protect their downside by moving their stops closer to the price action. However, there appears to be little real justification for doing this. There is a shortage of evidence that demonstrates that stops are actually providing the benefits that traders believe they are. This paper is an empirical study of the use of stops within a defined trading strategy. The methodology used within this paper can easily be ported to any individual traders’ strategy. In the specific case …
Intelligent Is — Artificial Neural Networks In Financial Trading, Bruce Vanstone, Clarence Tan
Intelligent Is — Artificial Neural Networks In Financial Trading, Bruce Vanstone, Clarence Tan
Bruce Vanstone
From the Introduction:
Soft computing represents that area of computing adapted from the physical sciences. Artificial Intelligence 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 signal-to-noise ratio is quite low. Soft computing is normally accepted to include the three key areas of Fuzzy Logic, Artificial Neural Networks, and Probabilistic Reasoning (which includes Genetic Algorithms, Chaos Theory, etc).
A Computational Exploration Of The Efficacy Of Fibonacci Sequences In Technical Analysis And Trading, Sukanto Bhattacharya, Kuldeep Kumar
A Computational Exploration Of The Efficacy Of Fibonacci Sequences In Technical Analysis And Trading, Sukanto Bhattacharya, Kuldeep Kumar
Kuldeep Kumar
Among the vast assemblage of technical analysis tools, the ones based on Fibonacci recurrences in asset prices are relatively more scientific. In this paper, we review some of the popular technical analysis methodologies based on Fibonacci sequences and also advance a theoretical rationale as to why security prices may be seen to follow such sequences. We also analyze market data for an indicative empirical validation of the efficacy or otherwise of such sequences in predicting critical security price retracements that may be useful in constructing automated trading systems. © 2006 Peking University Press
Applying Fundamental Analysis And Neural Networks In The Australian Stockmarket, Bruce J. Vanstone, Gavin Finnie, Clarence Tan
Applying Fundamental Analysis And Neural Networks In The Australian Stockmarket, Bruce J. Vanstone, Gavin Finnie, Clarence Tan
Bruce Vanstone
This paper demonstrates how Neural Networks may be successfully applied to the problem of security selection in the Australian stockmarket. In practice, it is unrealistic for a trader to apply capital to all securities available in the market, and a selection technique must be employed to reduce the number of securities competing for capital. Selection techniques are generally based on either fundamental analysis procedures, or technical analysis procedures. This paper focuses on fundamental procedures, and implements a neural network which enhances the effectiveness of these procedures.
A Survey Of The Application Of Soft Computing To Investment And Financial Trading, Bruce Vanstone, Clarence Tan
A Survey Of The Application Of Soft Computing To Investment And Financial Trading, Bruce Vanstone, Clarence Tan
Bruce Vanstone
This paper surveys recent literature in the domain of applying Soft Computing to Investment and Financial Trading. It analyses the literature according to the style of soft computing used, the investment discipline used, the successes demonstrated, and the applicability of the research to real world trading. This papers contribution is to expose the key areas where research is being undertaken, and to attempt to quantify the degree of successes associated with the different research approaches.
Enhancing Security Selection In The Australian Stockmarket Using Fundamental Analysis And Neural Networks, Bruce Vanstone, Gavin Finnie, Clarence Tan
Enhancing Security Selection In The Australian Stockmarket Using Fundamental Analysis And Neural Networks, Bruce Vanstone, Gavin Finnie, Clarence Tan
Bruce Vanstone
This paper examines financial trading from the aspect of security selection. In practice, it is unrealistic for a financial trader to participate in the full market of tradeable securities, and a selection mechanism must be employed to reduce the number of possible securities competing for investment capital. Essentially, there are two main methodologies used, namely, Fundamental Analysis, and Technical Analysis. This paper examines the practice of Fundamental Analysis, and demonstrates how neural networks can be practically employed to enhance the fundamentalist selection process.
Designing Short Term Trading Systems With Artificial Neural Networks, Bruce Vanstone, Gavin Finnie, Tobias Hahn
Designing Short Term Trading Systems With Artificial Neural Networks, Bruce Vanstone, Gavin Finnie, Tobias Hahn
Bruce Vanstone
There is a long established history of applying Artificial Neural Networks (ANNs) to financial data sets. In this paper, the authors demonstrate the use of this methodology to develop a financially viable, short-term trading system. When developing short-term systems, the authors typically site the neural network within an already existing non-neural trading system. This paper briefly reviews an existing medium-term long-only trading system, and then works through the Vanstone and Finnie methodology to create a short-term focused ANN which will enhance this trading strategy. The initial trading strategy and the ANN enhanced trading strategy are comprehensively benchmarked both in-sample and …