Add to ORKGAssume there exists information in past data that relates to future trends. This is the case with our physical world. It allows physics models to predict exactly how fast an apple will fall. With historical data in the physical world, such as the apple has been 8m above the surface for a long time and that the apple\u27s stem breaks at t = 0, it is possible to predict where the apple will be in the future, at t \u3e 0. If this assumption is made for nancial data, the resulting trend data would be extremely valuable. However there is a great volume of past data and much more complex and transient rules; in short decoding the limited information is di cult. A software signal processing system is proposed to attempt to decode trend informatio...
In this paper, predictions of future price movements of a major American stock index was made by ana...
We utilize a recently developed genetic algorithm, in conjunction with discrete wavelets, for carryi...
Deriving a relationship that allows to predict future values of a time series is a challenging task ...
Assume there exists information in past data that relates to future trends. This is the case with ou...
This thesis summarizes knowledge in the field of time series theory, method for time series analysis...
Rule extraction is performed on three kinds of time series. The first one is stock market data. The ...
A genetic algorithm (GA) is a search technique that falls within the inter-section of optimization a...
The future is often predictable from present and past events. Which of those are more important? Whi...
This paper studies the latest techniques for financial time series forecasting by extending the exi...
Finance is a very broad field where the uncertainty plays a central role and every financial operato...
Abstract: This paper presents the use of artificial intelligence and more specifically artificial ne...
In this paper an evolutionary approach to forecasting the stock market is tested and compared with b...
The problem of forecasting streaming datasets, particularly the financial time series, has been larg...
IEEE International Parallel and Distributed Processing Symposium. Long Beach, CA, 26-30 March 2007Ma...
Time series represent sequences of data points where usually their order is defined by the time when...
In this paper, predictions of future price movements of a major American stock index was made by ana...
We utilize a recently developed genetic algorithm, in conjunction with discrete wavelets, for carryi...
Deriving a relationship that allows to predict future values of a time series is a challenging task ...
Assume there exists information in past data that relates to future trends. This is the case with ou...
This thesis summarizes knowledge in the field of time series theory, method for time series analysis...
Rule extraction is performed on three kinds of time series. The first one is stock market data. The ...
A genetic algorithm (GA) is a search technique that falls within the inter-section of optimization a...
The future is often predictable from present and past events. Which of those are more important? Whi...
This paper studies the latest techniques for financial time series forecasting by extending the exi...
Finance is a very broad field where the uncertainty plays a central role and every financial operato...
Abstract: This paper presents the use of artificial intelligence and more specifically artificial ne...
In this paper an evolutionary approach to forecasting the stock market is tested and compared with b...
The problem of forecasting streaming datasets, particularly the financial time series, has been larg...
IEEE International Parallel and Distributed Processing Symposium. Long Beach, CA, 26-30 March 2007Ma...
Time series represent sequences of data points where usually their order is defined by the time when...
In this paper, predictions of future price movements of a major American stock index was made by ana...
We utilize a recently developed genetic algorithm, in conjunction with discrete wavelets, for carryi...
Deriving a relationship that allows to predict future values of a time series is a challenging task ...