We analyze the potential of unsupervised neural networks when they are employed to support intraday trading activity on financial markets. Several time frequencies have been considered: from five minutes to daily trades. At the current stage our major findings may be summarized as follows: a) unsupervised neural networks are helpful to localize profitable intraday patterns, and they make possible to achieve higher performances than common trading rules; b) trading strategies based on neural networks make exploitable with profits almost continuous trades (i.e. scalping), until transaction costs maintain below proper thresholds.
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Titolo: | On the Profitability of Scalping Strategies Based on Neural Networks |
Autori: | |
Data di pubblicazione: | 2006 |
Serie: | |
Abstract: | We analyze the potential of unsupervised neural networks when they are employed to support intraday trading activity on financial markets. Several time frequencies have been considered: from five minutes to daily trades. At the current stage our major findings may be summarized as follows: a) unsupervised neural networks are helpful to localize profitable intraday patterns, and they make possible to achieve higher performances than common trading rules; b) trading strategies based on neural networks make exploitable with profits almost continuous trades (i.e. scalping), until transaction costs maintain below proper thresholds. |
Handle: | http://hdl.handle.net/11567/229993 |
ISBN: | 978-3-540-46544-7 |
Appare nelle tipologie: | 02.01 - Contributo in volume (Capitolo o saggio) |
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