FINANCIAL TIME SERIES FORECAST USING SIMULATED ANNEALING AND THRESHOLD ACCEPTANCE GENETIC BPA NEURAL NETWORK

Anupam Tarsauliya, Ritu Tiwari, Anupam Shukla

2011

Abstract

Financial time series forecast has been eyed as key standard job because of its high non-linearity and high volatility in data. Various statistical methods, machine learning and optimization algorithms has been widely used for forecasting time series of various fields. To overcome the problem of solution trapping in local minima, here in this paper, we propose novel approach of financial time series forecasting using simulated annealing and threshold acceptance genetic back propagation network to obtain the global minima and better accuracy. Time series dataset is normalized and bifurcated into training and test datasets, which is used as supervised learning in BPA artificial neural network and optimized with genetic algorithm. Results thus obtained are used as seed for start point of simulated annealing and threshold acceptance. Empirical results obtained from proposed approach confirm the outperformance of forecast results than conventional BPA artificial neural networks.

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Paper Citation


in Harvard Style

Tarsauliya A., Tiwari R. and Shukla A. (2011). FINANCIAL TIME SERIES FORECAST USING SIMULATED ANNEALING AND THRESHOLD ACCEPTANCE GENETIC BPA NEURAL NETWORK . In Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-8425-54-6, pages 172-177. DOI: 10.5220/0003492101720177


in Harvard Style

Tarsauliya A., Tiwari R. and Shukla A. (2011). FINANCIAL TIME SERIES FORECAST USING SIMULATED ANNEALING AND THRESHOLD ACCEPTANCE GENETIC BPA NEURAL NETWORK . In Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-8425-54-6, pages 172-177. DOI: 10.5220/0003492101720177


in Bibtex Style

@conference{iceis11,
author={Anupam Tarsauliya and Ritu Tiwari and Anupam Shukla},
title={FINANCIAL TIME SERIES FORECAST USING SIMULATED ANNEALING AND THRESHOLD ACCEPTANCE GENETIC BPA NEURAL NETWORK},
booktitle={Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2011},
pages={172-177},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003492101720177},
isbn={978-989-8425-54-6},
}


in Bibtex Style

@conference{iceis11,
author={Anupam Tarsauliya and Ritu Tiwari and Anupam Shukla},
title={FINANCIAL TIME SERIES FORECAST USING SIMULATED ANNEALING AND THRESHOLD ACCEPTANCE GENETIC BPA NEURAL NETWORK},
booktitle={Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2011},
pages={172-177},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003492101720177},
isbn={978-989-8425-54-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - FINANCIAL TIME SERIES FORECAST USING SIMULATED ANNEALING AND THRESHOLD ACCEPTANCE GENETIC BPA NEURAL NETWORK
SN - 978-989-8425-54-6
AU - Tarsauliya A.
AU - Tiwari R.
AU - Shukla A.
PY - 2011
SP - 172
EP - 177
DO - 10.5220/0003492101720177


in EndNote Style

TY - CONF
JO - Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - FINANCIAL TIME SERIES FORECAST USING SIMULATED ANNEALING AND THRESHOLD ACCEPTANCE GENETIC BPA NEURAL NETWORK
SN - 978-989-8425-54-6
AU - Tarsauliya A.
AU - Tiwari R.
AU - Shukla A.
PY - 2011
SP - 172
EP - 177
DO - 10.5220/0003492101720177