Financial time series prediction in cooperating with event knowledge: A fuzzy approach

Do Thanh Sang; Dong Min Woo; Dong Chul Park; Thi Nguyen

doi:10.1007/978-3-642-16773-7_35

Financial time series prediction in cooperating with event knowledge: A fuzzy approach

Do Thanh Sang, Dong Min Woo, Dong Chul Park, Thi Nguyen

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

1 Citation (Scopus)

Abstract

A number of researchers have used historical numeric time series data to forecast financial markets, i.e. stock prices, and they achieved some results with reasonable accuracies. However, there are various non-numerical factors that influence prices such as company's performance, government involvement, trends of the market, changes in economic activity and so forth. We attempt to take such factors into account to our recent study. This paper surveys an application of a fuzzy inference system, namely Standard Additive Model, for predicting stock prices in cooperating with event-knowledge and several new training criteria. Experimental results show that the integrated model yields the outcomes which have error smaller than original model's one.

Original language	English
Title of host publication	Advances in Soft Computing - 9th Mexican International Conference on Artificial Intelligence, MICAI 2010, Proceedings
Publisher	Springer
Pages	406-417
Number of pages	12
Edition	PART 2
ISBN (Print)	3642167721, 9783642167720
DOIs	https://doi.org/10.1007/978-3-642-16773-7_35
Publication status	Published - 2010
Event	Mexican International Conference on Artificial Intelligence 2010 - Pachuca, Mexico Duration: 8 Nov 2010 → 13 Nov 2010 Conference number: 9th https://www.springer.com/series/0558 (Proceedings)

Publication series

Name	Lecture Notes in Computer Science
Number	PART 2
Volume	6438
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	Mexican International Conference on Artificial Intelligence 2010
Abbreviated title	MICAI 2010
Country/Territory	Mexico
City	Pachuca
Period	8/11/10 → 13/11/10
Internet address	https://www.springer.com/series/0558 (Proceedings)

Keywords

event knowledge
financial time series prediction
fuzzy logic
Standard Additive Fuzzy System

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10.1007/978-3-642-16773-7_35

Cite this

Sang, D. T., Woo, D. M., Park, D. C., & Nguyen, T. (2010). Financial time series prediction in cooperating with event knowledge: A fuzzy approach. In Advances in Soft Computing - 9th Mexican International Conference on Artificial Intelligence, MICAI 2010, Proceedings (PART 2 ed., pp. 406-417). (Lecture Notes in Computer Science ; Vol. 6438, No. PART 2). Springer. https://doi.org/10.1007/978-3-642-16773-7_35

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title = "Financial time series prediction in cooperating with event knowledge: A fuzzy approach",

abstract = "A number of researchers have used historical numeric time series data to forecast financial markets, i.e. stock prices, and they achieved some results with reasonable accuracies. However, there are various non-numerical factors that influence prices such as company's performance, government involvement, trends of the market, changes in economic activity and so forth. We attempt to take such factors into account to our recent study. This paper surveys an application of a fuzzy inference system, namely Standard Additive Model, for predicting stock prices in cooperating with event-knowledge and several new training criteria. Experimental results show that the integrated model yields the outcomes which have error smaller than original model's one.",

keywords = "event knowledge, financial time series prediction, fuzzy logic, Standard Additive Fuzzy System",

author = "Sang, {Do Thanh} and Woo, {Dong Min} and Park, {Dong Chul} and Thi Nguyen",

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Sang, DT, Woo, DM, Park, DC & Nguyen, T 2010, Financial time series prediction in cooperating with event knowledge: A fuzzy approach. in Advances in Soft Computing - 9th Mexican International Conference on Artificial Intelligence, MICAI 2010, Proceedings. PART 2 edn, Lecture Notes in Computer Science , no. PART 2, vol. 6438, Springer, pp. 406-417, Mexican International Conference on Artificial Intelligence 2010, Pachuca, Mexico, 8/11/10. https://doi.org/10.1007/978-3-642-16773-7_35

Financial time series prediction in cooperating with event knowledge: A fuzzy approach. / Sang, Do Thanh; Woo, Dong Min; Park, Dong Chul et al.
Advances in Soft Computing - 9th Mexican International Conference on Artificial Intelligence, MICAI 2010, Proceedings. PART 2. ed. Springer, 2010. p. 406-417 (Lecture Notes in Computer Science ; Vol. 6438, No. PART 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

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AB - A number of researchers have used historical numeric time series data to forecast financial markets, i.e. stock prices, and they achieved some results with reasonable accuracies. However, there are various non-numerical factors that influence prices such as company's performance, government involvement, trends of the market, changes in economic activity and so forth. We attempt to take such factors into account to our recent study. This paper surveys an application of a fuzzy inference system, namely Standard Additive Model, for predicting stock prices in cooperating with event-knowledge and several new training criteria. Experimental results show that the integrated model yields the outcomes which have error smaller than original model's one.

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Financial time series prediction in cooperating with event knowledge: A fuzzy approach

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