The use of domain knowledge in feature construction for financial time series prediction

Pedro De Almeida; Luís Torgo

doi:10.1007/3-540-45329-6_15

The use of domain knowledge in feature construction for financial time series prediction

Pedro De Almeida, Luís Torgo

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Original language	English
Title of host publication	Progress in Artificial Intelligence
Subtitle of host publication	Knowledge Extraction, Multi-Agent Systems, Logic Programming, and Constraint Solving - 10th Portuguese Conference on Artificial Intelligence, EPIA 2001, Proc.
Editors	Pavel Brazdil, Alipio Jorge
Publisher	Springer Verlag
Pages	116-129
Number of pages	14
ISBN (Print)	354043030X, 9783540430308
DOIs	https://doi.org/10.1007/3-540-45329-6_15
Publication status	Published - 2001
Externally published	Yes
Event	10th Portuguese Conference on Artificial Intelligence, EPIA 2001 - Porto, Portugal Duration: Dec 17 2001 → Dec 20 2001

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	2258 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	10th Portuguese Conference on Artificial Intelligence, EPIA 2001
Country/Territory	Portugal
City	Porto
Period	12/17/01 → 12/20/01

ASJC Scopus Subject Areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/3-540-45329-6_15

Cite this

De Almeida, P., & Torgo, L. (2001). The use of domain knowledge in feature construction for financial time series prediction. In P. Brazdil, & A. Jorge (Eds.), Progress in Artificial Intelligence: Knowledge Extraction, Multi-Agent Systems, Logic Programming, and Constraint Solving - 10th Portuguese Conference on Artificial Intelligence, EPIA 2001, Proc. (pp. 116-129). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2258 LNAI). Springer Verlag. https://doi.org/10.1007/3-540-45329-6_15

The use of domain knowledge in feature construction for financial time series prediction. / De Almeida, Pedro; Torgo, Luís.
Progress in Artificial Intelligence: Knowledge Extraction, Multi-Agent Systems, Logic Programming, and Constraint Solving - 10th Portuguese Conference on Artificial Intelligence, EPIA 2001, Proc.. ed. / Pavel Brazdil; Alipio Jorge. Springer Verlag, 2001. p. 116-129 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2258 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

De Almeida, P & Torgo, L 2001, The use of domain knowledge in feature construction for financial time series prediction. in P Brazdil & A Jorge (eds), Progress in Artificial Intelligence: Knowledge Extraction, Multi-Agent Systems, Logic Programming, and Constraint Solving - 10th Portuguese Conference on Artificial Intelligence, EPIA 2001, Proc.. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2258 LNAI, Springer Verlag, pp. 116-129, 10th Portuguese Conference on Artificial Intelligence, EPIA 2001, Porto, Portugal, 12/17/01. https://doi.org/10.1007/3-540-45329-6_15

De Almeida P, Torgo L. The use of domain knowledge in feature construction for financial time series prediction. In Brazdil P, Jorge A, editors, Progress in Artificial Intelligence: Knowledge Extraction, Multi-Agent Systems, Logic Programming, and Constraint Solving - 10th Portuguese Conference on Artificial Intelligence, EPIA 2001, Proc.. Springer Verlag. 2001. p. 116-129. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/3-540-45329-6_15

De Almeida, Pedro ; Torgo, Luís. / The use of domain knowledge in feature construction for financial time series prediction. Progress in Artificial Intelligence: Knowledge Extraction, Multi-Agent Systems, Logic Programming, and Constraint Solving - 10th Portuguese Conference on Artificial Intelligence, EPIA 2001, Proc.. editor / Pavel Brazdil ; Alipio Jorge. Springer Verlag, 2001. pp. 116-129 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{74e9b108be804a28b979e4497f40e365,

title = "The use of domain knowledge in feature construction for financial time series prediction",

author = "{De Almeida}, Pedro and Lu{\'i}s Torgo",

year = "2001",

doi = "10.1007/3-540-45329-6_15",

language = "English",

isbn = "354043030X",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "116--129",

editor = "Pavel Brazdil and Alipio Jorge",

booktitle = "Progress in Artificial Intelligence",

address = "Germany",

note = "10th Portuguese Conference on Artificial Intelligence, EPIA 2001 ; Conference date: 17-12-2001 Through 20-12-2001",

}

TY - GEN

T1 - The use of domain knowledge in feature construction for financial time series prediction

AU - De Almeida, Pedro

AU - Torgo, Luís

PY - 2001

Y1 - 2001

UR - http://www.scopus.com/inward/record.url?scp=84867810007&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84867810007&partnerID=8YFLogxK

U2 - 10.1007/3-540-45329-6_15

DO - 10.1007/3-540-45329-6_15

M3 - Conference contribution

AN - SCOPUS:84867810007

SN - 354043030X

SN - 9783540430308

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 116

EP - 129

BT - Progress in Artificial Intelligence

A2 - Brazdil, Pavel

A2 - Jorge, Alipio

PB - Springer Verlag

T2 - 10th Portuguese Conference on Artificial Intelligence, EPIA 2001

Y2 - 17 December 2001 through 20 December 2001

ER -

The use of domain knowledge in feature construction for financial time series prediction

Publication series

Conference

ASJC Scopus Subject Areas

Access to Document

Other files and links

Fingerprint

Cite this