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Pregled bibliografske jedinice broj: 1086351

Evaluation of Alternative Approaches in Classification Algorithms for Prediction of Stock Market Index


Vlah Jerić, Silvija
Evaluation of Alternative Approaches in Classification Algorithms for Prediction of Stock Market Index // Recent Applications of Financial Risk Modelling and Portfolio Management / Škrinjarić, Tihana ; Čižmešija, Mirjana ; Christiansen, Bryan (ur.).
USA: IGI Global, 2020. str. 204-221 doi:10.4018/978-1-7998-5083-0.ch010


CROSBI ID: 1086351 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Evaluation of Alternative Approaches in Classification Algorithms for Prediction of Stock Market Index

Autori
Vlah Jerić, Silvija

Vrsta, podvrsta i kategorija rada
Poglavlja u knjigama, znanstveni

Knjiga
Recent Applications of Financial Risk Modelling and Portfolio Management

Urednik/ci
Škrinjarić, Tihana ; Čižmešija, Mirjana ; Christiansen, Bryan

Izdavač
IGI Global

Grad
USA

Godina
2020

Raspon stranica
204-221

ISSN
2327-5677

Ključne riječi
Day Trading, Classification Problem, Neural Network, Support Vector Machine, Random Forest, K-Nearest Neighbors, Naïve Bayes, Crobex

Sažetak
This chapter tackles the problem of automatic recognition of favorable days for intra-day trading. The problem is modeled as a binary classification problem and several approaches are tested for solving it. Croatian stock index CROBEX data is used and 22 technical indicators are calculated as predictor variables. Performance of five classifiers is evaluated and compared by using Cohen’s kappa as evaluation metric: artificial neural network, support network machine, random forest, k-nearest neighbors and naïve Bayes classifier. The results give insight to effectiveness of technical analysis in predicting the day favorability for CROBEX index and suggest that technical analysis makes sense and might work for this case.

Izvorni jezik
Hrvatski

Znanstvena područja
Matematika, Računarstvo, Ekonomija



POVEZANOST RADA


Ustanove:
Ekonomski fakultet, Zagreb

Profili:

Avatar Url Silvija Vlah Jerić (autor)

doi

Citiraj ovu publikaciju

Vlah Jerić, Silvija
Evaluation of Alternative Approaches in Classification Algorithms for Prediction of Stock Market Index // Recent Applications of Financial Risk Modelling and Portfolio Management / Škrinjarić, Tihana ; Čižmešija, Mirjana ; Christiansen, Bryan (ur.).
USA: IGI Global, 2020. str. 204-221 doi:10.4018/978-1-7998-5083-0.ch010
Vlah Jerić, S. (2020) Evaluation of Alternative Approaches in Classification Algorithms for Prediction of Stock Market Index. U: Škrinjarić, T., Čižmešija, M. & Christiansen, B. (ur.) Recent Applications of Financial Risk Modelling and Portfolio Management. USA, IGI Global, str. 204-221 doi:10.4018/978-1-7998-5083-0.ch010.
@inbook{inbook, author = {Vlah Jeri\'{c}, S.}, year = {2020}, pages = {204-221}, DOI = {10.4018/978-1-7998-5083-0.ch010}, keywords = {Day Trading, Classification Problem, Neural Network, Support Vector Machine, Random Forest, K-Nearest Neighbors, Na\"{\i}ve Bayes, Crobex}, doi = {10.4018/978-1-7998-5083-0.ch010}, issn = {2327-5677}, title = {Evaluation of Alternative Approaches in Classification Algorithms for Prediction of Stock Market Index}, keyword = {Day Trading, Classification Problem, Neural Network, Support Vector Machine, Random Forest, K-Nearest Neighbors, Na\"{\i}ve Bayes, Crobex}, publisher = {IGI Global}, publisherplace = {USA} }
@inbook{inbook, author = {Vlah Jeri\'{c}, S.}, year = {2020}, pages = {204-221}, DOI = {10.4018/978-1-7998-5083-0.ch010}, keywords = {Day Trading, Classification Problem, Neural Network, Support Vector Machine, Random Forest, K-Nearest Neighbors, Na\"{\i}ve Bayes, Crobex}, doi = {10.4018/978-1-7998-5083-0.ch010}, issn = {2327-5677}, title = {Evaluation of Alternative Approaches in Classification Algorithms for Prediction of Stock Market Index}, keyword = {Day Trading, Classification Problem, Neural Network, Support Vector Machine, Random Forest, K-Nearest Neighbors, Na\"{\i}ve Bayes, Crobex}, publisher = {IGI Global}, publisherplace = {USA} }

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