Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Cover of the book

2019 | OriginalPaper | Chapter

An Investment Recommender Multi-agent System in Financial Technology

Authors : Elena Hernández, Inés Sittón, Sara Rodríguez, Ana B. Gil, Roberto J. García

Published in: International Joint Conference SOCO’18-CISIS’18-ICEUTE’18

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

In this article is presented a review of the state of the art on Financial Technology (Fintech) for the design of a novel recommender system. A social computing platform is proposed, based on Virtual Organizations (VOs), that allows to improve user experience in actions that is associated with the process of investment recommendation. The work presents agents functionalities and an algorithm that will improve the accuracy of the Recommender_agent which is in charge of the Case-based reasoning (CBR) system. The data that will be collected and will feed the CBR corresponds to user’s characteristics, the asset classes, profitability, interest rate, history stock market information and financial news published in the media.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
next chapter Using Genetic Algorithms to Optimize the Location of Electric Vehicle Charging Stations
Literature
1.
Abdou, H.A., Pointon, J., El-Masry, A., Olugbode, M., Lister, R.J.: A variable impact neural network analysis of dividend policies and share prices of transportation and related companies. J. Int. Fin. Mark. Inst. Money 22(4), 796–813 (2012)CrossRef
2.
Avital, M., Andersson, M., Nickerson, J., Sundararajan, A., Van Alstyne, M., Verhoeven, D.: The collaborative economy: a disruptive innovation or much ado about nothing? In: Proceedings of the 35th International Conference on Information Systems, ICIS, pp. 1–7. Association for Information Systems. AIS Electronic Library (AISeL) (2014)
3.
Bach, K.: Knowledge engineering for distributed case-based reasoning systems. In: Synergies Between Knowledge Engineering and Software Engineering, pp. 129–147. Springer, Cham (2018)
4.
Bajo, J., De la Prieta, F., Corchado, J.M., Rodríguez, S.: A low-level resource allocation in an agent-based Cloud Computing platform. Appl. Soft Comput. 48, 716–728 (2016)CrossRef
5.
6.
Chamoso, P., Rivas, A., Rodríguez, S., Bajo, J.: Relationship recommender system in a business and employment-oriented social network. Inf. Sci. 433–434, 204–220 (2017)CrossRef
7.
Corchado, J.M., Lees, B.: Adaptation of cases for case based forecasting with neural network support. In: Soft Computing in Case Based Reasoning, pp. 293–319. Springer, London (2001)CrossRef
8.
Corchado, J.M., Bajo, J., de Paz, Y., Tapia, D.: Intelligent environment for monitoring Alzheimer patients, agent technology for health care. Decis. Support Syst. 34(2), 382–396 (2008). ISSN 0167-9236CrossRef
9.
Corchado, J.M., Laza, R.: Constructing deliberative agents with case-based reasoning technology. Int. J. Intell. Syst. 18(12), 1227–1241 (2003)CrossRef
10.
De Paz, J.F., Bajo, J., González, A., Rodríguez, S., Corchado, J.M.: Combining case-based reasoning systems and support vector regression to evaluate the atmosphere–ocean interaction. Knowl. Inf. Syst. 30(1), 155–177 (2012)CrossRef
11.
DeStefano, R.J., Tao, L., Gai, K.: Improving data governance in large organizations through ontology and linked data. In: 2016 IEEE 3rd International Conference on Cyber Security and Cloud Computing (CSCloud), pp. 279–284. IEEE, June 2016
12.
Ðurić, B.O.: Organisational metamodel for large-scale multi-agent systems: first steps towards modelling organisation dynamics. Adv. Distrib. Comput. Artif. Intell. J. 6(3), 2017 (2017)
13.
Elnagdy, S.A., Qiu, M., Gai, K.: Cyber incident classifications using ontology-based knowledge representation for cybersecurity insurance in financial industry. In: 2016 IEEE 3rd International Conference on Cyber Security and Cloud Computing (CSCloud), pp. 301–306. IEEE, June 2016
14.
Gai, K., Du, Z., Qiu, M., Zhao, H.: Efficiency-aware workload optimizations of heterogeneous cloud computing for capacity planning in financial industry. In: 2015 IEEE 2nd International Conference on Cyber Security and Cloud Computing (CSCloud), pp. 1–6. IEEE, November 2015
15.
Gai, K., Qiu, M., Sun, X., Zhao, H.: Security and privacy issues: a survey on FinTech. In: International Conference on Smart Computing and Communication, pp. 236–247. Springer, Cham, December 2016
16.
García, E., Rodríguez, S., Martín, B., Zato, C., Pérez, B.: MISIA: middleware infrastructure to simulate intelligent agents. In: International Symposium on Distributed Computing and Artificial Intelligence, pp. 107–116. Springer, Heidelberg (2011)
17.
Georgakoudis, G., Gillan, C.J., Sayed, A., Spence, I., Faloon, R., Nikolopoulos, D.S.: Methods and metrics for fair server assessment under real-time financial workloads. Concurrency Comput. Pract. Experience 28(3), 916–928 (2016)CrossRef
18.
Gomber, P., Koch, J.A., Siering, M.: Digital Finance and FinTech: current research and future research directions. Bus. Econ. 87, 537–580 (2017)
19.
Han, F., Gu, T.Y., Ju, S.G.: An improved hybrid algorithm based on PSO and BP for feedforward neural networks. JDCTA: Int. J. Digit. Content Technol. Appl. 5(2), 106–115 (2011)
20.
Havandi, E., Shavandi, H., Ghanbari, A.: Integration of genetic fuzzy systems and artificial neural networks for stock price forecasting. Knowl. Based Syst. 23(8), 800–808 (2010)CrossRef
21.
Hüllermeier, E., Minor, M. (eds.): Case-Based Reasoning Research and Development: Proceedings of the 22nd International Conference, ICCBR 2014, Cork, Ireland, September 29–October 1, 2014, vol. 8765. Springer (2015)
22.
Kaastra, I., Boyd, M.: Designing a neural network for forecasting financial and economic time series. Neurocomputing 10(3), 215–236 (1996)CrossRef
23.
24.
Li, B., Hoi, S.C.: Online portfolio selection: a survey. ACM Comput. Surv. (CSUR) 46(3), 35 (2014)MATH
25.
Lu, C.J., Lee, T.S., Chiu, C.C.: Financial time series forecasting using independent component analysis and support vector regression. Decis. Support Syst. 47(2), 115–125 (2009)CrossRef
26.
Lu, Y., Roychowdhury, V., Vandenberghe, L.: Distributed parallel support vector machines in strongly connected networks. IEEE Trans. Neural Netw. 19(7), 1167–1178 (2008)CrossRef
27.
Owyang, J., Tran, C., Silva, C.: The Collaborative Economy. Altimeter, New York (2013)
28.
Rodriguez, S., Julián, V., Bajo, J., Carrascosa, C., Botti, V., Corchado, J.M.: Agent-based virtual organization architecture. Eng. Appl. Artif. Intell. 24(5), 895–910 (2011)CrossRef
29.
Sagraves, A., Connors, G.: Capturing the value of data in banking. Appl. Mark. Anal. 2(4), 304–311 (2017)
30.
Song, Q., Liu, A., Yang, S.Y.: Stock portfolio selection using learning-to-rank algorithms with news sentiment. Neurocomputing 264, 20–28 (2017)CrossRef
31.
Tkáč, M., Verner, R.: Artificial neural networks in business: two decades of research. Appl. Soft Comput. 38, 788–804 (2016)CrossRef
32.
Wang, L.X.: Dynamical models of stock prices based on technical trading rules part I: the models. IEEE Trans. Fuzzy Syst. 23(4), 787–801 (2015)MathSciNetCrossRef
33.
Wang, L.X.: Dynamical models of stock prices based on technical trading rules—Part III: application to Hong Kong stocks. IEEE Trans. Fuzzy Syst. 23(5), 1680–1697 (2015)CrossRef
34.
Xu, K., Yue, H., Guo, L., Guo, Y., Fang, Y.: Privacy-preserving machine learning algorithms for big data systems. In: 2015 IEEE 35th International Conference on Distributed Computing Systems (ICDCS), pp. 318–327. IEEE, June 2015
35.
Yu, K., Gao, Y., Zhang, P., Qiu, M.: Design and architecture of dell acceleration appliances for database (DAAD): a practical approach with high availability guaranteed. In: 2015 IEEE 17th International Conference on High Performance Computing and Communications (HPCC), 2015 IEEE 7th International Symposium on Cyberspace Safety and Security (CSS), 2015 IEEE 12th International Conference on Embedded Software and Systems (ICESS), pp. 430–435. IEEE, August 2015
36.
Zato, C., Villarrubia, G., Sánchez, A., Bajo, J., Corchado, J.M.: PANGEA: a new platform for developing virtual organizations of agents. Int. J. Artif. Intell. 11(A13), 93–102 (2013)
Metadata
Title
An Investment Recommender Multi-agent System in Financial Technology
Authors
Elena Hernández
Inés Sittón
Sara Rodríguez
Ana B. Gil
Roberto J. García
Copyright Year
2019
Book
International Joint Conference SOCO’18-CISIS’18-ICEUTE’18

Print ISBN: 978-3-319-94119-6

Electronic ISBN: 978-3-319-94120-2

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-319-94120-2_1

Premium Partner

    Image Credits