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  • Search: subject:"Performance optimisation"
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Year of publication
Subject
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Active management 2 Portfolio performance optimisation 2 Tracking error 2 artificial intelligence 2 bank telemarketing 2 data mining 2 heterogeneous data 2 machine learning 2 performance optimisation 2 predictive modelling 2 targeted marketing 2 Artificial intelligence 1 Bank 1 Benchmarking 1 Capital income 1 Data Mining 1 Data mining 1 Forecasting model 1 Investment Fund 1 Investmentfonds 1 Kapitaleinkommen 1 Künstliche Intelligenz 1 Portfolio selection 1 Portfolio-Management 1 Prognoseverfahren 1 Statistical error 1 Statistischer Fehler 1 Theorie 1 Theory 1 Volatility 1 Volatilität 1
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Online availability
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Free 4 CC license 2
Type of publication
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Article 4
Type of publication (narrower categories)
All
Article 2 Article in journal 2 Aufsatz in Zeitschrift 2
Language
All
English 4
Author
All
Gherghina, Ştefan Cristian 2 Hausner, Jan Frederick 2 Koumétio Tékouabou, Stéphane Cédric 2 Martins, José Moleiro 2 Mata, Mário Nuno 2 Mata, Pedro Neves 2 Toulni, Hamza 2 Van Vuuren, Gary 2
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Published in...
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Journal of Economics, Finance and Administrative Science 1 Journal of Risk and Financial Management 1 Journal of economics, finance & administrative science 1 Journal of risk and financial management : JRFM 1
Source
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ECONIS (ZBW) 2 EconStor 2
Showing 1 - 4 of 4
Cover Image
A machine learning framework towards bank telemarketing prediction
Koumétio Tékouabou, Stéphane Cédric; Gherghina, … - In: Journal of Risk and Financial Management 15 (2022) 6, pp. 1-19
The use of machine learning (ML) methods has been widely discussed for over a decade. The search for the optimal model is still a challenge that researchers seek to address. Despite advances in current work that surpass the limitations of previous ones, research still faces new challenges in...
Persistent link: https://www.econbiz.de/10014332470
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Cover Image
A machine learning framework towards bank telemarketing prediction
Koumétio Tékouabou, Stéphane Cédric; Gherghina, … - In: Journal of risk and financial management : JRFM 15 (2022) 6, pp. 1-19
The use of machine learning (ML) methods has been widely discussed for over a decade. The search for the optimal model is still a challenge that researchers seek to address. Despite advances in current work that surpass the limitations of previous ones, research still faces new challenges in...
Persistent link: https://www.econbiz.de/10013273676
Saved in:
Cover Image
Portfolio performance under tracking error and benchmark volatility constraints
Hausner, Jan Frederick; Van Vuuren, Gary - In: Journal of Economics, Finance and Administrative Science 26 (2021) 51, pp. 94-111
Purpose: Using a portfolio comprising liquid global stocks and bonds, this study aims to limit absolute risk to that of a standardised benchmark and determine whether this has a significant impact on expected return in both high volatility period (HV) and low volatility period (LV)....
Persistent link: https://www.econbiz.de/10013192195
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Cover Image
Portfolio performance under tracking error and benchmark volatility constraints
Hausner, Jan Frederick; Van Vuuren, Gary - In: Journal of economics, finance & administrative science 26 (2021) 51, pp. 94-111
Purpose: Using a portfolio comprising liquid global stocks and bonds, this study aims to limit absolute risk to that of a standardised benchmark and determine whether this has a significant impact on expected return in both high volatility period (HV) and low volatility period (LV)....
Persistent link: https://www.econbiz.de/10012598597
Saved in:
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