Naslov
Random Forest and Grey methodology in dynamic portfolio selection

Autori
Škrinjarić, Tihana ; Vlah Jerić, Silvija

Vrsta, podvrsta i kategorija rada
Poglavlja u knjigama, znanstveni

Knjiga
Artificial Intelligence and Big Data for Financial Risk Management Intelligent Applications

Urednik/ci
Metawa, Noura ; Hassan, M. Kabir ; Metawa, Saad

Izdavač
Routledge

Grad
London : Delhi

Godina
2022

Raspon stranica

ISBN
9780367700560

Ključne riječi
portfolio selection ; investment strategies ; Random Forest ; Grey methodology

Sažetak
This chapter deals with dynamic portfolio selection. The main methodological approaches are the Machine Learning (ML) method Random Forest and the Grey Relational Analysis (GRA) within Grey System Theory. Although many approaches of forecasting and portfolio selection exist today, this chapter combines approaches which have been proven in previous literature as being efficient and robust. Previous research deals with one or another approach, but here we use the forecasts from fandom forests to rank stock indices via the Grey approach in order to make the decision on the structure of the portfolio. The empirical analysis includes selected stock market indices, for the period 2015-2020. Firstly, daily data is used for the ML part and forecasting. Next, the out of sample forecasts are used to construct weekly data for the portfolio return and risk. Trading strategies are simulated so that comparisons can be made between those which are based on the approaches of this chapter and those which are usual benchmarks from portfolio theory. Since the results are promising, future research and applications could take into consideration such an approach.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo, Ekonomija

POVEZANOST RADA