Pregled bibliografske jedinice broj: 929713
Portfolio optimization using preference relation based on statistical arbitrage
Portfolio optimization using preference relation based on statistical arbitrage // International Conference on Smart Systems and Technologies (SST), Osijek, Croatia, 2017.
Osijek, Hrvatska, 2017. str. 161-165 doi:10.1109/SST.2017.8188688 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 929713 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Portfolio optimization using preference relation based on statistical arbitrage
Autori
Mrčela, Lovre ; Merćep, Andro ; Begušić, Stjepan ; Kostanjčar, Zvonko
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
International Conference on Smart Systems and Technologies (SST), Osijek, Croatia, 2017.
/ - , 2017, 161-165
Skup
2017 International Conference on Smart Systems and Technologies (SST)
Mjesto i datum
Osijek, Hrvatska, 18.10.2017. - 20.10.2017
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Portfolios ; Decision making ; Optimization ; Prediction algorithms
Sažetak
Abstract: We propose a new algorithm for portfolio optimization based on statistical arbitrage, that uses a multi-criteria decision making approach to obtain the most preferred assets. A preference flow graph of financial assets is constructed at each time step, with the aid of statistical arbitrage algorithm that describes preferences among the assets. Then, the individual preferences for each asset are obtained by using the potential method, and the most preferred assets are selected into the portfolio in accordance to them. A consistency measure of the preference flow graph is also obtained using the same method, and it measures the reliability of the decision making. The proposed method has been tested on a selection of S&P 500 constituent stocks from 1980 to 2004. The results indicate that the proposed method performs well in the considered market, which is indicated by high Sharpe ratios of the constructed portfolios. We also report that the algorithm performs better when provided with a larger number of assets, showing that the increased number of considered assets provides more insight into the market behavior.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo, Interdisciplinarne tehničke znanosti, Informacijske i komunikacijske znanosti
POVEZANOST RADA
Projekti:
HRZZ-UIP-2014-09-5349 - Algoritmi za mjerenje sustavskog rizika (ASYRMEA) (Kostanjčar, Zvonko, HRZZ ) ( CroRIS)
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb
Profili:
Lovre Mrčela (autor)
Andro Merćep (autor)
Stjepan Begušić (autor)
Zvonko Kostanjčar (autor)