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Pregled bibliografske jedinice broj: 929713

Portfolio optimization using preference relation based on statistical arbitrage


Mrčela, Lovre; Merćep, Andro; Begušić, Stjepan; Kostanjčar, Zvonko
Portfolio optimization using preference relation based on statistical arbitrage // International Conference on Smart Systems and Technologies (SST), Osijek, Croatia, 2017.
Osijek, Croatia, 2017. str. 161-165 doi:10.1109/SST.2017.8188688 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


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, Croatia, 18-20.10.2017

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


Projekt / tema
HRZZ-UIP-2014-09-5349 - Algoritmi za mjerenje sustavskog rizika (Zvonko Kostanjčar, )

Ustanove
Fakultet elektrotehnike i računarstva, Zagreb

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