TY - GEN
T1 - Portfolio Optimisation Using Ulimisana Optimisation Algorithm
AU - Maumela, Tshifhiwa
AU - Nelwamondo, Fulufhelo
AU - Marwala, Tshilidzi
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - In this paper we investigated the exploration and exploitation abilities of Ulimisana Optimisation Algorithm (UOA) in optimising the stock portfolio where it bal-ances between risk and returns from each asset while diversifying the portfolio. This algorithm's performance was compared to Particle Swarm Optimisation (PSO) and Grey Wolf Optimisation (GWO) and it was observed that though PSO and GWO resulted in high Sharpe Values, they did this by constantly updating their weight positions to be beyond the upper and lower bounds thus showing that they failed to have incremental position changes while optimising this portfolio. UOA was able to increase the weights for each asset incrementally and within the lower and upper bounds thus resulting in a more diversified portfolio. From a risk management perspective, the results from UOA are better than those of the PSO and GWO approaches.
AB - In this paper we investigated the exploration and exploitation abilities of Ulimisana Optimisation Algorithm (UOA) in optimising the stock portfolio where it bal-ances between risk and returns from each asset while diversifying the portfolio. This algorithm's performance was compared to Particle Swarm Optimisation (PSO) and Grey Wolf Optimisation (GWO) and it was observed that though PSO and GWO resulted in high Sharpe Values, they did this by constantly updating their weight positions to be beyond the upper and lower bounds thus showing that they failed to have incremental position changes while optimising this portfolio. UOA was able to increase the weights for each asset incrementally and within the lower and upper bounds thus resulting in a more diversified portfolio. From a risk management perspective, the results from UOA are better than those of the PSO and GWO approaches.
UR - http://www.scopus.com/inward/record.url?scp=85134345358&partnerID=8YFLogxK
U2 - 10.1109/CoDIT55151.2022.9803923
DO - 10.1109/CoDIT55151.2022.9803923
M3 - Conference contribution
AN - SCOPUS:85134345358
T3 - 2022 8th International Conference on Control, Decision and Information Technologies, CoDIT 2022
SP - 1250
EP - 1254
BT - 2022 8th International Conference on Control, Decision and Information Technologies, CoDIT 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th International Conference on Control, Decision and Information Technologies, CoDIT 2022
Y2 - 17 May 2022 through 20 May 2022
ER -