Computation of optimal investment allocations in a sequential portfolio optimisation

Orientation: This article is related to Financial Risk Management, Investment Management and Portfolio Optimisation. Research purpose: The aim is to compute optimal investment allocations from one period to another. Motivation of the study: Financial market systems are governed by random behaviour...

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Main Authors: Masiala Mavungu, Evan Hurwitz, Tshilidzi Marwala
Format: Article
Language:English
Published: AOSIS 2019-09-01
Series:Journal of Economic and Financial Sciences
Subjects:
Online Access:https://jefjournal.org.za/index.php/jef/article/view/416
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author Masiala Mavungu
Evan Hurwitz
Tshilidzi Marwala
author_facet Masiala Mavungu
Evan Hurwitz
Tshilidzi Marwala
author_sort Masiala Mavungu
collection DOAJ
description Orientation: This article is related to Financial Risk Management, Investment Management and Portfolio Optimisation. Research purpose: The aim is to compute optimal investment allocations from one period to another. Motivation of the study: Financial market systems are governed by random behaviours expressing the complexity of the economy and the politics. Risk Measure and Management are current and major issues for financial market operators and attract the attention of researchers who develop suitable tools and methods to describe and control risk. In this article, financial risk management is considered for an investor operating in the financial market. Research approach/design and method: This research developed Mathematical Models to describe the problem and Computational Simulations to compute, summarise the results and show their reliabilities. Main findings: The results are the investments allocations stored, some tables and the related computational simulations. By going from period one to another, one can notice from the graphs that the portfolio risk is decreasing and the portfolio profit increasing. Practical/managerial implications: The approach used in this article shows a way of solving rigorously any linearly constrained quadratic optimisation problem and any constrained nonlinear problem. It gives the ability of transforming judiciously certain linearly constrained nonlinear programming problems into sequences of linearly constrained quadratic problems and solving them efficiently. Contributions/value-add: This article developed Mathematical Models and Matlab Computer Optimisation Programs to give Computational Simulations. It wrote Computer Programs for a fifth-order autoregressive model to forecast asset profits.
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spelling doaj.art-f5fc857bcd1d4891bf26b85ebf28a2352022-12-21T21:19:26ZengAOSISJournal of Economic and Financial Sciences1995-70762312-28032019-09-01121e1e810.4102/jef.v12i1.416374Computation of optimal investment allocations in a sequential portfolio optimisationMasiala Mavungu0Evan Hurwitz1Tshilidzi Marwala2Department of Electrical and Electronic Engineering, University of Johannesburg, JohannesburgDepartment of Electrical and Electronic Engineering, University of Johannesburg, JohannesburgDepartment of Electrical and Electronic Engineering, University of Johannesburg, JohannesburgOrientation: This article is related to Financial Risk Management, Investment Management and Portfolio Optimisation. Research purpose: The aim is to compute optimal investment allocations from one period to another. Motivation of the study: Financial market systems are governed by random behaviours expressing the complexity of the economy and the politics. Risk Measure and Management are current and major issues for financial market operators and attract the attention of researchers who develop suitable tools and methods to describe and control risk. In this article, financial risk management is considered for an investor operating in the financial market. Research approach/design and method: This research developed Mathematical Models to describe the problem and Computational Simulations to compute, summarise the results and show their reliabilities. Main findings: The results are the investments allocations stored, some tables and the related computational simulations. By going from period one to another, one can notice from the graphs that the portfolio risk is decreasing and the portfolio profit increasing. Practical/managerial implications: The approach used in this article shows a way of solving rigorously any linearly constrained quadratic optimisation problem and any constrained nonlinear problem. It gives the ability of transforming judiciously certain linearly constrained nonlinear programming problems into sequences of linearly constrained quadratic problems and solving them efficiently. Contributions/value-add: This article developed Mathematical Models and Matlab Computer Optimisation Programs to give Computational Simulations. It wrote Computer Programs for a fifth-order autoregressive model to forecast asset profits.https://jefjournal.org.za/index.php/jef/article/view/416investment allocationsportfolio selectionportfolio optimisationdata forecastingrisk minimisationprofit maximisationsequential quadratic programming
spellingShingle Masiala Mavungu
Evan Hurwitz
Tshilidzi Marwala
Computation of optimal investment allocations in a sequential portfolio optimisation
Journal of Economic and Financial Sciences
investment allocations
portfolio selection
portfolio optimisation
data forecasting
risk minimisation
profit maximisation
sequential quadratic programming
title Computation of optimal investment allocations in a sequential portfolio optimisation
title_full Computation of optimal investment allocations in a sequential portfolio optimisation
title_fullStr Computation of optimal investment allocations in a sequential portfolio optimisation
title_full_unstemmed Computation of optimal investment allocations in a sequential portfolio optimisation
title_short Computation of optimal investment allocations in a sequential portfolio optimisation
title_sort computation of optimal investment allocations in a sequential portfolio optimisation
topic investment allocations
portfolio selection
portfolio optimisation
data forecasting
risk minimisation
profit maximisation
sequential quadratic programming
url https://jefjournal.org.za/index.php/jef/article/view/416
work_keys_str_mv AT masialamavungu computationofoptimalinvestmentallocationsinasequentialportfoliooptimisation
AT evanhurwitz computationofoptimalinvestmentallocationsinasequentialportfoliooptimisation
AT tshilidzimarwala computationofoptimalinvestmentallocationsinasequentialportfoliooptimisation