Analysis of a Stochastic Optimal Control for Pension Funds and Application to Investments in Lower Middle-Income Countries

Tolulope Latunde,Damilola Deborah Dare,Joseph Oluwaseun Richard,Opeyemi Odunayo Esan

doi:10.46481/jnsps.2020.22

Tolulope Latunde, Damilola Deborah Dare + Show 2 more

Open Access

https://doi.org/10.46481/jnsps.2020.22

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Abstract

One of the major problems faced in the management of pension funds and plan is how to allocate and control the future flow of contribution likewise the proportion of portfolio value and investments in risky assets. This work considers the management of a pension plan by means of a stochastic dynamic programming model based on Merton's model. The model is analyzed such that the conditions of optimal contribution and investment in risky assets are determined and sensitized. The case study of Nigeria, Ghana, Kenya is considered for various periods in the model simulation. Thus, the volatility condition obtained is used to estimate the efficiency of some important parameters of the model.

Highlights

One of the major problems faced in the management of pension funds and plan is how to allocate and control the future flow of contribution likewise the proportion of portfolio value and investments in risky assets
Pension plans are classified into two categories: The Defined Benefit (DB) and Defined Contribution(DC) scheme
The DB pension plan is mostly preferred by pension members due to his ability to bear the risk to the pension fund manager, while on the other hand DC pension fund plan on the other hand, is more popularly preferred by the pension fund managers due to its ability to transfer the risk to the pension fund members

Summary

Introduction

One of the major problems faced in the management of pension funds and plan is how to allocate and control the future flow of contribution likewise the proportion of portfolio value and investments in risky assets. The world Bank uses Gross National Income (GNI) per capita, in current U.S dollars converted by the Atlas method of a three-year moving average of exchange rates,as the basis for this classification. It views GNI as a broad measure and the single best indicator of economic capacity and progress. Revisions to population of roughly 48.5 million work at least part-time in the national accounts methods and data can influence GNI per agricultural sector, including livestock and pastoral activities

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Discussion

Conclusion