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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/9025

Title: Measuring The Investment Risk and Using Annuities to Determine The Expected Liability of Pension Funds:A case study of the Social Security and National Insurance Trust (SSNIT)
Authors: Cornah, Morkeh
Issue Date: 30-Sep-2016
Abstract: Effective management of investment risk is essential for every institution which is exposed to investment risk. Pension funds in Ghana are especially exposed to investment risk due to increasing investment risk factors exposed to the market. Pension fund exist to provide benefits to its members, therefore members are mainly concerned with losses as far as it decreases the value of their benefits. These losses usually occur as a result of the pension fund investing in the financial market and portfolio mismatching, which makes the tradeoff between risk and return a topic that most pension fund (investors) must consider carefully before an investment decision is made. The study uses the concept and methodology of the “value at risk" risk measure which is a tool for measuring an entity’s exposure to market risk, to determine the maximum loss of the investment portfolio of SSNIT on the Ghana capital market. The maximum loss of the scheme’s investment is quantified under the variancecovariance method of computing value-at-risk using an implementation of portfolio consisting of twenty-three stocks for 30 time interval with the confidence level of 95%, 99% and 90%.The study further used the whole life annuity model with mortality data to determine the expected liability to be paid by the fund to its members. Based on the normality of the distribution of the portfolio risk factors at 95% confidence level,the maximum loss of SSNIT is quantified under the 95% confidence level.
Description: A thesis submitted to the department of mathematics, Kwame Nkrumah University of Science and Technology in partial fufillment of the requirements for the degree of MSc. Actuarial Science , 2016.
URI: http://hdl.handle.net/123456789/9025
Appears in Collections:College of Science

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