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Asset allocation of the Norwegian Government Pension Fund Global with programming in Python

Thorp, Ida Christine Korme; Yttervik, Martine Hauahei
Master thesis
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Master Thesis Preliminary Report.pdf (1.262Mb)
URI
http://hdl.handle.net/11250/2579687
Date
2018
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  • Master of Science [1823]
Abstract
This thesis aims to assess if the optimal asset allocation for the Norwegian

Government Pension Fund – Global could be improved. We were curious to see if

we were able to optimize the portfolio by only looking at the risk-return

relationship, without taking political, economic or ethical interest into evaluation.

Since Norges Bank Investment Management has expressed that they do not have

the absolute answer for what is the optimal asset allocation, we were interested to

research whether or not we could obtain better results by purely examine the

financial performance. The research set out to calculate the optimal portfolio

weighting from historical data collected from 2008 until 2018. To analyze and

compare the results we used the FTSE Benchmark Index, which is the benchmark

used for the Government Pension Fund – Global. Therefore, we tried to replicate

the FTSE benchmark by using 25 of the same countries in our portfolio. Upon

advice from our supervisor we chose to program our own portfolio optimizer from

scratch with Python as our programming tool. We constructed the different

portfolios and divided them into constant expected return and time-varying

expected return. Even though this was much more time consuming than using

another software, we found it to be rewarding. As expected, our results showed

that with our asset allocation we did not outperform the benchmark, except one

portfolio that is rather close. However, this portfolio was closer than one should

assume – compared to the benchmark Norges Bank uses that has considerably

more complexity and more political-economic decisions behind its investment

strategy. So – is it possible to rather concentrate on the return and variance tradeoff

instead off introducing the vast complexity of several influencing factors.
Description
Masteroppgave(MSc) in Master of Science in Business, Economics/Masteroppgave(MSc) in Master of Science in Business, Finance - Handelshøyskolen BI, 2018
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Handelshøyskolen BI

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