The Investment Strategies of Sovereign Wealth Funds

  • Abdulaziz Alosaimi

Student thesis: Phd

Abstract

Sovereign Wealth Funds (SWFs) have become key players in global financial markets, managing portfolios totalling some $7.06 trillion at the end of 2014. SWFs are state-owned investment funds, set up to fulfil a variety of objectives through investing in well diversified investment portfolios. SWFs' official statements suggest that they are primarily seeking optimum risk-adjusted return, but may also aim to achieve various national objectives. This research investigates the investment strategies of SWFs. Using a data set of public equity holdings for 30 SWFs from 2001 to 2012, we conduct a comparative analysis for SWFs with two benchmarks of institutional investors. We also conduct several intra-SWF analyses to examine the impact of the sovereign nature of SWFs on their investment behaviour. We end the research with a case study of the organizational structure and investment practice of a well-known SWF. The results reveal that SWFs are a distinctive class of investors with a unique set of investment preferences. SWFs behave as long-term investors with no concern for the market liquidity of target firms or their recent stock performance. As fiduciaries that work under intensive public supervision, SWFs heavily weight prudence considerations in their investment decisions. They tend to act as passive investors with no intention of being involved in a target firm's management. Their sovereign nature appears to affect their investment style. SWFs with a national development agenda favour firms with high innovation capacity. Our tests fail to find any evidence of SWFs' political motives that might harm reception markets. SWFs strongly prefer firms in markets with a high level of governance and sound institutional structure. Further tests reveal that well governed SWFs act more efficiently and target those firms with better performance. The case study uncovers the complexity of an SWF's organizational structure, which vindicates why an analysis of SWFs' aggregate portfolios is highly challenging.
Date of Award31 Dec 2015
Original languageEnglish
Awarding Institution
  • The University of Manchester
SupervisorThomas Kirchmaier (Supervisor) & Mohammad Salehnejad (Supervisor)

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