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\title{Analysis of Sovereign Wealth Funds: From Asset Allocations to Growth}
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             \author[1]{Antonia  Ficova}

             \affil[1]{  PANEUROPEAN UNIVERSITY}

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\date{\small \em Received: 3 February 2015 Accepted: 28 February 2015 Published: 15 March 2015}

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\begin{abstract}
        


This paper explores forecast of future growth of Sovereign Wealth Funds, we used data of number of funds that were created during period from 1976 to 2012. In this regard, we found that number of SWF´s will rise during period 2013-2030 by 61 from 74 to 135, it means an increase of number of funds by 82.43 percent more compared with during period 1876 till 2012. Second, we provide asset allocations of 14 observed SWFs and different strategies. Third, we examine if Sovereign Wealth Funds will play important role in the future, moreover in terms of assets under management of 74 observed funds in 2014. In addition to this, we found that that 93.21 percent of changes in assets under management of Sovereign Wealth Funds can be attributed to changes (investments) in each future quarters.

\end{abstract}


\keywords{sovereign wealth fund, asset allocation, SWOT analysis.}

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\let\tabcellsep& 	 	 		 
\section[{Introduction}]{Introduction}\par
overeign Wealth Funds (SWFs) has primarily focused on their unique ability to merge the most feared elements of the public and private sectors: the power of private finance and state coerciveness. More to the point, SWFs were not originally created to establish the perfect blend of state centric coercive power and market oriented financial acumen, but to solve very real economic policy dilemmas. In other words, SWFs increased their importance in the global financial system in the last decade and especially during the financial crisis period. Ergo, the overall investment appraisal framework plays an important role in ensuring that the SWFs strategic objectives are achieved, in other words that the acquisition process is supported by rigorous, robust financial analysis. In sum, this will help SWFs to satisfy their fundamental aims, including capital preservation, value creation and furthering the national agenda.\par
However, the investment appraisal framework is a fundamental part of a SWFs operations and this can, S and should, be continually reviewed to identify areas for improvement. Viewed in this light, the cause for deals proving successful or unsuccessful can, in a large part, be tracked by following factors: first, back to the original investment, second, the quality of the decision-making and lastly, level of challenge arising from the investment appraisal framework. However, investments of SWFs is already increasing. On the one hand, SWFs work to boost economic diversification, on the other hand they seek performance and returns when they invest internationally. Nonetheless, the influence of SWFs has become undeniable, with total assets topping USD 6.585 tn in June 2014, these investors have reached a size comparable to that of the entire alternative assets industry. According to International Sovereign Wealth Fund Institute 2012 report comparing the assets under management (AUM) of these funds with the market capitalization of 16 top stock exchanges of the world suggests, that the AUM of SWFs are more than all the exchanges except NYSE Euronext (US) with market capitalization of USD 12.6 tn. 
\section[{a) The Objectives}]{a) The Objectives}\par
The research objectives of this paper are presented as follows: What is forecast of future growth of SWFs? Will play SWFs important role in the future? Are investments of the country that set up SWF closely related to gross domestic product, gross national savings, volume of exports of goods and services and general government gross debt? 
\section[{b) Data and Methodology}]{b) Data and Methodology}\par
The methods to be deployed in this thesis are qualitative and quantitative analysis, comparative research. On the other hand, literature concerning these funds is contained mostly in financial institutions research, macroeconomic publications of countries, academics. In this regard, we also use analytic, statistical methods, regression analysis, moving average, SWOT analysis. We present forecast of future growth of SWF´s, for calculations we used data of number of funds that were created during period from 1976 to 2012 according to the data from SWF Institute, last updated July 2014. We used linear trend by method of least squares. In addition to this, testing hypothesis we examine through method of least squares MLS, analysis of variance ANOVA. We examine if SWFs will play important role in the future, moreover in terms of AUM of 74 observed funds, and we used quarterly data from website of Sovereign Wealth Funds Institute, last updated July 2014. Than we examine whether the investments of country that set up SWF is closely related to following variables x: gross domestic product, gross national savings, volume of exports of goods and services and general government gross debt. Ergo, we observe 45 countries with SWFs according to the data from Sovereign Wealth Fund Institute, and World Economic Outlook of IMF, 2013. 
\section[{c) Structure of the Study}]{c) Structure of the Study}\par
The remainder of this paper proceeds as follows: Section 2 provides variety of definitions on this subject. First, we present a number of studies on the subject of SWFs since 2007 till 2014, more to the point among authors examined this subject. Second, we present where SWFs invest, in short we provide latest available asset alocation of 14 observed SWFs. Than, we also focus on future growth of SWFs. Section 3 includes testing hypotheses, section 4 contains SWOT analysis and section 5 concludes the paper. 
\section[{II.}]{II.} 
\section[{Literature Review}]{Literature Review}\par
However, for better understanding how a Sovereign Wealth Fund (SWF) may impact to foreign economic policy it is necessary to describe variety of definitions of this subject. More to the point,  {\ref McKinsey \& Company (2007)} describes that SWFs are funded by the Central Bank's reserves, aimed to maximize the returns within manageable risk bands. On the one hand, according to the Organisation for Economic Cooperation and Development (OECD-August 2008) SWFs are essentially: foreign exchange reserves, the sale of scarce resources such as oil, or from general tax and other revenue. On the other hand, the EU Commission (2008) describes SWFs as state owned investment vehicles, which manage a diversified portfolio of domestic and international financial assets. In other words, SWF´s are mainly created when countries have surplus revenues, reserves and their governments feel it would be advantageous to manage these assets with a view to future liquidity requirements and as a way of stabilising irregular revenue streams argued by Gugler, P.; Chaisse, J. (2009). Alter, \hyperref[b19]{Miracky and Bortolotti (2009)} presented definitions of SWFs as follows: (i) an investment fund rather than an operating company, (ii) that is wholly owned by a sovereign government, in other words organized separately from the central bank or finance ministry to protect it from excessive political influence, (iii) that makes international and domestic investments in a variety of risky assets, (iv) that is charged with seeking a commercial return, and (v) a pension fund, the fund is not financed with contributions from pensioners and does not have a stream of liabilities committed to individual citizens.\par
It is important to mention a number of studies on the subject of SWFs since 2007. In this section we present related research of academics. Jones, S. G. -Ocampo, J. A.,  {\ref (2008)} presented in details the evolution of foreign exchange assets in different parts of the developing world, optimal reserves, developed a broader framework for the analysis of the motives for the accumulation of foreign exchange assets.  {\ref Matoo}   
\section[{a) Objectives of SWF´s}]{a) Objectives of SWF´s}\par
There are many SWFs with multiple objectives, based on Al-Hassan, A. et al.  {\ref (IMF, 2013)} and the Santiago Principles taxonomy, five types of SWFs can be distinguished as follows: First, stabilization funds are set up to insulate the budget and economy from commodity price volatility and external shocks (e.g., Chile (Economic and Social Stabilization Fund), Timor-Leste, Iran, and Russia (Oil Stabilization Fund)). Their investment horizons and liquidity objectives resemble central banks reserve managers, in view of their role in countercyclical fiscal policies to smooth boom/bust cycles. They tend to invest largely in highly liquid portfolio of assets (and sometimes in instruments that are negatively correlated with the source of risk being addressed with the fund) by allocating over 80 percent of their assets to fixed income securities, with government securities consisting around 70 percent of total assets. Second, savings funds intend to share wealth across generations by transforming nonrenewable assets into diversified financial assets (Abu Dhabi Investment Authority, Libya, Russia (National Wealth Fund)). Third, development funds are established to allocate resources to priority socioeconomic projects, usually infrastructure (e.g., UAE (Mubadala) and Iran (National Development Fund)). Fourth, Pension reserve funds are set up to meet identified outflows in the future with respect to pensionrelated contingent-type liabilities on the government's balance sheet (e.g., Australia, Ireland, and New Zealand). They held high shares in equities and other investments to offset rising pension costs. Fifth, reserve investment corporations intend to reduce the negative carry costs of holding reserves or to earn higher return on ample reserves, while the assets in the funds are still counted as reserves (e.g., China, South Korea, and Singapore). To achieve this objective, they pursue higher returns by high allocations in equities and alternative investments, with up to 50 percent in South Korea and 75 percent in Singapore's Government Investment Corporation. 
\section[{b) Asset Allocations}]{b) Asset Allocations}\par
Moreover, asset allocation designs the longterm strategic neutral benchmark for the total portfolio, with goal of maximise expected returns subject to risk tolerances and liquidity constraints. However, risk is defined as the probability of a loss or underperformance relative to a reference asset, such as T-bill or a government bond, over a given horizon. On longer horizons, equities are less volatile than short-term instruments because of the reinvestment risks associated with short-term investments. In nuce, infrastructure, real estate, and private equity are long investment horizons because of ability to invest in illiquid assets to enjoy the illiquidity premium. In other words, SWF´s assets and the returns can have a significant effect especially on public finances, monetary conditions, external accounts and balance sheet linkages with the rest of the world. IMF (2013) presents following factors: First, Fiscal policy might be affected by SWF funding and withdrawal rules that are usually derived from a fiscal rule. Second, monetary policy may be impacted by wide fluctuations in fiscal revenues and procyclical implications for aggregate demand that typically affect inflation and the real exchange rate. Third, exchange rate variations could be mitigated by investing the SWF's resources abroad.\par
i. Analysis of observed asset allocations Strategic asset allocation optimize allocation proportions of each asset class (bonds, equities, alternative investment). We provide latest available asset allocation of 14 observed SWFs. Therefore, the section follows compares the actual asset allocations of savings funds, stabilization/savings funds, pension reserve funds, reserve investment funds. For this purpose, we categorize assets into four classes: allternative assets, fixed income, cash and public equties. Alternative assets may include private equity, hedge funds, property, commodities, infrastructure, forests, absolute return.\par
Infrastructure projects include transportation/logistics, power/energy and utilities (e.g., water, waste water, natural gas networks). Fixed income includes bills, notes, and bonds of the treasury, and corporate bonds. Cash includes current accounts and other cash-equivalent instruments. Public equities comprise domestic and global stocks, including those of both developed and emerging markets.   Figure  {\ref 3} includes average of data of Ireland, National Pensions Reserve Fund -1Q 2014, Australia Future Fund -1Q 2014, New Zealand Superannuation Fund -2Q 2013. NPRF Ireland decreased investments in public equties from 33.7 percent in 2012 to 24.1 percent in 1Q 2014, and also by 13.3 percent decreased investments in alternative assets. Australia´s fund invested 34.70 percent in alternative assets, an increase by 4.70 percent in comparison with New Zealand Supernnuation Fund. New Zealand holds by 18.4 percent more in public equties compared with Australia´s fund. Australia´s fund focus on more liquid credit sectors this includes areas such as investment grade corporate credit, higher quality asset backed securities, and some areas of the liquid high-yield and corporate loans markets, exposure to alternative or nontraditional risk premia such as commodities, volatility and re-insurance. Figure  {\ref 4}   
\section[{c) Size}]{c) Size}\par
What explains the size differences of SWFs? The size of a SWF´s depend primarily on its purpose and the size and wealth of the state funding it. Nevertheless the exact size of the funds is uncertain due to the opaque nature of SWF´s. More to the point, the relative size of an SWF compared to the whole economy can be quite substantial, especially for the older SWFs. Viewed in this light, in case of the Republic of Kiribati's Revenue Equalization Reserve Fund, SWF assets amount to three times the country's GDP explained by Curzio/Miceli (2010). In sum, the SWF puts the country in a relatively comfortable position, because it represents a cushion for future governmental funding gaps.\par
i. Forecast of increase number of SWFs At this point we focus on future growth of SWF´s, for calculations we used data of number of funds that were created during period from 1976 to 2012 according to the data from SWF Institute last updated July 2014. We used linear trend by method of least squares. According to the number of funds we see an increase by 3 funds annually, forecast from 2013 to 2030 illustrated in Figure 5 and 6. By using values (years; T, y) through graphs we obtained formula y = 0.0254x -47.915, R 2 = 0.1777 (see Figure \hyperref[fig_3]{2}). Then we calculated by using this formula others variables in Table  {\ref Y\textasciitilde }; (y/Y\textasciitilde )*100; \% coeficient. Then by using T* and y, we may obtain formula y = 0.0254x + 2.6762, R 2 = 0.17771. We used this formula for calculations of forecasts, moreover our value y from 2013 till 2030.\par
Regression output which depicted in Figure 5-6 is much more positive in the favor of positive linear relationship. The most important statistics here is that coefficient of determination R 2 is 17 percent of total variation around the mean value of y is explained by the variable x included in the model, so quite well for a cross sectional regression analysis. And 17.77 percent of change of numbers of funds is caused by year, so 82.23 percent change of number of funds is not attributed by year of set up. However, number of SWF´s will rise during period 2013-2030 by 61 from 74 to 135, it means an increase of number of funds by 82.43 percent more compared with during period 1876 till 2012. In short, SWF´s are not a new phenomenon, but by increasing number of funds show their presence in global finance and economic and financial relations. 
\section[{Global Journal of Management and Business Research}]{Global Journal of Management and Business Research} 
\section[{III.}]{III.} 
\section[{Hypotheses}]{Hypotheses}\par
Based on data analyzed for the paper, we developed following hypothesis and preliminary results We formulate next hypothesis in terms of Assets Under Management of 74 observed funds, and we used quarterly data from website of Sovereign Wealth Funds Institute, last updated July 2014. We composed hypothesis as follows:\par
H 0 : SWFs will play an important role in international finance in the future.\par
H 1 : SWFs will NOT play important role in international finance in the future. If we look at moving average, one of the basic tools of technical analysis, was based on the fact that determining the trend from the graph can be quite difficult and inaccurate, due to cyclical fluctuations. We used functions of a moving average, presented in Appendix B, for identifing trends and measure the strength of an AUM of SWFs. Moving averages can be beneficial in setting stop-losses. The number of periods for moving average is K=3 constant. A simple moving average is calculated as the sum of values in a given time period divided by the number of values.\par
As is revealed by Figure 7 the coefficient of correlation is positive and the coefficient of determination is R 2 =0.9321; what means that 93.21 percent of changes in AUM of SWFs can be attributed to changes (investments) in each future quarters. In short, we may say that SWF will be bigger than today, more highly liquid, and focus long-term, less sensitive than for example Hedge Funds, Private Equity. 
\section[{b) Testing Hypothesis II.}]{b) Testing Hypothesis II.}\par
At this point we want to know whether the investments of country that set up SWF is closely related to following variables x: gross domestic product, gross national savings, volume of exports of goods and services and general government gross debt. We will use regression analysis, transferring observed data using the least squares method. Lets analyze the impact  The significance of F is 0.0180<0.05; what is statisticaly significant (+). The parameter ? is high statistically significant because the P-value is 0.000159466<0,01; (++). The parameter x 1 is not statistically significant because the P-value is 0.383368228>0,05; (-). The parameter x 2 is high statistically significant because the P-value is 0.000786096<0,01; (++). The parameter x 3 is not statistically significant because the P-value is 0.18496218>0,05; (-). The parameter x 4 is not statistically significant because the P-value is 0.492766467>0,05; (-). The parameter x 5 is not statistically significant because the P-value is 0.556055605>0,05; (-). And we obtained regression function as follows: y=15.54359971 + 0.000481477x 1 + 0.3790898x 2 -0.269225351x 3 -0.126713805x 4 -0.027351623x 5 . More to the point, if we want to calculate the total investments of the country of Angola, we get after substituting into the regression function;y=15.54359971+0.000481477*121.704+0.379 0898*18.242-0.269225351*9.291-0.126713805*0.959-0.027351623*26.638=19.16607; that shows 19.16 percent of total investments of GDP.\par
At this point we want to test the assumption of mean value of random residuals will be zero, according to the results from Residual outputs below. We formulate hypothesis as follows:\par
We may use formula above. As a result coming out from this formula we can say that average residuals is low, the mean value is close to zero, so we accept null hypothesis.\par
IV. 
\section[{Swot Analysis}]{Swot Analysis}\par
At this point, after our research, we provide SWOT analysis below that briefly analyzes SWFs. We use these an analytic method to determine competitive strengths, competitive weaknesses, opportunities and threats of the funds. In this regard, through clearly identifying these factors may funds, companies, etc. determine the future development, formulate strategy and an appropriate policy strategy. H 0 : H 1 : 0 ? ? ? ? ? ? ? ? u E 0 ? ? ? ? ? ? ? ? u E 15 - -1.53951E ? ? ? ? n e x i e 
\section[{Strengths}]{Strengths}\par
Weaknesses Notwithstanding, SWFs have recently drawn a great deal of attention, both in the popular press and academic research. Moreover, some of the attention is based on world leaders' and policy makers' discomfort with the unknown, as SWFs often fail to disclose their investment objectives. However, we can say that SWFs will play important role in future as a global investors.? 
\section[{VI.}]{VI.}\par
The question are: Do SWFs appear to be similar with regard to their type and funding? What did cause their different asset allocations, growth across them? We contributed with findings that are mentioned in previous section, in short, in terms of asset allocation of SWF, whereas savings funds have varying proportions of public equities in their portfolios, debt (fixed income) are typically for stabilization SWFs. In sum, differences in observed asset allocations of SWFs may be due to reasons, including the investment objective, investment strategy (investment horizon), investment portfolio (strategic, tactic, target asset allocation), investment risk (portfolio, credit, liquidity, currency and interest rate, risk due to fact uncertainty in financial markets), investment return, opportunity cost, the funding source or sovereign balance sheet.\par
Consequently, we identified that savings funds invest 1.97 percent in cash, and the most part of assets holds 54.12 percent in public equities. Stabilization/savings funds invest 39 percent into fixed income, pension reserve funds invest into 42.80 percent into public equties, and reserve investment funds holds 41 percent in public equities. Moreover, we identified differences of 14 observed funds in their investment strategies. Whereas savings funds have varying proportions of public equities in their portfolios, cash figures are excluded except Botswana Pula Fund. Funds with stabilization/savings objectives usually invest more in fixed income. Pension reserve funds had the most assets in cash and on the other hand reserve investment funds holds assets in fixed income.\par
We found that forecast of numbers of SWFs shows that coefficient of determination R2 is 17 percent of total variation around the mean value of y is explained by the variable x included in the model, so quite well for a cross sectional regression analysis. Viewed in this light, 17.77 percent of change of numbers of funds is caused by year, so 82.23 percent change of number of funds is not attributed by year of set up. However, SWF´s must provide frequent reports for ministry of finance, the central bank and the fund's independent management checks and balances by the legislative branch.\par
We examined that SWF will play important role in the future. In short, coefficient of correlation is positive and the coefficient of determination is R2=0.9321; that resulted that 93.21 percent of changes in assets under management of SWFs can be attributed to changes (investments) in each future quarters. In sum, we may say that SWF will be bigger than today, more highly liquid, and focus long-term, less sensitive than for example Hedge Funds, Private Equity.\par
We came to the conclusion that investments of country that set up SWF is closely related to following variables x: gross domestic product, gross national savings, volume of exports of goods and services and general government gross debt. In this regard, the correlation coefficient is 0.5351 (Multiple R), positive in the favor of positive linear relationship, it means high dependency between y (investments of country) and observed variables. The coefficient of determination R2 = 0.2864 means that 28.64 percent changes of total investments of the country that set up SWF is attributed by changes of our variables X; so 71.36 percent of changes of investmenst of countries is attributed by other variables. On the other hand, the significance of F is 0.0180<0.05; what is statisticaly significant (+). The parameter ? is high statistically significant because the P-value is 0.000159466<0,01; (++).\begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-2.png}
\caption{\label{fig_0}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{34}\includegraphics[]{image-3.png}
\caption{\label{fig_1}Figure 3 : 4 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{121}\includegraphics[]{image-4.png}
\caption{\label{fig_2}Figure 1 : 2 :Figures 1}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2}\includegraphics[]{image-5.png}
\caption{\label{fig_3}Figure 2}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-6.png}
\caption{\label{fig_4}}\end{figure}
    \begin{figure}[htbp]
\noindent\textbf{1} \par 
\begin{longtable}{P{0.85\textwidth}}
Year 2015\\
Volume XV Issue IX Version I\\
( )\\
Global Journal of Management and Business Research\end{longtable} \par
  {\small\itshape [Note: C]} 
\caption{\label{tab_1}Table 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2} \par 
\begin{longtable}{P{0.3678571428571429\textwidth}P{0.00892857142857143\textwidth}P{0.15535714285714283\textwidth}P{0.12857142857142856\textwidth}P{0.10714285714285714\textwidth}P{0.08214285714285714\textwidth}}
\multicolumn{2}{l}{Difference}\tabcellsep SS -sum of\tabcellsep MS -mean\tabcellsep F\tabcellsep The\\
\tabcellsep \tabcellsep squares\tabcellsep squares\tabcellsep \multicolumn{2}{l}{significance of}\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep F\\
Regression\tabcellsep 5\tabcellsep 1429.069\tabcellsep 285.813\tabcellsep 3.130\tabcellsep 0.018\\
Residues\tabcellsep 39\tabcellsep 3560.182\tabcellsep 91.286\tabcellsep \tabcellsep \\
Total\tabcellsep 44\tabcellsep 4989.251\tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep \tabcellsep Coefficients\tabcellsep Standard Error\tabcellsep t Stat\tabcellsep P-value\\
Investment\tabcellsep \tabcellsep 15.543\tabcellsep 3.718\tabcellsep 4.179\tabcellsep 0.000\\
Gross domestic product,\tabcellsep \tabcellsep 0.000\tabcellsep 0.000\tabcellsep 0.881\tabcellsep 0.383\\
current prices\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
Gross national savings\tabcellsep \tabcellsep 0.379\tabcellsep 0.104\tabcellsep 3.641\tabcellsep 0.000\\
\multicolumn{2}{l}{Volume of imports of goods}\tabcellsep -0.269\tabcellsep 0.199\tabcellsep -1.349\tabcellsep 0.184\\
and services\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{2}{l}{Volume of exports of goods}\tabcellsep -0.126\tabcellsep 0.182\tabcellsep -0.692\tabcellsep 0.492\\
and services\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{2}{l}{General government gross}\tabcellsep -0.027\tabcellsep 0.046\tabcellsep -0.593\tabcellsep 0.556\\
debt\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
  {\small\itshape [Note: Source: Author´s estimation.]} 
\caption{\label{tab_2}Table 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{3} \par 
\begin{longtable}{P{0.85\textwidth}}
Source: Author´s estimation\end{longtable} \par
 
\caption{\label{tab_3}Table 3 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{}
\end{longtable} \par
 
\caption{\label{tab_4}Table 4 :}\end{figure}
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