EDHEC-Risk Integrated approach to sovereign wealth risk management

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  • EDHEC-Risk Integrated approach to sovereign wealth risk management
  • EDHEC-Risk Integrated approach to sovereign wealth risk management
  • EDHEC-Risk Integrated approach to sovereign wealth risk management
  • EDHEC-Risk Integrated approach to sovereign wealth risk management

Bernd Scherer, Professor of Finance, EDHEC Business School, Member, EDHEC-Risk Institute

Asset allocation for sovereign wealth funds (SWFs) predominantly focuses on optimal portfolio choice with non-tradable wealth (usually resource-based wealth like underground oil). In this framework SWFs will — depending on their preferences — allocate their resources towards a combination of minimum-variance portfolio, speculative demand and hedging demand (against oil price shocks). The generic advice from these models is to invest less in assets with strong positive oil price correlation and instead increase the exposure to recession-hedging assets like government bonds that pay off well if oil prices are down. SWFs following this advice would have avoided in 2008 the large losses incurred with more traditional asset allocation advice. This is essentially a risk management argument with strong support in economic theory. Oil price movements are unpredictable and volatile with extremely wide confidence intervals.

Little research so far has been undertaken in the area of FX reserve-related SWF investments. Resource-based SWF assets are financed through (owned/taxed) foreign currency earnings on commodity exports. These assets provide a very good representation of sovereign wealth that can be used to manage macroeconomic risks or intergenerational distribution. However, many Asian SWFs are instead financed from FX reserves after periods of significant reserve accumulation. Reserve accumulation in managed exchange rate regimes is usually accompanied by sterilisation (ie, the domestic currency created to purchase foreign assets is sterilised through local currency debt issuance). Given that we can think of these funds as being financed through borrowed funds (local currency debt) it is not always clear that they represent net sovereign wealth. In fact, not only do assets grow but so do liabilities (issued bonds for sterilisation purposes). As a consequence, increased economic leverage should induce more conservative asset allocation policies. This illustrates the need to move from an SWF-centric framework to an asset/liability approach integrating sovereign liabilities (monetary base, local and foreign debt). Instead of focusing on SWF assets and liabilities in isolation, the SWF is now integrated into total sovereign assets and liabilities. This is analogous to modern pension fund investing where a pension fund is being integrated into the corporate balance sheet and capital structure (enterprise-wide risk management) rather than managed in isolation. The size of local- and foreign-currency-denominated debt (or contingent liabilities towards pension systems or industries) relative to foreign reserves and sovereign assets will, for example, determine sovereign leverage and is expected to have a material impact on optimal sovereign asset management. Our research asks how to derive the optimal dynamic asset allocation (DAA) for sovereign assets given different drivers of economic risks as well as varying levels of debt.

Integrating economic leverage into the one-period model
So far SWF asset allocation has not taken liabilities into account. In fact, there is a widespread belief in the SWF literature that SWFs lack dedicated liabilities. While this is true from the bottom-up view of an SWF portfolio manager it is not true from the top-down view of a sovereign risk manager (sponsoring country). The approach taken in this section is to look at sovereign assets and liabilities in the same way as we would look at corporate assets and liabilities. We present a simplified version of a sovereign balance sheet that can be found in figure 1. All values are in foreign currency. The left side of the sovereign balance sheet contains sovereign assets. These contain FX reserves, the SWF and the present value of the primary budget. The latter can be thought of as the present value of future taxes minus future expenditures. It reflects the present value of economic surpluses from running a country. The right-hand side of the sovereign balance sheet describes how the economy is financed. We view the monetary base and local debt as equivalent to shares such that its local currency value multiplied by the current exchange rate resembles the sovereign market capitalisation. Foreign currency debt is treated as a senior claim. Sovereign default occurs if sovereign assets fall below foreign debt (in foreign currency). Given that default is costly (ie, it comes with frictional bankruptcy costs in the form of social unrest, capital flight, and so on) we treat the level of foreign currency debt as a hard threshold. If the Modigliani/Miller proposition applied on the sovereign level the asset allocation decision would be irrelevant. Moreover, the above approach offers only an approximate summary of the economic position of a sovereign sponsor. For example, we left out the sovereign sponsor's contingent liabilities against key industries (banks, for example).

An economy with zero foreign debt exhibits a leverage of 0%. Suppose our sovereign desires to maximise the long-term growth of net sovereign wealth (sovereign assets minus senior sovereign liabilities). Our model shows that economic leverage leaves hedging demand unchanged but has a material effect on speculative demand. High economic leverage leads to strongly reduced speculative demand. A SWF is not a standalone investment vehicle. Second, an SWF should find it desirable to invest in assets that have low correlation with changes in their primary budget. Assets that offer insurance in bad states for the particular sovereign sponsor (tail hedge) are even more desirable. Economies differ, and so should SWF asset allocation.

As examples we look at China, Russia and the Gulf Cooperation Council (GCC) countries. The main risk factor for the primary budget in China is a slowdown in US consumer demand. Hence a Chinese SWF should not hold US retail stocks (unless return expectations are high enough to generate enough speculative demand to offset negative hedging demand). In fact a Chinese SWF might want to sell short Wal-Mart stocks (the biggest US retail stock highly dependent on Chinese exports and the main distribution channel for cheap Chinese goods to Americans). On top of hedging a fall in US consumer demand it will also prove to hedge a renminbi appreciation. The situation in Russia is different. Here the Russian budget is strongly dependent on oil price growth combined with economic balance sheet leverage. Finally, the GCC countries share the dependence of Russia on oil revenues, but with much less economic balance sheet leverage (GCC countries have little outstanding foreign debt).

The multi-period model of SWF portfolio choice
Suppose the objective of the SWF is to maximise long-term portfolio growth of net sovereign wealth. Net wealth decreases as economic leverage increases. The sterilisation of accumulated FX reserves arising from undervalued exchange rates results in increased sovereign leverage and should hence lead to less aggressive investment policies. To model sovereign assets we use equity (MSCI US), bonds (Barclays Long Treasury Index) and cash (rolling one-month US T-bills). We assume the primary budget is driven by commodity prices (GSCI). All data are quarterly and run from Q1 1970 to Q4 2009. We assume n = 12 (three-year time horizon with quarterly rebalancing). Figure 2 shows the optimal equity allocation for a sovereign sponsor with 50% of sovereign wealth being tied up in sovereign financial assets for a one-period, four-period and eight-period investor.

Given the high volatility of the primary budget (approximated by GSCI commodities) even the most aggressive sovereign sponsor will invest only 25% in US equities. This amount falls as economic leverage increases. The remainder of the portfolio will be invested in bonds. For an investor with four periods to go the optimal asset allocation in the first period is higher than for a one-period myopic investor. This reflects the advantage of our dynamic stochastic programme. We can afford to invest a higher portion of current wealth in equities because we are aware that the optimal asset allocation can be reduced if period-one returns disappoint. This logic carries over to the eight-period investor. For low leverage there is virtually no difference between the optimal dynamic and the rollover myopic investor.

The impact of constraints
Investment guidelines designed by SWF risk management committees often impose target ranges for SWF asset allocation purposes. For example, if the target allocation to equities is set to 50%, tactical boundaries of 40% and 60% are set. While initially thought to be conservative this will reduce the benefit of purely risk-based dynamic decision making. Figure 3 shows the impact of a [70%/30%] range on the optimal equity allocation over time. The equity allocation is smaller over all time horizons when compared to the unconstrained case as risk management effectiveness is largely reduced. Our dynamic stochastic programme is not allowed to invest 100% in cash if leverage becomes very high.

This has consequences for the extent of the rebalancing advantage (advantage of dynamic decision-making versus a buy-and-hold investor) summarised in figure 4. We see that the rebalancing advantage is small for investors with little leverage. In this case the difference from a constrained solution is also small as the constraints do not bind. However, as we are increasing leverage the difference between optimal and myopic solutions grows and so does the advantage of having few constraints. Dynamic investment policies are even more desirable for highly leveraged sovereigns.

The author thanks Steffen Kern for his valuable comments and Deutsche Bank for its research support. This research is drawn from the Deutsche Bank research chair at EDHEC-Risk Institute on ‘Asset-Liability Management Techniques for Sovereign Wealth Fund Management'.


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