CASE STUDY

Emerging Market Debt

UK Local Government Pension Scheme | June 2017


Engagement at a glance

The UK Local Government Pension Scheme client sought an EMD manager that successfully blended emerging market hard currency (sovereign and corporates) and local currency within a standalone portfolio, with a view to investing £300 million.


CLIENT-SPECIFIC CONCERNS

The client already had exposure to emerging markets via local currency strategies. After performance challenges in local currency (2013 - 2015), their focus shifted to identifying a strategy which provided exposure to local rates and FX but offered better diversification and lower drawdowns. The primary objective was efficient use of risk.

A key consideration was the ability of the manager to execute the transition of their local currency portfolio to a blended portfolio. This was to avoid the added layer of complexity (and fees) involved in appointing a third-party transition manager.

Outcome

  • A strong level of manager participation was received, covering the entire breadth of blended EMD investment styles. These included absolute return strategies, benchmark aware strategies, dynamic asset allocation strategies and more bottom-up country selectors. Given the significant differences in styles and observed asset allocation, simple performance comparison yielded misleading results. As such, early analysis focused on the fit with the client’s objectives and observed risk characteristics.

  • Once a second stage shortlist was defined, comprehensive understanding of the factors which generate the final asset allocation of the portfolio was crucial, from idea generation and implementation to risk allocation, team structure and experience. Favoured strategies had a structured investment process with experience transitioning portfolios.

  • After detailed qualitative comparison and due diligence, narrowing the group to seventeen and then eight, the client invested with two managers with complementary investment styles: one dynamic absolute return, the other more benchmark-aware with efficient use of its tracking error budget.

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