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The anatomy of long-term asset allocation


Parit Jakhria, Head of Long-Term Investment Strategy (LTIS), explains how his team operates to determine our long-term investment strategy to ultimately deliver outcomes for your clients.

LTIS Overview

The Long-term Investment Strategy Team determines the optimal strategic asset allocation (SAA) and the strategic hedging policies for Prudential's multi-asset portfolio. As part of this, LTIS develops its proprietary capital markets assumptions and stochastic asset modelling capabilities to model the risks, returns and correlations between different asset classes, asset sub-classes and macro-economic factors across different geographies over the medium to long-term. Additionally, these assumptions and modelling capabilities are used internally within the Prudential Group by Finance, Risk, Distribution and Product Development.

Of course, it’s important to remember that the value of a client’s investment can go down as well as up and isn’t guaranteed. They could get back less than they paid in. Bearing this in mind, let’s look at our approach to SAA.

SAA

The SAA is a key input into the overall fund outcomes. It's focused on customer outcomes, and a four follow-on sub-principles, which are:

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  • Customer outcomes: focus on customer outcomes, and ensure that that there's a design framework that maps the expected customer outcomes to the fund objectives in an efficient manner.
  • Tailored risk appetite: all client portfolios have specific outcomes. This means that all portfolios have a bespoke SAA that is designed for their needs. Specific constraints such as capital or Solvency II are also taken into account where appropriate.
  • Efficient risks and returns: a given risk appetite enables PPMG to choose an asset allocation based on the analysis of the risk return trade-off of portfolios relative to the "efficient frontier" derived from the medium-to-longer-term views of returns, volatility and correlations.
  • Consistency across fund ranges: Within the stated objectives and risk appetite, the aim is to ensure a consistent SAA across funds with similar risk appetite/other similar funds.
  • Other constraints: our investment strategy is also optimised along other constraints as required by clients for example, cost and liquidity.

The process for determining the long-term investment strategy can be summarised into four stages:oracle quarterly q3 2017- art2 img2

1. Capital market expertise: Takes into account:

  • medium and long-term capital market assumptions.
  • market insight from PPMG Research and other internal/external research.
  • manager insight and opportunities from across Prudential Group.

2. Portfolio modelling

  • the capital market input feeds through into a full term structure of returns across different capital markets and scenarios.
  • Proprietary stochastic in-house financial model.
  • Quality position papers on new asset classes.

3. Client risk appetite

  • The risk/return analysis takes into account the client risk appetite to come up with an optimal client outcome.
  • Portfolio optimisation along the risk-return space, in order to maximise returns for a given risk appetite.

4. SAA

  • Leads to a return optimised portfolio, diversified across asset classes and geographies.

Capital market assumptions and modelling

Our strategic, global, multi-asset investment process is necessarily broad in seeking to construct capital markets views and assumptions for all asset classes and geographies over a medium to long-term investment horizon. Hence our capital markets assumptions and modelling captures the key components/factors of the asset universe (and their interactions) across multiple future scenarios.

Our starting point is to take all available inputs from research and analysis, both internal and external, making sure that our sources are as varied and heterogeneous as possible.

The external research is sourced from:

  • academic literature as well as market practitioners, university faculties, central banks, supranational organisations, industry bodies, sell-side analysts, buy-side analysts and independent research consultancies.

The internal research leverages on resources within the Prudential Group, including:

  • PPMG Manager Oversight, PPMG Research, PPM America, M&G, EastSpring and PruCap.

The analysis and the hypotheses are independently tested using historical capital markets returns obtained from numerous data sources, proprietary third party databases, time series and cross-sectional analysis of returns distributions.

The analysis is further enhanced and deepened by bespoke in-house modelling of structural factors like:

  • demographics trends
  • economic growth models
  • globalization and technological change
  • Monte Carlo scenarios and simulations of volatility, correlations and dependency structures of risk premiums.oracle quarterly q3 2017- art2 img3

Having sourced the greatest breadth of input, we seek to achieve a balance between financial theory and empirical validation in coming up with the structures. We filter the ideas which are both theoretically sound and empirically tested, using fundamental insights to design investment strategies which aim to work on a forward-looking basis rather than just historically.

Capital markets modelling - GeneSIS

Our capital markets assumptions process involves detailed stochastic modelling of different asset classes and macro-economic variables. This led to the birth of Prudential's proprietary in-house economic scenario generator, GeneSIS, about 15 years ago, which is now widely used across Prudential UK. It’s also used by other parts of Prudential Group for a variety of functions.

We acknowledge that past asset class history is deterministic but the future is stochastic; there is a single past but importantly there can be many futures. GeneSIS is invaluable in mapping out the full range of future possibilities for all asset classes and geographies, along with the impact of each future possibility on the risks and returns characteristics of various asset allocations. This allows us to ensure that our portfolios are optimised for the base case but also remain robust across the full range of scenarios.

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Output

The output from all these investment processes is a portfolio which is diversified across geographies and asset classes (see illustration below). The diversification provides valuable risk mitigation benefits to our funds against specific risks affecting individual economies and assets.

A key theme has been the diversification out of UK assets, over the past five years, resulting in portfolios that are much less dependent on, and sensitive to, the UK economy. This has been carried out across all the asset classes, and is visible in the graphic below. This has also helped ensure that the impact of the Brexit referendum and subsequent political risks was well managed.

Another theme visible in our SAA is to increase allocation to some of the niche asset classes in recent years, including African Equity, Asian and European Property, Asian Fixed Income, Bridge Loans and Private High Yield as well as other alternatives. We continue to search for assets which have favourable risk-adjusted returns characteristics and diversification benefits, using the capabilities across the wider Prudential Group to source such assets in a cost-effective manner.

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A diverse, talented team

Delivering these various investment functions requires the collaboration of different skill sets, which is reflected in the diverse composition of the LTIS team. LTIS consists of 11 team members from a number of different nationalities with deep knowledge of capital markets and economics, strong market, quantitative and actuarial skills as well as significant knowledge of how the Prudential business and wider insurance and investment landscape operates.

While the talent pool is diverse, the skills and expertise driving each one of these different work streams is the same; whether it is the SAA, the capital markets assumptions and modelling, or the hedging and ALM policy. All of them involve a fundamental understanding of the behaviour of different investment asset classes, the mathematical knowledge required to model them using complex quantitative systems, and the ability to integrate them into portfolio solutions which deliver the long-term investment outcomes which we seek to deliver to Prudential clients.

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