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    Take back control: shift your static allocation strategy to an active mix

    Take back control: shift your static allocation strategy to an active mix

    31 March 2023 Solutions

    2022 highlighted the vulnerabilities of a simple static asset allocation

    Traditionally, bond and equity markets exhibit a negative correlation – a decline in one market tends to coincide with a positive performance from the other. Previously, mixing an allocation to both bond and equities has been an easy call, as the diversification benefits were significant which led to the creation of the concept of the 60:40 portfolio.

    In 2022, this relationship broke down, with markets experiencing one of the broadest asset dislocations seen in decades. Both bond and equity markets experienced notable declines over the year (see figure 1), and a portfolio with a traditional 60:40 asset allocation would have experienced one of the worst years in recent history (see figure 2). This period highlighted the vulnerabilities of static asset allocations to macro shocks.

    Figure 1: 2022 was a historically poor year for bond and equity returns

    historically poor year for bond and equity returns

    Source: Insight and Bloomberg, as at 31 December 2022. Shows S&P 500 Index vs US Treasury returns between 1872 and 2022.

    Figure 2: A traditional asset allocation would have experienced the worst performance in over 40 years

    traditional asset allocation

    Source: Insight and Bloomberg, as at 31 October 2022. YTD return paths using 60% allocation to S&P 500 Index and 40% allocation to US 30 year Treasuries.


    Taking back control with a bespoke solution

    We believe a more active approach to asset allocation should help to benefit returns over the medium term, while also providing a smoother journey than relying on a strategic asset allocation alone.

    In our view, this is best approached using two steps:

    1. Pick a set of investment tools that provide sufficient diversification. This includes:
      a. Beta management to capture underlying movements in bond and equity markets,
      b. An independent and diversifying alpha component, specifically geared towards currencies

    2. Use of unique macro regime framework to determine likely asset classes behaviours and adjust our exposures accordingly

    Complemented by a diversifying alpha component focused on currencies

    Our currency engine is designed to capture opportunities whatever the market conditions. We have mapped out the key drivers of medium-term currency movement – the investment horizon we operate in - and ensured all are covered in our currency engine.

    Utilising factors that can have very different correlations with risk assets, we can seek to add diversification and alpha

    Each of the factors we use has historically varied significantly in terms of information ratios and correlations with the S&P 500 Index. Factors based on inefficiencies related to currency market participant behaviour (such as Value) have low correlations while Carry, as a pro-cyclical factor, has a much higher correlation. Quality is a more defensive factor and has an inverse correlation. By taking advantage of these variations in expected returns during different market conditions, investors can potentially add significant diversification benefits with the additional of an active currency strategy to their portfolios.

    Figure 3: Information ratio and correlation to the S&P 500 Index of different currency factors

    Information ratio and correlation to the S&P 500 Index

    Source: Bloomberg and Insight. The information ratio for each signal is simulated assuming transaction costs and implemented on the portfolio assuming a specified risk target without taking into account any fees. The 60%:40% equity/bond mix is based on a 60% weight in the MSCI World Index and a 40% weight in the Bloomberg Global Aggregate Index, reweighted monthly between January 1993 to August 2022. Model results have certain inherent limitations. Unlike an actual performance record, model results do not represent actual trading/returns and may not reflect the impact that material economic/market factors might have. Clients' actual results may be materially different than the model results presented
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