It is one thing to talk a good game, it is another thing to review the actual game played. This sentiment is clearly illustrated if we look back at the historical performance of the Old Mutual Global Managed Alpha Equity Fund (FSCA approved), which was launched in December 2017. We will start the analysis at inception date and unpack the five-and-a-half-year track record by illustrating how our investment team’s systematic model was able to tilt the fund toward the factors that it forecast would drive the market. Furthermore, to demonstrate the fund’s dynamic approach to factor investing, we will consider the positioning over the last 24 months, ended June 2023.
Recapping our investment process
Our proprietary systematic model evaluates six broad market drivers or factor buckets – value, growth, quality, momentum, size and volatility (risk). This process is style agnostic, meaning that the approach will tilt toward or away from these factors depending on the forecasted return drivers. By ‘tilt’, we mean an over- or underweight exposure to the factors relative to the MSCI All Country World Index (ACWI).
The ‘end product’ of these factor exposures will be an over- or underweight to the underlying shares, which ultimately results in over- or underweight exposure to countries and industry sectors. This is done within the tight risk parameters we have integrated into the portfolio construction process. Risk management is a deliberate part of the approach as our objective is to provide an outcome that produces incremental excess returns without taking on undue risk relative to the benchmark. We seek to achieve this by having a broadly diversified fund with relatively tight tracking error limits.
Today’s market drivers might not be tomorrow’s
Chart 1 alongside shows that the return of the value factor was negative during the first half of the fund’s track record, but subsequently moved into positive territory. As a result, the fund’s overall exposure to value moved from an underweight to an overweight (brown line). This tilt was achieved by moving from shares that exhibit a low exposure to value into shares with a higher exposure to this factor.
It is important to note that we have designed the process to avoid unnecessary trading costs by smoothing the signals. This means that we are not jumping in and out of shares, but rather incrementally changing our positions. In this way, we accept that we will most likely not time the top or bottom of a factor’s cycle, but in our view, slow and steady wins the race.
The heatmap table below illustrates how the factors driving the market change through time. This highlights the need for a dynamic approach to factor investing. It is also worth emphasising that the estimation of factor returns across all factors and all companies in our universe is done simultaneously.
Based on the above table, the market was driven by the volatility, momentum and growth factors post the tumultuous Covid-19 period. The model, therefore, constructed a portfolio blend which produced exposure to these factors.
Over this period, the cumulative return above the benchmark, was 14.03% and ultimately produced the following attribution:
From the tables above, we can observe that sectors comprising of companies with high exposure to the volatility and growth factors had a net-positive impact on the fund’s overall excess return – specifically when it came to global technology-oriented stocks.
Previous 24-months positioning and subsequent attribution (June 2021 – 30 June 2023)
If we once again consider the heatmap table, we see a number of gradual changes in the market drivers as we move into the second half of the fund’s performance history. The colour patterns highlight a move away from the volatility and growth factors toward the value and quality drivers. To demonstrate how the model was able to pivot toward these exposures, we selected the 24-month attribution period, ended 30 June 2023.
This was a weaker period in the market, but the fund was still able to produce a cumulative return above the benchmark of 3.41%.
From the tables above, we can see that previously ‘unloved’ sectors, comprising of companies with higher exposure to the value factor and negative exposure to the volatility factor, had a net-positive impact on the fund’s overall excess return – specifically regarding global energy, real estate and utilities-oriented stocks. In summary, the fund pivoted to more defensive factor exposures.
CONCLUSION
The historical performance of our Old Mutual Global Managed Alpha Equity Fund has, essentially, been a tale of two halves. Importantly, our systematic approach was able to successfully tilt away from a net-positive exposure to the growth, momentum and volatility factor buckets, toward a more pronounced exposure to the value and quality buckets. As shown in the attribution, the process doesn’t seek to perfectly time the top or the bottom of a factor-cycle (there will always be some red), but rather aims to incrementally skew exposure toward the drivers predicted to produce relative future outperformance. All of this is done within a portfolio construction approach that seeks to consistently produce the optimal blend of risk, liquidity and expected excess return.