In our first post about our Model Portfolios*, on Global Bonds, we explained that we run Model Portfolios for two reasons: Firstly, to help us understand the dynamics operating within markets and second to demonstrate the power of Dynamic Allocation between components of any portfolio in order to generate a superior risk/return trade off.

(*NB, the terminology used here of Model Portfolios is not to be confused with that used by wealth managers and Independent Financial advisors, i.e. that these are provided as solutions for investors. Market Thinking is not a licensed investment manager and does not make investment recommendations. These are, literally, representations of internal portfolios based upon our models)

This then, is the second in our series of posts about our various model portfolios, and looks at Global Equities from the perspective of Factors. Factor investing has become increasingly popular among institutional investors in recent years and there is a wealth of academic literature on the subject, including this on the update to the original Fama and French 5 Factor model as well as this from one of the big Investment Advisers to institutions who support the approach. Also this.

The systematic approach and the rewards from diversification that Factor investing offers means that it has been eagerly embraced by the Quants and also the index providers such as MSCI, who offer a good primer on the subject here as well as a lot of discussion and debate (Factors or Fiction?) Meanwhile, ETF giant Blackrock, who run a number of ETFs on Global Factors have further literature here.

What appeals to us at Market Thinking is that the 5 Factor Model fits with our approach of the Three Tribes of Investing that we set out in the Global Bond Model Portfolio post. To recap,

Market Thinking is based on the idea that, at any given time, market prices reflect the differing risk/return expectations of three different ‘Tribes’ – short term traders, medium term asset allocators and long term investors – and that inefficiencies and opportunities arise as the balance of (buying and selling) power shifts between them. Sometimes they are all moving in the same direction, creating powerful directional markets, while at other times they are pulling in different directions. Understanding the behaviours of the different groups – traders are usually leveraged and focussed on absolute return, while asset allocators are usually unleveraged and focus on relative return, for example – is key to analysing potential market behaviours.

PRINCIPLES OF MARKET THINKING

5 Factors meets 3 Tribes

If we take as our basis the Five Global Factors available as Global Indices from MSCI and essentially tracked by ETFs from Blackrock, we get the following factors.

• Momentum
• Minimum Volatility
• Quality
• Size
• Value

Thus in our world, we see Momentum as the dominant driver of activity by the leveraged traders, Minimum Volatility as the dominant driver of risk management for the medium term asset allocators, leaving the ‘fundamentals’ of Quality, Size and Value as the primary focus of long term buy and hold investors. Of course, the whole point of Market Thinking is that each of the tribes can (and does) influence the other factors at various times, which means that at any one time ‘the market’ can appear irrational – although this is where the opportunities are then often to be found.

The Process – Dynamic Factor Allocation using Market Thinking

Passive investing is cheap in a bull market, but nobody wants to track a benchmark down and, as we know from experience, portfolio insurance also tends to become very expensive the minute you need it. At Market Thinking, out underlying belief is that by Dynamically allocating where we are most confident – including cash if we need it – we can achieve better risk adjusted returns by being Active with Passive.

The (Market Thinking based) Global Equity Factor Portfolio shown here thus aims to outperform the benchmark MSCI All Country World Index of Equities (ACWI) on a risk adjusted basis by dynamically allocating and selecting a blend of the Five Factors, Momentum, Minimum Volatility, Quality, Size and Value as well as ultra short term bonds (cash), utilising large and liquid ETFs. We do this by combining our insights based on behavioural finance generated over more than 30 years of investment strategy advice with a series of indicators about the risk/return stance of the different investor groups to establish a series of proprietary confidence or conviction scores for each index.

The idea is to weight the overall portfolio according to the conviction, the higher the conviction or confidence, the greater the allocation, with the important caveat that, with the lowest level of conviction there is no weighting at all (the use of cash). If there is little conviction across the whole asset class then the allocation is to cash (in effect ultra short dated bonds). This is relatively rare, but it is certainly where we found ourselves early this year.

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Chart 1. Applying Dynamic Factor Allocation to a Global Equity Portfolio

The chart shows the performance of our Global Equity Factor Portfolio since 2017 (based on out of sample back test and run ‘live’ since 2019). We show this against two benchmarks, one of which is the standard MSCI ACWI and the other a straight equal weight of the Five different Factors. Note the red line is horizontal on a number of occasions when there is a higher allocation to ‘cash’.

At first take this does not ‘look good’ versus the benchmark, but it depends on whether you are looking for absolute or relative returns and in particular what level of ‘risk’ you are willing to take.

Table 1: Cumulative Returns %

As table 2 shows, volatility, downside risk and max drawdown are all significantly lower, in most cases less than half the risk of the benchmark. Note these are annualised returns.

Table 2: Annualised Return % – ‘Risk’ considerably lower

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Chart 2: Momentum has been the dominant factor over time

This begs the obvious question, “Why not have more momentum?”, but that is to overlook the point that the aim of this particular model portfolio is to capture most of the upside, but without the same level of risk as the benchmark. Notice also in table 3, showing monthly performances, that the bounce back in July – that added 6.5% to the benchmark – reduced its under-performance against the model this year from 8.2% to 3.1%.

Table 3: Monthly and Annual Returns – Alpha (excess return) of Global Equity Factor Portfolio over benchmark

This table thus appears to show that the Global Equity Factor Portfolio only ‘delivered’ in terms of Alpha in the big down years of 2018 and 2022. This of course is the ‘curse’ of Alpha for the active manager, the commentariat, not least the ‘Management’ of Fund Management companies want constant ‘green’ boxes, while most actual clients are keen on absolute return and crucially also want to understand what risk has been taken to get that return. If we look instead at tables 4 and 5 below, we can see a different set of ‘Green’ in terms of positive months and negative months, we see 21 down months and 46 up months, almost identical to the benchmark, but with the consistent theme that, until this year and with the exception of 2018, most of the ‘negative’ alpha was simply not going up as much, while offering far more stability. Meanwhile, almost without exception it has been a question of not going down as much, which is the key message for both this year and 2018.

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Table 4 : Global Equity Factor Portfolio: Monthly Return

Table 5: iShares MSCI ACWI ETF:  Monthly Return

Note that we are comparing with the I-shares ETF of the All Country World Index (ACWI) for a more realistic alternative return to an actual investor.

Confidence Scores and Cash

As with the other model portfolios, the key to our downside protection is the use of cash

As we noted in our post on Global Bonds, the ability to allocate to Cash (in reality ultra short dated bonds) is key to what Charles Ellis in the 1980s referred to as (Winning the Loser’s Game) Just like amateur rather than professional tennis, you survive (and thrive) by letting your opponent make mistakes – ie losing less in the downturn, leaving you with more capital to compound in the upturn.

Note that the returns are calculated by looking at the performance not of the indices themselves, but of the passive ETFs that track those indices, giving a better representation of returns available to actual investors. Also note that trades are calculated at mid closing price on day T+1, in other words, we are not trying to claim trading skill, this is about dynamic allocation capturing the bigger moves.

The Process

The essence is the Dynamic Allocation process driven by the conviction scores. These are calculated daily, but unless something dramatic occurs, we only rebalance weekly. This is about capturing medium/long term trends, not short term trading.

The ability to protect the downside through allocations to cash is an obvious, but key component of protecting returns

Chart 3 illustrates that, for long periods of time, the portfolio will have been fully invested (fully shaded in blue). However, for a few periods, and certainly since the start of the year, the weighting has been very heavily skewed towards cash (ultra short duration bonds) and away from the equity ETFs as shown by the white areas.

Chart 3: Cash helps protect the downside

Table 6 meanwhile illustrates the Conviction scores for the 5 Factors over the last two years as a trailing average. (Note we calculate the scores every day, but only rebalance weekly, if required). The higher the score, the greater the conviction and the higher the relative weighting in the portfolio.

Table 2 meanwhile gives some insight into the process, illustrating the trailing monthly average Conviction Score for a series of Bond ETFs since 2020. The scores are calculated daily and used to drive weekly rebalancing of the Model Portfolios – the higher the score, the greater the allocation. Clearly as conviction falls across the board the ‘cash’ element rises.

Table 6: Dynamic Bond Allocation over time – Conviction Scores

To Conclude – better Risk Return

By back-testing from long established advisory principles that are embedded in what we call Market Thinking, we believe that we can show that a system of dynamic allocation within a basket of Global Equity Factor ETFs can achieve diversification and outperform the benchmark MSCI ACWI, on a risk adjusted basis, with considerably lower volatility and much lower monthly drawdowns. Moreover, as with all our Model Portfolios, the simple expedient of being able to take meaningful benchmark risk at times of high uncertainty through holding ‘cash’ considerably enhances not only the efficiency but also the effectiveness of the strategy.

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