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• Momentum has been the best performing factor
• Can factors get crowded, but can they be timed?
• Will we see a persistent rotation to value?

 
A Factor-based approach to investing
Factor-based investing means choosing securities for an inclusion in an index based on what characteristics or factors drive their risk-return behaviour, rather than a particular geography or sector.
Just like food can be categorised simply by ingredients, it can also be analysed more scientifically by nutrients.  Factors are like the nutrients in an investment portfolio.
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What are the main factors?
There is a realm of academic and empirical study behind the key investment factors, but they can be summarised as follows
The different factors can be summarised as follows:

• Size: smaller capitalisation companies
• Momentum: companies with upward price trend
• Quality: companies with strong and stable earnings
• Value: companies that are undervalued relative to their fundamentals
• Min Volatility: companies with lower volatility performance characteristics

 
Which has been the strongest performing factor?
Momentum has been the best performing factor over the last 5 years.  Value has been the worst performing factor.
 
Fig.1. World equity factor performance

Source: Elston research, Bloomberg data

A crowded trade?
Data points to Momentum being a “crowded trade”, because of the number of people oerweighting stocks with momentum characteristics.  This level of crowdedness can be an indicator of potential drawdowns to come.
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Fig.2. Momentum Factor is looking increasingly crowded

Source: MSCI Factor Crowding Model

The best time to buy into a Momentum strategy has been when it is uncrowded – like in 2001 and 2009, which is also true of markets more generally.  MSCI’s research suggests that with crowding scores greater than 1 were historically more likely to experience significant drawdowns in performance over subsequent months than factors with lower crowding scores.
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Fig.3. Factors with higher crowding score can be an indicator of greater potential drawdowns, relative to less crowded factors

Source: MSCI Factor Crowding Model

Rotation to Value
The value-based approach to investing has delivered lack lustre performance in recent times, hence strategists’ calls that there may be a potential “rotation” into Value-oriented strategies in coming months as the post-COVID world normalises.  But can factors be timed?

Marketing timing, factor timing?
Market timing is notoriously difficult.  Factor timing is no different.  To get round this, a lot of fund providers have offered multi-factor strategies, which allocate to factors either statically or dynamically.  Whilst convenient as a catch-all solution, unless factor exposures are dynamically and actively managed, the exposure to all factors in aggregate will be similar to overall market exposure.  This has led to a loss of confidence and conviction in statically weighted multi-factor funds.

Summary
Factors help break down and isolate the core drivers of risk and return.

• Factor investing looks at the “nutrients” of investment
• Static “catch-all” approach to multi-factor investing has clear constraints, so a more dynamic approach makes sense
• Factors can get crowded, but factor allocation is hard to time

 
For more on Factor investing, see
https://www.elstonsolutions.co.uk/insights/category/factor-investing  
​https://www.msci.com/factor-investing 

Factor-based investing – an alternative approach to cap-weighted indices
Factor-based investing focuses on identifying broad persistent characteristics for securities within a single asset class.  Factor-based indices ascribe weights to securities within an index based on those factor characteristics.
Factor-based indices are therefore typically single asset in nature, and represent an alternative approach to capitalisation weighted indices.
For example, Minimum Volatility equity index is typically constructed with a single asset class, e.g. equities whose constituents exhibit the lowest volatility characteristics.
Risk-based strategies – an alternative approach to multi-asset
When looking at multi-asset strategies, there are two approaches.
For asset-based investing, asset weights determine portfolio risk characteristics.
For risk-based investing, portfolio risk characteristics determine asset weights.
Risk-based indices are therefore typically multi-asset in nature, and represent an alternative approach to asset-based (e.g. 60/40) multi-asset indices.
For exanoke, a Minimum Variance index strategy targets the minimum variance multi-asset portfolio.
Risk-based multi-asset strategies therefore reflect a portfolio construction approach, rather than a factor screen.  It is the set of rules by which a multi-asset portfolio is optimised.
What are the advantages of a risk-based strategy?
The advantages of long-only risk-based index strategies are that they:
1.            Provide a systematic approach to risk management
2.            Can be constructed with liquid underlying ETFs
3.            Do not use leverage or shorting
 
Get the full report here
http://www.elstonetf.com/store/p3/Multi-Asset_Indices%3A_risk-based_strategies.html

• We look at the different factor versions of World Equity indices to see which factors won in 2017.
• World Equity Momentum factor delivered highest 1Y total return at +20.57%
• World Equity Momentum factor delivered highest 1Y risk-adjused return with Sharpe ratio of 1.94

Focus on market cap indices is a choice, not an obligation
A market cap weighted approach has well known drawbacks: it biases larger companies, regardless of efficiency and is "procyclical" - buying larger amounts of more expensively valued companies.

This is a critique of "passive investing". We don't believe there's such a thing as passive investing. There is index investing and non-index investing. There is subjective investing and systematic investing. Choice of index, choice of methodology, choice of asset allocation are all active decisions. Index investing simply delivers the desired investment approach in a way that is efficient, transparent and cheap.

Factor-based indices
The arrival of factor-based indices, means that for a required World Equity exposure, we can select which factors we want exposure to: for example, Size, Momentum, Quality, Value or Minimum Volatility.

The different factors can be summarised as follows:

• Size: smaller capitalisation companies
• Momentum: companies with upward price trend
• Quality: companies with strong and stable earnings
• Value: companies that are undervalued relative to their fundamentals
• Min Volatility: companies with lower volatility performance characteristics

How have these different factors fared?
Ranking the 1Y performance of these factors in 2017: Momentum factor delivered the highest total return at +20.6%, followed by Size factor at +13.1%, followed by Quality factor at +12.5%, followed by Value factor at +11.5%, and finally Min Volatility at +7.1%. This compares to +13.2% for the traditional cap-weighted approach.

Fig 1. Equity Factor 1Y Realised Risk-Return

• ETFs are a convenient building block for portfolio construction and there has been a rapid expansion in the number and type of ETFs available.
• Smart Beta indices so far have been confined to single-asset classes and give an alternative approach to weightings of securities within an index/ETF.
• Smart Beta strategies are emerging that are multi-asset or multi-factor and give an alternative approach to weightings of indices/ETFs within a portfolio.
• ETF portfolio strategies can be designed to target specific client outcomes and systematically constructed and adapted to offer a liquid alternative investment approach that is more consistent with real-life market conditions than traditional portfolio construction techniques.
• The growing range of ETFs and of ETF portfolio strategies available broadens the toolkit available to deliver client outcomes.

The portfolio puzzle
The Rubik’s cube has become a popular metaphor for the marketing teams of ETF providers.  With good reason.  For each client there’s a portfolio construction puzzle to be solved with building blocks, representing geographies, sectors, asset classes, factors and styles.

There has been rapid expansion from providers of ETFs tracking main-market indices, with the largest institutional providers capturing the lion’s share of flows, owing to their ability to deliver on four key ETF governance criteria – consistency, liquidity, transparency and, of course, price.
This means that ETFs for main market cap-weighted indices are increasingly commoditised.  After all, there doesn’t seem to be anything overly smart about replicating market beta, other than the smartness of saving on fees relative to 'closet-tracker' active funds.  Traditional cap-weighted index investing is a preference: either out of philosophy or necessity.

Innovation means smarter?
Hence R&D of institutional investors, index providers and ETF manufacturers alike has focused more on “smart beta”.  This has triggered a slew of innovation – both superficial and substantive.

At a superficial end, age-old alternative weighting strategies (eg value indices that screen stocks for low book values, or dividend-weighted indices) have been rebranded as being “smart”.  In these cases, for “smart” read “non-market-cap weighted”.  In fairness, this rebranding is part of broadening of alternative weighting strategies that are factor-based.

More substantively, research programmes such as EDHEC-Risk Institute’s Scientific Beta have been instrumental in promoting fresh thinking the field of both factor-based and risk-based smart beta strategies.

Factor-based approach
As a result, providers are focusing on making building blocks smarter.  Instead of relying on the ‘traditional’ factor of market capitalisation for index inclusion, smart beta indices (and related ETFs) look at alternative factors: book value, dividend yield, volatility, for example. In that respect, the FTSE Russell 1000 Value Index launched in 1987 is probably the oldest factor index on the block.  More recent factor indices are stylistic: Both iShares (Oct-14) and Vanguard (Dec-15) havelaunched  global equity factor ETFs focusing on Liquidity, Min Volatility, Momentum and Value.  The sophistication of factor-based index construction will continue to increase with the increase in data availability and computing power.

Risk-based approach
Portfolio strategists meanwhile can apply quantitative rules-based approaches to portfolio construction, creating static or dynamic asset allocation strategies from a growing universe of both cap-weighted and alternatively-weighted index tracking funds.  These strategies – such as Maximum Sharpe, Minimum Variance, Equal Risk Contribution and Maximum Deconcentration – offer an alternative to the standard but troubled single period mean variance optimisation (“MVO”) approach.

MVO’s limitations
Single period MVO approach remains the traditional bedrock of very long-run investing in normal market conditions where the sequence of returns does not matter.  However it runs into difficulty in the short-run when markets are non-normal and sequence of returns matters a lot.  So unless you are a large endowment with an infinite time horizons, or perhaps can afford to invest for yourself and your family without ever needing to withdraw any capital, relying entirely on the MVO approach for asset allocation gives false comfort.

For cases where there are constraints that challenge the MVO model - due to multiple or limited time horizons, expected capital withdrawals, risk budgets, and unstable risk/return/correlation profiles of asset classes (collectively known as real life) - portfolio construction requires a smarter, more adaptive approach that observes, isolates and captures the reward from shifting risk premia over time.

Risk-based portfolio strategies attempt to achieve this and are designed to offer a liquid alternative approach to investing that is uncorrelated with traditional Single-Period MVO strategies.

What’s the problem to solve?
Whether assessing factor-based ETFs, or risk-based ETF strategies, at best these new developments seem all very smart. At worst it’s just a bit different.

However, as ETFs get smarter and the strategies that combine them become more sophisticated, there’s a risk that the key question in all of this gets lost in an incomprehensible barrage of Greek.

The key question for portfolio managers nonetheless remains the same. What client outcome am I targeting? What client need am I trying to solve?

For portfolio strategy, whether using a discretionary manager that relies on judgement, or a systematic rules-based approach that relies on quantitative inputs, the key client considerations remain return objective, time horizon, capacity for loss, and diversification across asset classes and/or risk premia.

Broadening the toolkit
A portfolio strategy has little meaning without an objective that focuses on client outcomes.  Factor-based ETFs and Risk-based ETF portfolio strategies offer an alternative or additional set of tools to help deliver on those outcomes, in a way that is systematic, liquid and efficient.