• Stuart Fowler

Is your manager doing a good job?

How are you supposed to know?

The challenge for private clients our title alludes to has two dimensions: giving them the right job and ensuring they do the right job well. The typical portfolio approaches for private clients focus on short-term constraints that are not consistent with maximum satisfaction with horizon-specific outcomes.

Using as an example No Monkey Business portfolio returns over the last two years of large falls and rises in markets, we illustrate how to set objectives and assess performance better. Because all our portfolios are different, for reasons that will be obvious from reading this Insight, we reference the same two portfolios as we did in an earlier Insight, Anatomy of a bear, one in ‘accumulation’ and one in ‘drawdown’.

Performance and confidence

Performance appears to be an important reason, perhaps the most important, for individual investors deciding to change their investment arrangements. This is not because they have a lot of information about their managers’ performance and are able to assess it rationally. In fact, they probably only get to see their own returns, compared with benchmarks, every three or possibly six months. Even then, without a lot more data history than their patience may tolerate, and without attribution (was it policy choices, market timing or selection choices?), there is limited information to be extracted from the reports.

If it is not continuous well-informed appraisal that leads clients to change manager, what aspects of performance do? It is usually because they are surprised by what has happened and in the absence of proper explanation they lose confidence that their adviser has understood the constraints or the objective or both. The surprise is all about expectations but the interpretation is all about confidence.

In other cases, however, investors will realise that the adviser or manager they appointed did a good job given the mandate but the mandate was wrong. It can be hard to leave a manager who has done a good job against the wrong mandate. In selecting us many clients have moved their money from managers with very good performance as well as from those with disappointing performance.

Wrong job, right job

We identify five common causes of disappointed expectations and mismatched mandates that are prevalent today:

  1. The spread of a ‘factory’ approach to portfolio organisation that lacks close links to relevant personal objectives

  2. The fact that equity returns over the past decade have not typically delivered the ‘risk premium’ professionals led clients to expect

  3. The failure of diversification across the traditional asset classes to smooth portfolio volatility as portfolio theory apparently posited

  4. The failure of ‘alternative’ asset classes to perform as expected, in terms of absolute returns, correlations and premiums for illiquidity

  5. The ‘false prospectus’ that the fad of ‘absolute return investing’ turned out to be for many of its followers.

What all five have in common is that they are policy choices: high-level decisions about the general approach to how your money is to be managed. They belong to the client, who makes that policy choice. This is not to say the industry is blameless in adopting the easy sale in preference to a more exacting route to developing optimal investment solutions. The easy sale not so long ago was, after, all unitised with-profits.

We suggest that ‘outcomes driven’ investing, which Chris Drew and I developed ten years ago in parallel with the emergence of Liability Driven Investment in the institutional market, has avoided these problems and allowed for much clearer expectations and therefore more stability and consistency in following a planned and appropriate strategy.

The expectations effect works by being more explicit about what can happen, with more quantification of risks. But is also works via a feedback from greater confidence about outcomes to greater tolerance of short-term volatility. Consistency on the part of our clients means we are free to follow a model-driven discipline which is likely to increase wealth outcomes. Inconsistency means investors tend to raise their risk tolerance when times are good and lower it when markets and the economy are doing badly. This destroys wealth.

To illustrate how our clients can assess the job we are doing we reference our two actual portfolio examples. We do this in terms of three key questions we think all clients should want answers to:

  • How is my portfolio structured to deliver what I want?

  • How is risk being controlled?

  • Are both evidenced by the activity in the period?

How is my portfolio structured to deliver what I want?

‘Delivering what I want’ translates, in investment theory, to ‘maximising the benefits I want to get from my money in the form I specify’. In this context, ‘benefits’ translate into ‘utility’ or (as sometimes expressed in the theory) as ‘welfare’. Utility is specific to a goal not general to an ‘investment personality’, assuming such a thing even exists.

In practice, utility is mainly about the consequences of uncertainty and how individuals express preferences in response to those consequences. In the factory model, the presumption has to be that these are common to everyone, not idiosyncratic. In reality, we make value judgements that are highly specific, such as:

  • preferring to push possible bad outcomes further into the future, where we think we can better bear the consequences, or nearer where we can deal with them through adjustments to behaviour (such as a household budget change)

  • setting explicit constraints on the consequences, such as a minimum spending level in retirement which no incremental potential spending chance should put at risk

  • preferences that are dependent on progress in funding an objective that calls for a particular pot of money, which (whether the progress is good or bad) could invite taking either more risk or less risk.

You will know personal utility was never addressed if you did not start with planning conversations that identified these preferences and described a portfolio solution that matched them.

You will also know it if the conversations about ‘risk tolerance’ did not address whether your utility was best expressed in terms of path risk, or the short-term volatility in the path of the portfolio in money terms (as measured by those performance reports) or outcome risk, as in the form in which you ultimately derive the benefits from your wealth, such a future level of real spending (after inflation) say 20 years out. The first is not a substitute for the second.

We find that in practice most investors, when encouraged to plan in terms of specific goals for their money, can see clearly when (and why) path risk or real outcome risk dominates. The investment solution will be radically different depending on which dominates.

For the client who owns our drawdown example, the goal is meeting a schedule of annual draw in real terms from capital (part in pension, part not) subject to the constraints of i) not running out of capital before age 95 and ii) sustaining the spending plan without being forced to cut it, except to the extent of a planned schedule of tapering minimum spending at different stages of retirement. In this plan, risk taking is constrained by the agreed range of tolerable outcomes, as ‘real’ money available in a cash account to meet the next three years spending, in a schedule of three-year time slices from 50 to 95. With known resources, risk is solved for by reference to the range of probable outcomes (which come from our model) and the consequences (which must come from the client).

The key element of our quarterly performance reporting is therefore where the client now stands in relation to the goal outcomes: is the ‘new’ portfolio value sufficient, with ‘new’ expected returns, to meet the agreed drawdown targets with the same confidence?

Because there is a degree of volatility in the ‘funding status’ (though as the return-generating element of the model is designed, this is much less than the volatility of ‘the market’), we report (as a monetary amount and as a percentage of the ‘fully-funded’ position) the ‘interim projected shortfall or surplus’. What the client wants to know is:

  • Has the portfolio done so badly that I may now breach the plan constraints and therefore need (in this example) to cut spending, contrary to the objective of sustaining it a planned real rate?

  • Have I done so well that I can change the targets or risk level or assign surplus assets to a different goal?

  • Is the change just ‘noise’ I should not attach any significance to?

We provide this guidance in every report, every quarter, drawing on stochastic simulations of a long-term plan and its changing interim funding status. Usually we will be suggesting that no action is called for by the client, particularly in the first 6-10 years of a plan.

A secondary aspect of the portfolio progress report is that, because the target outcomes were planned in real terms, we need to adjust them each quarter by the actual inflation in the quarter before calculating the new funding position. We report that change too.

How is risk being controlled?

In the typical investment solutions that dominate the IFA, banking and wealth management business models, risk is managed by diversification. This is not a control. It was never put forward by theorists as a risk control. Its origin was in the separation of:

  • diversifiable risks that provide no reward and therefore should be eliminated from a portfolio and

  • systematic risks, common to any exposure to particular asset classes or markets however you select within them.

Relying on diversification between asset classes and markets reduces risk to the extent the returns from each are less than perfectly correlated and so for a given level of resulting risk there is a set of possible portfolios that will yield the highest expected return. These portfolios are ‘more efficient’ in using risk than portfolios that have lower returns per unit of risk. That is all it means.

To serve as a risk control, there would need to be sufficient of these asset classes and markets with both i) low or negative correlations (or co-movement) and ii) stable and predictable correlations to reduce portfolio risk reliably to acceptable proportions. As investors worshiping at the new altars of ‘absolute returns’ and ‘multi-asset classes’ discovered, correlations do not have these highly desired characteristics. And they converge when you most depend on them, such as when liquidity tightens up and asset prices are falling. Hence the disappointment.

In a liability-driven approach, risk is controlled by combining risky exposures and hedges. Hedges are assets that perfectly match a liability, or goal outcome. If the outcome is a target level of money in real terms 10 years out, for instance, that exact amount can be produced, on time, with certainty, by buying an index linked gilt with the same duration.

When investors have preferences for outcomes that involve trading off possible higher wealth against some minimum wealth, there has to be a range of probable outcomes, with risk taking, that is acceptable and efficient. The size of that range is controlled not by diversification, although that is part of an efficient solution, but by the mix of risky assets and hedges, or risk free assets.

What is the evidence?

So when we report our transaction activity for a client in the quarter, it should be seen to be consistent, at a high level, with the process of risk control as market values alter. It becomes the visible proof of a risk management discipline. It will be particularly seen as a discipline if the actual activity appears (at the time) counter-intuitive.

In Fig 1 we show the market returns from the start of 2008, just after the bear market began, up to the end of 2009. This describes the environment for each of cash returns, index linked gilts (the FTSE over 5-year index whose duration most closely corresponds to the time slice outcomes we hedge) and the four equity markets and regions (in sterling terms) we use as building blocks for the risky asset portfolio.

fig 1 index total returns in £ for portfolio building blocks

Two aspects are important to our model:

  • The expected return on equities rises as markets fall in price, because we accept the evidence that equities generate a trend of positive real return over long horizons (capitalism requires it) and ‘revert to the mean’

  • The attraction of any expected equity return depends on the competition it faces from hedging assets, at their own ‘certain’ real return.

In Fig 2. we show how we moved money between the hedge portfolio and the risky portfolio over the course of the market cycle, responding to both effects. The bars show the net addition to (positive) or sale (negative) of equities in each quarter of the two-year period.

fig 2 net flow from risk free to risky assets as % risky

At the start of the bear market, equities fell but so did the risk free rate, so we added to the equity position. As this was followed by a reversal of the fall in risk free rates and slightly higher equity prices, we took some bets off the table and added to index linked gilts. As the bear market turned nasty, and the crisis in the banking sector spilled over into expectations of a global recession or new depression, additions to equities were mainly driven by falling price, rising expected returns, rather than by changes in risk free rates. More recently we have started taking bets off the table as both equities and index linked gilt prices have been very strong. Though mean expected equity real returns are still above average, the incentive to take risk is greater because index linked gilt yields are at record lows. However, the incentive has been lessening simply because of the scale of the recovery.

We suggest that few managers have shown such consistency in their risk taking approach during this market cycle. Looking at their activity will probably tell a clearer story than the performance they reported or the comparisons they showed. Over the long term, there is clear evidence that adopting a consistent attitude to risk, which is not at all the same as the same level of risk, produces higher returns because it avoids selling low and buying high.

Backward looking performance

Even on a pure accounting basis, we need to report what actually happened to our clients’ portfolios in each quarter and we do that too, in a fairly conventional way.

  • We calculate the money weighted returns in each month (so adjusting for cash flows into or out of the portfolio during the month according to roughly when they arose) and multiplying them through to produce what is then very close to a time-weighted or internal rate of return for that quarter

  • We show the returns for the assets we use a building blocks in the same period, so that the actual return can be viewed broadly in the context of the environment in which we were operating

  • And from now on we plan to show something we have resisted hitherto: a measure of what clients might have earned with a more conventional approach, for which purpose there is nothing ‘better’ than the benchmarks developed to match the different version of the factory model by the Association of Private Client Investment Managers and Stockbrokers.

In a liability driven approach, the changing market values of the hedging assets are meaningless in terms of outcomes, as the two are perfectly matched: a rise in price will reduce the expected real return symmetrically leaving outcomes unchanged. So realistically it is only the risky portfolio whose volatility is meaningful, but in our view its meaning is in the impact on funding adequacy, and so requires a forward-looking measure. As a backward-facing measure of industry returns, the closest APCIMs benchmark for the risky portfolio is the Growth index although it is not still not representative of equity returns alone, as it includes cash, bonds, property and hedge funds (to the extent in full of 22.5%).

In Fig 3 we show the returns of two portfolios, one in drawdown (and so combining hedges and risky assets, the latter averaging about 55% over the period) and one in accumulation (with long enough horizons to have been fully invested in risky assets throughout the two-year period).

fig 3 quarterly portfolio and benchmark returns (indexed)

We can note, in terms of attribution, that we were helped by the extent of our diversification geograhically, as we tend to more equal weightings than conventional managers and have less of a bias to the UK as home market. This helped particularly in the bear market because of currency gains, although this was partially offset in the following year. The returns to these structural characteristics, or policy features, in any particular period contain relatively little information except that diversification does not necessarily require lots of different assets. As the APCIMs benchmark shows, conventional diversification, even with the addition of 7.5% in hedge funds, did not produce either better performance or less volatility than our risky portfolio.

Though you can make comparisons with your own performance, we suggest the guidance in this Insight as to how to interpret what your manager is doing is probably much more important than a crude comparison of the numbers in a short period. As my book suggested, investment is best viewed as a journey not a race. You are not picking the winner so much as the best planner, navigator and driver, all rolled into one.

#BENCHMARKS #diversifaction #managerselection #performance #risk


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