Our Defined Outcome portfolios are managed to individually-customised applications of a quantitative model, designed at the asset allocation level to deliver goal-specific outcomes within explicit tolerance ranges at defined future dates. The allocation decisions follow from monthly computer runs of a unique model for every goal-based portfolio for every client. For the first time since the collapse of Lehman Brothers, we reran models midmonth, using Tuesday’s Tokyo close and Monday’s close for all other markets.

Several recent posts have focused on the attraction of Japanese equities. In this one, we focus on changes in exposure, rather than the allocations themselves, in the belief any investor, whatever their views, should change their exposures in response to such large price changes. As an explanation, we show below in full what we sent to clients on Monday, in advance of the changes. Though specific to our process, we think it is of interest to investors with different approaches.

Why we should follow the model

Our model is by design ‘contrarian’ but it is also blind to emotional influences on how it allocates capital (other than those emotions captured in the risk preferences for each portfolio goal). It is hard headed and also hard hearted.

The assumptions the model has been given about extreme short-term volatility in absolute and relative returns, from whatever source, allow for the kind of shock experienced in Japanese stocks. These assumptions are what keeps us out of equities for short-term liabilities.

The assumptions the model has been given about uncertainty in the long-term trend of real returns from any equity markets are also extremely prudent. In Japan’s case, the shortage of history (we only use data since the initial post-war reconstruction phase which we think ended in the mid-1950s) means that our trend projections allow for greater uncertainty than either the UK or US, which have over a century of data. But in fact there is widespread agreement amongst expert professionals that we ought not to expect any impact on the long-term trend of real returns from investing in Japan as a result of these tragic events.

The near-term impact on markets is likely to be explained by three factors:

1. The effects on measured activity – output, GDP, exports etc
2. Perceptions about the underlying valuation of Japanese equities
3. The effects on the mood of Japanese investors.

We should comment briefly on all three influences on the impact.

Counting the cost

While the destruction of national resources is always a loss, in economics the replacement of scrapped assets is counted as a gain. We can also anticipate that economic output will be temporarily lost due to power shortages. We do not yet know how public capital will be applied to making good personal loss, so that the neutral effects of reinvestment we should expect in the national accounts are not prevented by financial incapacity at the individual household level. Overall, however, the profile of activity will definitely change but not , over a decent interval, its eventual level. Temporary effects should not greatly alter the price investors are willing to pay for long-term profit and dividend streams for Japan’s businesses.

Market valuation

The market’s capacity to absorb such a shock ought therefore to be partly dependent on whether the valuation of share prices is thought to be particularly high or low at the time of the shock. Valuations are generally much less demanding than at the time of the Kobe earthquake in 1995, thanks to the combination of modest returns and gradual improvement in both profitability and profits in absolute. If we examine all incidents of major earthquake activity in industrial Japan since the start of the 20th century it is arguably the health of the banking system and the state of the property market (its main collateral) that has explained best the market impact. Both are infinitely healthier than in 1995.

You will read or hear that the Japanese public sector could not be in a worse shape to deal with a disaster. This misses the point that governments never have money; only the private sector and foreign sector have money. Governments merely attach some of it, through taxation or borrowing. Japan is fortunate as an immensely wealthy and highly successful trading nation that it is not dependent on foreign creditors. In an era of low personal incomes growth and high risk aversion, the government’s financial deficit necessarily follows from the personal sector’s preference for high, liquid and low-risk holdings of financial assets and so has not made borrowing difficult.

Mood

If the economic impact of the tsunami is temporary and the valuation context is supportive, the market impact may mainly reflect its unpredictable effect on the mood of Japanese households and their instincts for how to manage their own balance sheets better in response to this sort of risk. We will see some national characteristics come to the fore in this crisis involving fortitude and discipline but we cannot assume either will extend to their risk tolerance.  They are likely to be glad they have been so risk averse to date but we cannot be sure they will not decide to be even more risk averse. If they are, the job of markets is to lower prices to tempt them back to risk taking.

Unlike 1995, markets look much more attractive to foreign investors and so their reaction could prove an important factor in determining the subsequent price action in Tokyo. Several major investment houses had said before the earthquake that they were bullish of Japan at current valuations and had been increasing exposure.  Amongst conventional valuation measures, yields are now higher than in the US and price to book values lower than either the US or UK. Earnings and cash flow multiples will be less useful for comparative purposes because of the short-term dislocations to sales.

The three page profile tells the story of how Stuart, a former institutional fund manager, became the pioneer of a fully integrated financial planning and wealth management business.

And in typical fashion, Stuart refuses to pull any punches, drawing attention to those areas of advisory businesses that all too often fail their clients, such as standardised investment solutions (which we refer to as ‘factory models’) that fail to effectively manage risk within client portfolios.

The full article can be read by clicking on the following link.

Two well-known academics from Edhec, the French business school renowned for its investment faculty, writing under the heading ‘Private wealth management needs better risk control’, argue that ‘in investment risk management, customisation all too often stops at the client’s overall level of risk aversion, without specific consideration of his or her particular situation’.

The paper published by Edhec-Risk Institute on the application of liability driven investing to private wealth, on which this article is based, was featured in Stuart’s post Academic endorsement for outcomes-driven investment on 4th October.

Stuart was asked by the FT to contribute a piece as a case study because (as far as they know) we are the only firm that has adopted the institutional techniques of liability driven investing when designing and managing fully-customised goal-based portfolios for individuals and  families. The key difference we highlight is the way basing all decisions on probable outcomes changes the nature of the relationship between client and adviser. The FT heads Stuart’s piece ‘The conversation that transfers power’ which is exactly what No Monkey Business thinks needs to happen. For a link to the article please click here.

If you would like to read more about outcomes driven investing, we have also posted this Master Class which uses drawdown from capital in retirement as an example.

When defined in terms of a set of explicit benefits, success can also be measured explicitly, such as by
• spending the maximum that is both sustainable and desired
• meeting preferences for different spending at different ages and stages
• taking the right amount of risk to create as much additional wealth as is valued
• making the best decisions about gifting or managing ‘surplus’ wealth
• avoiding unnecessary costs.

Success is of course measured by outcomes but also by the way the progress of the journey is experienced. This depends heavily on clarity and confidence about these outcomes, both at the start of the journey and at every stage, whatever happens to markets, inflation, your health.

In this Master Class, I explain why the methodology of liability-driven investment (LDI) used by institutions should be used by private investors to manage money to meet defined outcomes, such as annual spending in real terms, at defined dates (or ages). It deals robustly with the three sources of risk that need to be addressed by all those approaching or enjoying retirement:

• inflation
• investment
• longevity.

In contrast, the typical industry products, portfolio solutions and planning advice do not deal properly with these risks and cannot confer clarity and confidence. Their simplistic premise, based on industry convenience rather than client need, repeats the common errors of unrealistic assumptions and bad product design that people are likely to have encountered in the past when accumulating financial assets.

The principles of drawdown

Funding retirement spending involves assigning to some money the role of meeting spending needs when earnings cease. Money does not need to be held exclusively in a pension account to be assigned this role.

The process of funding retirement spending is divided into two sequential phases: accumulation and drawdown. Using a bath-time analogy, accumulation is about filling it and drawdown is about emptying it. As long as there is some water in the bath, its volume is subject to a capital-market process of expansion and contraction, as a function of any trend rate of return (expansion) and volatility (over short periods, expanding faster than trend or even contracting). The return and risk characteristics of a ‘portfolio’ (which you can think of as describing a particular stock of water) depend on the sort of assets it holds and how they are put together.

Whilst the bath is filling up, the effect of volatility will be cushioned by the new inputs. Whilst drawing down, however, the speed with which the capital stock is exhausted depends critically, for any given rate of draw, on the volatility of the portfolio.

The returns we are interested in are called ‘total return’ and include both change in capital value and any dividend or interest. Cumulative returns are calculated assuming this income is reinvested as received. Investors collectively trade off yields and growth potential against each other on a presumption of a common required total rate of return. It follows that consuming income is in any circumstances (including distributions from trusts) a form of drawdown from capital.

Constraints

How the entire process is planned and managed depends on the constraints imposed on the goal. If these are not specified correctly, the plan will not be managed efficiently and the benefits derived from the capital are likely to be less than they should be.

The first general constraint is that the target outcomes need to be expressed in real terms, whatever the actual rate and profile of inflation over the life of the plan. Unless outcomes have comparable purchasing power, they are as meaningless as if expressed in Turkish lire.

The second is that the bath must not run out before it has achieved its minimum objectives. This constraint needs to bite hardest if all spending depends on the plan assets alone.

To the extent the assigned money is held in a pension account, the rules governing personal pensions now constrain each of:

• the level of inputs
• the stock (in the form of a ‘lifetime allowance’)
• the rate of draw
• the benefit of generation-skipping bequests.

These constraints are general but in my introduction I referred to explicit valued benefits, such as time preferences and competition between goals that constrain drawdown in a way specific to each individual. This calls for a high level of customisation of the management of the journey that standard industry solutions cannot easily provide.

Balance

For a plan to have integrity, that things that define it must be quantified and the values must be internally consistent. What defines it are:

• the resources applied (availabel or required)
• the target outcomes
• the time horizons (if drawing down, these are a sequence of dates not a single date)
• the amount of risk accepted or sought.

This inconvenient truth about internal consstency, or balance, flows from the same theoretical source as the tenet ‘there is no such thing as a free lunch’. For instance, taking more risk increases the uncertainty of outcome so achieving a given minimum acceptable outcome at the same level of confidence must call for additional resources. The investment industry generally does not like inconvenient truths.

Management

The entire process is subject to several sources of uncertainty that need to be allowed for when planning but also call to be managed thereafter. The management techniques can be one of three:

• avoiding a risk
• insuring (or hedging it)
• embracing it but also trying to control it.

As financial management tasks go, living off capital subject to constraints is one of the toughest, needing to deal jointly with the three different sources of risk. It is mostly performed with hopelessly inadequate technical resources.

Inflation risk

“Inflation is as violent as a mugger, as frightening as an armed robber and as deadly as a hitman”, said Ronald Reagan in 1978. Inflation risk is also very well disguised and difficult to model. No Monkey Business addresses this problem by modelling the return and risk of asset classes in real terms, based on all available histories for inflation-adjusted returns from equity markets around the world.

The uncertainty inherent in different asset classes can alter significantly when expressed in terms of either long-term real wealth or short-term nominal volatility. The largest transformation occurs for fixed-income investments or bonds. They are inflation’s most frequent and most damaged victim. It happens because inflation is so well disguised that the markets’ implicit estimates of future inflation, which make up most of the nominal yield of a bond, have historically shown very large cumulative errors. Cash also has uncertainty of real outcome but the impact of errors in estimating inflation are at least dampened by the market effectively making fresh estimates all the time instead of once only, when the bond is bought.

Longevity risk

Longevity defines how long the plan needs to last. Uncertainty about longevity for a single life is very high so self-funding of the risk means you have to plan on a long life and draw less. This risk can be eliminated by an annuity, whose payout reflects the mean mortality of all insured lives of the same age.

You have a choice about the form of annuity you buy, affecting the level of income. Options include:

• a pension for the surviving spouse
• maximising starting nominal yield (leaving inflation risk uncovered)
• maximising inflation protection
• covering mortality risk while still enjoying payoffs from equity bets.

Once drawdown starts, the option of leaving the casino by covering some or all of the longevity risk needs to be constantly assessed as part of the management of the plan. The impact on the welfare value assigned to a bequest has to be part of this assessment.

Investment risk

Investment risk is, as we have seen, best described as the uncertainty or possible error associated with assumptions about the portfolio’s real total return. Since we are interested mainly in risk as the uncertainty of real outcomes, we need this to be specific to the time horizon.

This level of specification of the investment inputs to the plan is a problem for the retail investment industry, because of the economics of matching, or managing the mismatch, of assets to specific date-stamped liabilities, which is the essence of modern approaches to liability-driven investment for occupational pension schemes. The problem of applying the same portfolio to different needs or liabilities was once thought to have been solved by with-profits policies and that failed solution has not been replaced by a more robust one, except in rare firms like ours.

The industry’s solution to non-customised portfolio management (multi-purpose, multi-horizon) relies on diversification between several asset classes. As we have seen, this gives a role to bonds which is suboptimal in terms of real outcomes. A better approach is to manage outcome risk by diluting equity exposure using a risk free asset. In real terms, the only risk-free asset is a horizon-matched index linked gilt, incorporating an inflation guarantee. Cash can only be considered risk free for very short horizons.

We divide the plan into time slices (each funding say two or three years of draw) and manage the asset allocation for each time-slice portfolio dynamically as market conditions and horizons change. Broadly speaking, early years are matched by cash, middle years by a combination of equities and index linked gilts and later years by equities. Clients see the aggregate portfolio allocations.

The approach is described graphically in the chart below. The plan runs from age 60 (now) to age 90. The assets assigned to the goal are the sum of all the time-slice columns, each of which represents the present value of the resources required to fund the acceptable range of outcomes for real spending in a particular two-year period based on age (normally the age of the younger of a couple). That range, capturing in this example 99% of probable outcomes, is shown as future values, with a mean level, an upper boundary (with just 1% chance of being achieved) and a lower boundary (with 99% chance of being exceeded) equivalent to the worst acceptable outcome. In this example, the minimum spending target starts at £160,000 pa gross equivalent draw, in real terms, tapering at several stages of retirement. Note that if the minimum was scaled down to £16,000, say, everything else adjusts proportionately.

The relationship between the floor and the mean is a measure of both the investment and the inflation risk being taken. But the preference for that amount of risk will have been exhibited by the client directly, from the information we provided about different ranges of real outcomes, anchored on different minimum levels and associated with different levels of resources required. They will have processed that information by thinking about personal consequences (which they know best) and applying their own values (that they may not even explicitly know they hold).

This approach to discovering risk preferences is far superior to the solutions they would be forced to use if not given information about probable outcomes, such as self-diagnosis of risk ‘scores’, hypothetical questionnaires or psychometric testing. These are all means the industry wants to use to connect individuals, regardless of the diversity of their horizons and constraints, to a relatively small number of standardised, collective portfolio solutions. In fact, those risk assessment approaches make no such connection, because they can mean everything or nothing and certainly not the same thing to all parties to the conversation.

The resources assigned to each time slice are shown in the chart divided between the different assets held. Blue denotes risk-free assets, which are cash for the first two and thereafter index-linked gilts. Red denotes equity, diversified geographically across markets representing over 90% of the world’s total market capitalisation. These are markets that can be invested in cheaply using index-tracking funds.

The plan as a journey

As time passes, the early time slices drop out, as the money is spent, and the later slices become shorter, and so their asset allocation will move from risky equities to risk free. The speed of that change is responsive to market conditions as well as to the time remaining.

If the plan is funded to achieve its lowest tolerable outcomes, instead of an outcome with only a 50% chance of being reached, projected surpluses are likely to build up. As the journey progress is reviewed, these can be used as a basis for assigning some money to other goals, taking less risk or increasing spending. This is clearly more robust than funding on a 50:50 basis, an approach which we have seen lead to large deficits in UK occupational pension schemes and shortfalls in mortgage endowments.

Prepared with route maps marked out with realistic objectives and planned with proper respect for the many and complex sources of uncertainty, self-funded retirees are far more likely to maximise the benefits, exactly as they define them, from their capital.

The information contained in the returns themselves and in the underlying asset allocations is about our investment process itself. So an analysis of our performance is an analysis of our process in action.

The process itself addresses a much trickier question: how do you manage money when the lesson properly learnt from both theory and practice in financial markets is that a manager cannot know what is going to happen in the short term, and their opinion is of limited value to their client? How does a battle-hardened agnostic place their bets and why?

The process is an outcomes-driven approach to goal-based investment portfolios, which we term ‘Defined Outcome Portfolios’. The approach is detailed here on the website.

The key characteristic of this approach is that some bets are avoided or hedged and others tightly and dynamically managed, within a specified ‘risk budget’. The risk budget is expressed in terms of a range of tolerable outcomes, in real terms (after inflation), at the times the money is needed.

With such an approach, the outcomes at shorter horizons are the wrong ones to make bets about. To the extent they are fully matched by risk free assets, matched to the duration of that time horizon, a key insight is that clients can afford to be indifferent to the volatility of these assets. If the volatility has no impact, their short-term performance is also of little import. The volatility is zero for cash but index linked gilts, though risk free in real terms at maturity (because of the government guarantee of inflation uplift), are nonetheless quite volatile in the period prior to maturity. But the volatility has no impact on outcomes, by definition.

Only the volatility of risky assets has a bearing on the probable plan outcomes and therefore the chances of the client achieving their minimum objective. These are the bets, as opposed to the hedges.

This transforms the relevance of the volatile short term return path of the ‘current’ portfolio. It makes a nonsense of comparisons of achieved short-period returns with other managers. Our clients are out of the performance race and in a journey, of their own planning.

Private clients are largely unaware of how to use performance information where planned goal outcomes are partially protected by hedging. They are not alone, however. The advent of ‘liability driven investment’ in the institutional market, which is the closest parallel, has also forced trustees to rethink the significance of reported performance, both for their own asset manager and for comparisons between managers.

Returns
In an earlier post, part way through the market fall, we took two clients as examples. Since all clients have a different combination of explicit time horizons, outcome profiles and risk tolerance, we have to use samples, not a universe. We have updated these two examples in this article.

They both have Defined Outcome portfolios funding retirement spending. One is still ‘in accumulation’, with about 5 years before drawdown starts. The second is already in drawdown, meeting current retirement spending.

The examples were chosen to have similar risk tolerance so that the asset allocation differences, as output by their own models, are explained by the time horizons (although changing profiles for spending outcomes at different stages of retirement also make a difference).

The returns are money-weighted returns. Because the cash flows, mainly new savings or draw, typically arise at month end, there is essentially no difference in the cash-flow adjusted returns whether money-weighted or time-weighted.

The period is from December 2007 through August 2009, as this roughly corresponds to the start of the bear market and the subsequent recovery.

The accumulation portfolio achieved a return over the whole period of -11.3%. The drawdown portfolio achieved a return of -4.1%. The paths of each, indexed to 100 at 31/12/2007, are shown below in Fig 1.

Fig 1: Index returns of two Defined Outcome portfolios

Asset allocation
The building blocks of a Defined Outcome portfolio are divided into two:

• Risk free assets (matched to the nature and duration of the time horizon, such as £x real spending in year y)
• Risky assets (in the form of a mix of equity markets across the world, as represented by broad indices with all but ‘systematic’ risk diversified away).

The two are combined to ensure that the projected outcomes of a dynamically-managed ‘plan’ (not just the current portfolio), counting down to fixed dates, are always consistent with the agreed tolerable outcomes.

The return paths of the building blocks (source: Lipper Hindsight) are shown in Fig 2 below, indexed to 100 at 28/09/2007

• The cash return is a one month deposit rate (the risk free asset for durations below about three years)
• The index linked gilt return is derived from the over 5 years FTSE index (as representative of the ‘medium-dated’ maturities where we typically combine risky and risk free)
• The equity returns are for index-tracking funds provided by Legal & General (as representative of the returns that could have been earned from tracking the risky asset building blocks, after the fund expenses attributable to institutional units).

Fig 2: Indexed total returns of the portfolio building blocks

Attribution
Because the asset allocations output from each model run for each client are implemented using index-tracking funds and individual index linked gilts, the portfolio return and its variability are almost entirely explained by the allocations.

The accumulation portfolio started with an equity allocation of 100% and the drawdown portfolio 65%. The risk free return has been relatively flat due to both low interest rates on cash and moderate volatility and net change in index linked gilt yields over the period.

Considering the difference in equity exposure at the outset, the gap at its widest point between the two portfolios is surprisingly small. The largest drop for the accumulation portfolio reached 28%. This also appears relatively small compared with the returns apparently experienced by most UK-based equity investors, including those investing purely in the UK, which was down 38% at that same point.

As Fig 2 hints at, a large part of the answer is geographical diversification. We tend to hold more in European, Japanese and US markets than most investors. This follows logically from the intention of diversification and is likely to be an output of any portfolio optimisation process that seeks to maximize expected return per unit of risk. However, most investors constrain exposures to foreign markets to suboptimal levels. Diversification benefits reflect the distribution of weights to each market not just the number of markets held.

Short-term correlations between different equity markets are highly unstable (and indeed increased dramatically during the bear market). But differences in achieved returns do emerge, implying differences in future returns. With fairly similar long-term real return trends apparent in the historical data, mean reversion operates both between and within markets. Larger international exposure allows this to be exploited more efficiently.

As it turned out, much of the benefit from geographical diversification in this particular period came from currency movements. Sterling fell as asset prices were at their weakest and strengthened as equities themselves rallied.

Currency movements are not normally well correlated with market movements so most of the time these two sources of risk will not combine to increase portfolio risk significantly. What happened here, with currency dampening portfolio volatility, cannot be predicted in advance or relied on.

Asset allocation changes
Fig 3 shows the asset allocation changes for a drawdown model starting with the December 2007 quarter and ending in the two months to August 2009. The actual model runs are monthly but we have conflated the changes to quarterly, to simplify the rebalancing narrative.

The resources at the outset in this model run were £1.8m which puts the changes shown below into context. The range of monthly change in allocations at the highest level, between risk free and risky, is from 4% to 8% of the total portfolio. This is clearly a gradualist approach.

Fig 3: Changes in net equity exposure

The narrative here, even if at the time it needed some explanation and illustration,  is entirely consistent with the portfolio process and so held no surprises for the client.

• Two quarters of additions to equity exposure relative to index linked gilts as the bear market began, as expected equity returns to each planning horizon were then higher than before and higher relative to index linked gilt yields for the same horizon – hence hedges can be marginally lifted
• A small net pull-back in the next quarter as equities rallied and index linked gilts fell, lifting their real yields
• As the US housing bubble started to go wrong and the credit crisis got worse, dragging risk free yields down with it, the next three quarters saw net additions to equities
• From March 2009 the model called for net sales of equities as prices rallied and risk free rates also moved higher.

The net change over the whole period is an addition to equities of £0.25m, equivalent to 14% of the starting portfolio value. Considering the net fall in equities over the whole period, and the relatively small net fall in risk free rates, a constant risk tolerance should be expected to lead to reductions in hedging and an increase in risky exposures. Investors (or their advisers) who instead altered their risk tolerance in response to what they thought was happening in the world would have shown the opposite response, selling risky assets as they declined in price, or might have been frozen into inactivity.

The net changes filter out the rebalancing arising between different equity markets which is also shown in the table. The gross change over the whole period is 42%. In practice, some of the smaller changes indicated by monthly model runs may not be implemented, as the likely improvements in risk-adjusted return are too small relative to the costs of transactions (even when these are minimized by using exchange traded funds on an execution-only stockbroker dealing platform). Many small changes should reverse themselves from month to month. There is an element of judgement in filtering these small changes.

The main changes in country weights are as follows:

• Reductions in Japan, which had started the period at 36% of the risky allocations – high exposure in Japan is a key test of a globally-diversified approach to long-term return return opportunities
• Roughly half of the net addition to equities was in the UK, which is a natural response to increasing real return ranges in all markets, as plan outcomes can then be met with less uncertainty in the home market.

The portfolio model run for August had the following new target allocations.

Fig 4: Closing model allocations

These allocations are entirely logical given the client’s planned profile of the drawdown over the life of the plan; the client’s tolerance of uncertainty in the draw; and our projected return probabilities for the portfolio building blocks, as generated by a new model run in August 2009.

• The 16% cash allocation is matching about three years of spending targets (as an estimated pre-tax equivalent portfolio draw).
• From years 4 to about 8 the outcome targets are fully matched by a schedule of maturing index linked gilts with the same duration as the spending
• The next 6 years are partially matched by index linked gilts but equities are also held against these spending targets
• Only durations later than 15 years are fully backed by equities.

The proportion of the total plan resources that is sensitive to volatility in the portfolio value is represented by the allocations to equities from years 8 to about 15. They are sensitive because the return-generating element of the model does not assume that a fall in equity prices will be offset fully by higher real equity returns within the time frame required for that horizon. There just is not enough time to be that sure. This portfolio proportion, for which short-term performance has an impact on probable outcomes, is about 28%!

The earlier horizons (35% of current resources) are indifferent to volatility because they are fully matched. The later years, beyond 15 years, (the balance of 37%) are far enough off for mean reversion to have offset much of the fall in current value, leaving outcome probabilities little moved by the fall.

Even though there is a middle segment of the plan that is sensitive to volatility, any plan that was fully funded to meet the drawdown targets with a high level of certainty should still meet its original planning targets. This is based on the simulations of the plan, which tested randomly-generated paths for equity markets and exchange rates as well as their interaction with a pre-defined rate of draw in real sterling amounts per annum.

In practice, the progress of the portfolio is likely to feed back to the client’s comfort level in spending. Should this arise because of really bad equity markets globally, implying widespread economic stress, it would not be surprising if the client chose to trim their spending objectives anyway, even if the model stress tests suggested it was not strictly necessary.