Cookie Settings

Managing risk in volatile markets:How stochastic models help combat investment risks

For Professional Advisers only

Multi-asset funds underpinned by long-term strategic asset allocation can have some unexpected benefits for investors

Multi-asset funds sit in a single category but can be close to incomparable.

Some funds invest in a broad range of asset classes beyond the ‘big three’ to include, for example, commodities and futures, while others may only stray a little.

Meanwhile, forecasting models underpinning funds’ strategic asset allocation are far from uniform.

Many funds do not use an overall quantitative model to set their asset allocations. There will be a model of some description, but it often involves some ‘round number’ strategic asset allocations with a tactical overlay.

For those taking the quantitative route, asset allocation is more systematic, and the choice of model becomes an important one. There are several kinds out there…

A model choice

Deterministic models – the original and simplest, and which provide a single projection – have little concept of risk and may be more suited to adviser cashflow tools than fund asset allocation.

On the other hand, stochastic models – which predict a range of outcomes – allow for risk modelling and are more suited to making longer-term projections.

A note on stochastic modelling

The truth is that stochastic modelling is a broad brush; not all models capture the range and evolution of investment outcomes.

For example, mean-variance-covariance models are stochastic but describe a distribution around a single ‘deterministic’ path, so are not much good for capturing investment term effects.

Other stochastic models, meanwhile, fail to capture the volatility clustering seen in equities, which has crucial implications for investor risk profiles and sequence risk in drawdown.

Still other models ignore the impact of prevailing market conditions and simply replay the recent past.

Investment decisions should be based on as realistic assumptions as possible, so the model needs to tick a lot of boxes: be forward-looking; capture the term structure of investment returns and the stochastic volatility of equities; and respond proportionately to changing market conditions.

With your clients facing a range of investment risks, the benefits of these stochastic models can be wide-ranging and, in some cases, surprising.

Market risk

One of the main investment risks facing your clients is market risk. Market risk is a broad term but refers to the risk of a loss because of a drop in the market price of securities. It covers market corrections, bear markets and, as we have experienced this year, the impact of black swan events. At retirement, market risk also encompasses sequence risk.

Fund managers often react, as investors would expect, in a downturn, sometimes changing the weights of their allocations depending on their views and the level of risk in their portfolios. Adjustments can help to stem a short-term decline in value, and calm investors.

The potential downside to this approach is that the funds may be less favourably positioned to benefit from the upswing which can follow.

Conversely, funds with stochastic longer-term models will typically make fewer adjustments and may therefore be better placed to take advantage of any turnaround.

The graphic below illustrates how Embark Horizon Multi-Asset Fund III – which is underpinned by a stochastic long-term asset allocation model – has performed in five sustained rising market periods since launch in 2013.


(click on image to open in new tab)

Volatility is not consistent – and this is key. Periods of high volatility do not typically persist, but periods of low volatility can. And while long-term models are less likely to respond to spikes in volatility, this can leave some simply ignoring the market.

Instead a model should allow volatility to be stochastic instead of fixed. This means that, when individual scenarios are simulated, they will include clusters of volatility interspersed with spells of lower volatility.

Just think what investors would have missed out on if managers panicked in late March this year and sold out of equities – an asset class which pretty much recouped all of what was lost in the following months.

Longevity risk

Longevity risk – you may use another term – is the risk to your clients of outliving their savings. Naturally, as savings are not typically needed until retirement, longevity risk increases as clients approach this point, particularly if they are not putting enough away.

Can clients approaching or even in retirement still be long-term investors?

Most people underestimate how long they are likely to live. A 65-year-old man has a 50% chance of living to 87, while a 65-year-old woman has a 50% chance of living to 90 (Source: ONS 2014).

Research1 suggests that for those with defined contribution savings who draw down, rather than annuitise, as an income in retirement, up to 60% of that income is dependent on investment growth during retirement.

Conversely, the amount saved during one’s working life typically accounts for only 10% of the stream of income, while investment growth on those savings pre-retirement might account for 30%, according to the research from Russell Investments.

So, asset allocations based on stochastic modelling can still be valuable for many clients in retirement, and not only for their benefits over the long term.

Figures show that, should clients’ needs change, portfolios underpinned by stochastic forecasting also tend to remain efficient over shorter periods too.


One of the primary benefits to investors of multi-asset funds remains their original purpose: to provide diversification via strategic and tactical asset allocation.

Research2 suggests that asset allocation ‘explains’ between 90% and 94% of the variability of pension fund returns over time (if broadly conventional asset allocation and active management is employed).

The remainder – the 6% to 10% – is attributable to market timing and stock selection.

This conclusion is backed by the well-known asset class ‘patchwork’, illustrating discrete-year returns.

The message is clear and explains how the chart got its ‘patchwork’ moniker: asset classes finishing top of the pile one year could finish anywhere the next and may indeed finish bottom. Equally, some of the best performers can continue to deliver stellar returns for several years in a row.

The value of multi-asset investing can also be illustrated using the same approach.

The graphic below shows discrete-year annual returns for a range of asset classes, and where Embark Horizon Multi-Asset III sits in that patchwork in the six years since it launched.

Generally, this is a useful exercise to illustrate how difficult it can be to pick the best (or worst) performing asset class in a given year. It also shows how a multi-asset approach can provide some consistency – a degree of predictability, even – for advisers and investors.


(click on image to open in new tab)

Last word

Multi-asset funds underpinned by long-term strategic asset allocation – and dynamic tactical asset allocation – can have some unanticipated benefits for investors.

Having a long-term outlook can combat market risk by side-stepping the need to adjust weightings prematurely, and potentially doubling down on the negative effects of volatility.

Likewise, stochastic forecasting has become increasingly relevant to retirees, many of whom will almost certainly still be long-term investors.

And for whom the phrase still holds: It’s time in the market, not timing the market, that counts.



Past performance is not necessarily a guide to future performance and the value of investments (and any income from them) can go down, so an investor may get back less than the amount invested

To find out more or to discuss any of the points raised in this article, contact your Account Manager on 0345 607 2013.

To access any of the documents, graphs or images in this article, see under ‘supporting documents’ on our managing risk home page.


1 The Russell 10/30/60 Retirement Rule. Russell Investments. July 27, 2015

2 Gary P. Brinson, L. Randolph Hood and Gilbert L. Beebower. Determinants of Portfolio Performance. The Financial Analysts Journal, Vol 42 No4, July/August 1986. Roger G. Ibbotson. The Importance of Asset Allocation. Financial Analysts Journal, Vol 66 No2, 2010

About the author

Scott Sinclair, Content Strategy Manager, Embark Group

Scott Sinclair is a former financial journalist and editor who has spent the past five years creating engaging content for financial advisers, first with Zurich and then Embark Group. Scott was editor of Professional Adviser, part of Incisive Business Media, between 2012 and 2016.

Related items

Managing risk in volatile markets - image

Managing risk in volatile markets

Show clients how four key investment risks rise and fall over time, shaping your advice.

Read more
The role of financial personality - image

The role of financial personality

How to best engage with different personality types during market volatility.

Read more
The case for staying invested - image

The case for staying invested

How Covid-19 reinforces a famous investment principle followed by Warren Buffett and others.

Read more