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Stochastic models incorporating Modern Portfolio Theory techniques as used by a number of leading actuarial firms have been challenged as not being appropriate for developing strategies for retail investors.

The majority of IFAs are now, however, using these models through one route or another be it directly licensing them or accessing them through platforms or providers. According to NMG’s IFA Census in April last year, over 60 per cent of IFAs now use risk profiling and asset allocation tools in the UK.

This figure rises to 70 per cent where the IFA specialises in investment or retirement planning. Financial and investment planning tools continue to grow in their popularity and they are increasingly central to many firms’ investment advice processes.

Stochastic asset models provide advisers and their investors with a forecast range of likely investment returns over time and an assessment of how likely those returns are to happen. MPT expects that extreme events, both good and bad, will happen but that they will happen much less frequently than ‘average’ returns.

If a model has incorporated extreme events successfully then that should provide advisers with comfort that it is robust and that the long-term investment plans prepared using it are solid.

Many commentators are focusing on the hugely negative nature of the recent market turmoil as if it is a one-off. This is not the case. It has been rare, but not unusual. History suggests that such events occur once every 50 years or so but with intervening periods of over 100 years and as short as 20 years. The table lists six stock market collapses that were clearly global in terms of the investing participants and which have occurred in the last 300 years.

Other local events may have had repercussions elsewhere in the world, but each of the six had a clear impact globally where there were investment markets. While the limited number of data points prevents us easily putting an expected frequency on a likely global collapse, in principle the level of returns we have seen in the credit crunch collapse should be shown by a model to happen rarely.

Stochastic modelling companies determine assumptions for modelling future investment strategies through a combination of historical data analysis, implied current market yield expectations, current equity risk premiums and assumptions as to rational investor decisions. Historic data gives us a sense of the degree to which returns from certain asset classes move around their long-term averages, their volatility. We then create model portfolios that meet the various needs of investors based on their attitude to risk.

In one provider's standard asset model, it provides 10 risk-constrained asset allocations. The model portfolios start with 100 per cent cash and for each subsequent portfolio the cash is replaced with a percentage of bonds, property and equities of different types. The most risky portfolio has all equities, most of which are in emerging markets. Hence the level of volatility in each portfolio gradually increases with a commensurate expectation of an increase in expected returns. The increasing volatility is reflected by an increasing range of confidence limits around the expected return, that is, larger potential up-side potential but also larger down-side risk.

To demonstrate the robustness of the model we have prepared charts showing the distribution of returns that are expected from the various model portfolios when they were originally created. Given the nature of markets recently, I have concentrated on the down-side, that is, the potential for returns below the expected average for each portfolio.

I then roll the clock forward and superimpose the results of the actual performance experienced since they were created.

Note that we are concerned here with just the performance as reflected by the various underlying market returns. I have not allowed for the additional returns achieved through active fund management nor have we made any allowance for expenses of management or tax.

The chart shows the actual performance of the 10 model portfolios in the 3 ½ year period since they were constructed at the end of 2005 to the end of the this year's first quarter, to date the bottom of the UK market.

Looking at the chart we would expect a 1 per cent chance of the returns - or worse - indicated by the green line. While the actual performance for the 10 portfolios over the period has been disappointing in absolute terms the outcomes have been in line with expectations in all but one portfolio.

In the most cautious cash portfolio and the two most aggressive portfolios, the actual returns have been well within the expected range. The most aggressive portfolios have a significant overseas exposure and the actual returns reflect to some extent the appreciation of the dollar and euro against the Sterling. The others have been close to the fifth percentile. As such the actual performance has been shown to have occurred within the range of expected outcomes that were identified at the start of the three-year period.

This asset allocation model has successfully incorporated the level of returns seen in the recent downturn. Advisers should draw comfort from this and encourage their clients to stay the course and maintain their long-term plans on the basis that their investments should recover to deliver the average expected returns over time.

If clients are considering investing, advisers should use this approach to modelling to help them understand the potential downside associated with any given risk level, which is treating a customer fairly, as well as of course the upside. It will be reassuring for investors to know that the model used by their adviser has held up in the toughest markets for a generation.

Asset modelling has not only survived the storm but emerged as a powerful tool for advisers to describe the level of investment risks and potential returns faced by their clients and as a result to support mutually profitable long term relationships.

Danny Quant is actuarial director of Distribution Technology