Ahead of the curve: Modelling the unmodellable

• Scenario planning and thematic analysis is growing in popularity as a means of countering the unpredictable nature of the investment universe

These trends were not known then, but such lack of foresight is not unusual. Not being able to prepare for the future is the norm rather than the exception.

In his youth, the economist Kenneth Arrow analysed weather forecasts for the US Army. When he found that the predictions were as reliable as historical averages, he suggested reallocating manpower. The response from the army general’s office? “The general is well aware that your division’s forecasts are worthless. However, they are required for planning purposes.”

Even before COVID-19, many shared that scepticism of forecasts. The failure to foresee the 2008-09 financial crisis started a debate on economic modelling. Over the past year, the performance of epidemiological models has not resolved this quandary.

Investors have long known that “all models are wrong, but some are useful,” to use the statistician George Box’s pithy idiom. But, there are modellers who use this defence to preserve models beyond usefulness. Meanwhile, there are unrealistic expectations from consumers of models including investors, policymakers and society. They assume that complex issues are easy to forecast, when some things are just unknowable. This gap begs the question of what investors should do.

In the 1920s, economist Frank Knight, made a distinction between uncertainty and risk that remains essential. Risk applies when the outcome is unknown, but the odds can be accurately measured. For example, the probability of heads or tails. 

Uncertainty is not having the information needed to set accurate odds in the first place. In 1980, what was the likelihood of the end of the Soviet Union? Or in 2000, what was the chance that China would develop an indigenous and sophisticated technological ecosystem? 

Or today: what is the prospect of generating inflation via the US Federal Reserve’s recent framework review? No model can answer these adequately. There are too many moving parts; the probability distributions are unknown, and things are fundamentally uncertain.

Scenario planning, and thematic analysis, is one response to such ‘unmodellable’ events. It can be used to encourage investors to stretch their thinking and consider possibilities that seemed remote, including a global pandemic. 

Thematic investing, which is what this is, is as old as the investment, even if it has become a bit unfashionable. 

Themes, some say, encourage momentum investing.  Themes are fine, another view goes, but they do not pick stocks. Thematic investors frequently pick too many themes and are overdiversified. Finally, some say themes are just marketing and sales, not insight. Some of this is true. If done badly, thematic investing can indeed degenerate into all those things. 

But used correctly, themes are a tool for seeing the wood for the trees. Themes are important for three reasons.

First, they help investors generate an understanding of the key tailwinds and headwinds that, perceived early, can provide analytical advantage.  The decline of US government bond yields is a good example. For several connected reasons, yields fell from double digit rates to zero over 40 years, providing a tailwind to all kinds of financial assets, especially duration-led strategies. 

Similarly, in the late 1980s, when Japanese stocks outperformed US stocks by 250% in dollar terms, discussing whether to buy Sony or Nintendo was less important than allocating to Japan. Meanwhile, since the 1990s a technology bull-market has been apparent, driven by secular winners, many also Covid-19 winners. In all these cases, getting that big decision right was key for investors.

Second, themes cut through traditional indices and narrow specialisations by country, region, sector, or capitalisation. These divisions made sense before financial markets professionalised. But they have been undermined by globalisation, with the correlation between the Stoxx 600 and the S&P 500 close to 80% (see figure). In recent years, it mattered less whether investors were in the US or Europe than whether, for example, they avoided financial firms. Yet within that sector, payment providers have outperformed substantially, and some emerging markets banks generate extremely high returns on assets. And within emerging markets, places such as Vietnam have less to do with economies such as South Africa, and yet they remain ‘emerging markets.’ 

Themes encourage epistemological honesty. They ask investors to clarify what they really do know, and why they are investing in what they are investing.

Finally, themes improve awareness of the strategic context in which decision-makers act. They are a way of thinking how companies think, and go hand-in-hand with scenario analysis. 

To conclude any thematic analysis, it is important therefore to consider a range of plausible scenarios that could emerge, and identify key markers that help indicate which particular path we are on. This encourages investors to think through the decision, before the judgement call has to be taken.

The price of a financial asset is affected by many markers. These include, credit conditions, central bank policy, geopolitics, litigation, ownership structure, fund flows, policy and environmental liabilities. And no model can capture all of this adequately. The question therefore is not just which outcome is right, but how asset allocation can be conducted in a probabilistic way to account for these future outcomes. 

Models are more likely to be useful when used in conjunction with thematic analysis and scenario planning.   

Sahil Mahtani is thematic strategist at Ninety One