SA’s wheels will just spin in the mud if it produces plans without specifics such as costs, responsibilities and timelines.

This column was first published in Business Day. 

As soon as the border is open, I plan to have a long holiday in some of my favourite spots in SA’s nine provinces. Maybe I will check out what the fuss is about in Nkandla. I know where I want to go, what I want to do and when, how much it will cost — and who is responsible for making it happen.

I am sure we all made plans in lockdown we didn’t keep. “Learn Mandarin” comes to mind. The plans were non-specific, uncosted, amorphous, too big to handle and involved slipped schedules.

Does President Cyril Ramaphosa know how to plan?

This is a very serious question at the heart of the current malaise as SA slips towards the fiscal cliff edge. He has given very little hint that he does — though there are occasional forays of loyalists in the media saying there is a 10-year (two-term) “governance masterclass” arc of a plan, without any real evidence for it. One wonders how easy it is to plan without, for instance, an energy adviser in one’s office.

Businesses know they live or die by their ability to plan supply off forecast demand, to plan workforces and investment. A fascinating cycle of board meetings occurs annually, particularly in about September and October, in which the biggest companies discuss and sign off on the following year’s budgets, investment decisions and levels of risk appetite.

These types of meetings for 2021 are about to start. What will they say? Does the government even know that decisions that will dictate 2021 are already being made, while load-shedding and political navelgazing are ongoing?

The government has generally been exceptionally poor at planning.

The National Planning Commission does less planning than broad strategic direction research — excellent though it is, particularly recent papers on state-owned enterprises (SOEs) and the digital future (which are well worth reading). The failure of the National Development Plant (NDP) was to not shift it from the good initial plan into a timelined and budgeted work plan.

Government plans lack specificity, and with it the ability to hold ministers and directors-general to account.

There have been rare exceptions. Former finance minister Malusi Gigaba’s 14-point plan in 2017 was unique in laying out a specific timeline for implementation, though it was quickly abandoned.

Similarly, the Eskom road map by public enterprises minister Pravin Gordhan lays out actual goals with dated timelines. These have allowed the energy industry to hold Eskom to account recently for pushing back and then dragging forward, under pressure, dates for its unbundling to take place.

Ramaphosa’s 10-point plan for the economy in 2018 has been long forgotten because there was no detail, costing, timelines or delineated responsibilities. These are the key conditions.

Plans ultimately gain credibility and buy-in, and are accepted in corporate board planning meetings, only if these key conditions are met. They are not currently met regarding the economy, so markets, companies and investors do not give the government the benefit of the doubt.

It is equally true for corruption. That is why the bar was set so high for the past weekend’s ANC national executive committee meeting. Only if real and solid measures regarding ANC membership (and various issues such as wages and pensions that go with them) are withdrawn will the bar be cleared.

So we turn to discussions among Nedlac social partners about a recovery and reform programme. Is it a recovery plan to sit in a room with big labour, big government, big civil society and big business armed with large Velcro words to stick on the wall? If we say “infrastructure”, everyone will clap in agreement and can “compact” that this is all a jolly good idea. But so what?

What is the mindset on the issue of state versus private enterprise? What is the specificity of who will do what within the government, in business, development banks, banks and asset managers? What are the specific funding, tendering and project design modalities?

All these questions won’t generate much bonhomie but are challenging and might require challenging decisions and the expenditure of political capital to break through. The “agreement” — much trumpeted in the media — between social partners on “plans” has been a chimera.

If there is no specificity, costing, timelines or delineated responsibilities, the process will generate much spin and PR but it will flop.

Now is the test for whether Ramaphosa had some type of plan all along. A plan that meets the conditions will raise eyebrows and give him the benefit of the doubt as political capital will be seen to be deployed. Interest rates will fall and capital will flow.

A well-made plan will cause skills and capacity to be deployed across sectors (yes, some real Thuma Mina).

(The capacity issue is there but is for consideration on another day.)

Everyone is tired of plans because real ones are so rare. That can be changed, but it won’t be easy. Momentum, or the lack of it, will be key after the weekend, combined with the right people (such as a new energy minister) and real leadership — all to help the economy not just recover to its previous, slightly slower, grind towards real crisis but to properly diverge to somewhere new and exciting.

• Attard Montalto is head of capital markets research at Intellidex.

Banks taking an extra conservative approach to impairments are finding market support, says Intellidex’s Stuart Theobald. Featured in Reuters. 

Corruption is so deeply rooted within the ANC and how it manages political power that it is impossible to change without party-wide reform, says Intellidex analyst Peter Attard Montalto in response to President Ramaphosa’s letter to his party. Featured in Business Tech. 

Considering the social impact of investments with risk and return might not always be the best idea.

This column was first published in Business Day. 

We are increasingly in love with the idea that investments can do good and not just deliver a financial return. Pressure has been growing worldwide for investment managers to consider the social impact of investments alongside risk and return. In SA, regulation 28 of the Pension Funds Act requires pension fund managers to think about the trifecta of environmental, social and governance (ESG) issues when making investment decisions. A guidance note in 2019 from the Financial Sector Conduct Authority said funds should put ESG criteria into their investment policy statements and make these available to members.

Recent research by my firm Intellidex found that almost all pension fund principal officers are expecting sustainable investing to become more important over the next five years, and some even think it is more important than generating returns.

This direction of travel appears to be positive, but I’m sceptical about the conceptual starting point. If we can use investments to make the world a better place and not only deliver a financial return, that seems an obviously good thing. Many argue that sustainable investing can deliver better financial returns anyway. This argument is convenient in that it helps remove tension between those who benefit from the financial returns of an investment and the social returns. Seldom are these the same people.

But I doubt that we can magically get both financial returns and ESG. It seems on purely logical grounds unlikely that ESG investments will match or outperform non-ESG investments for several reasons. One is that as the popularity of ESG investing grows, demand increases for compliant investments, increasing their price and therefore reducing potential returns. Another is that an ESG investing strategy is about constraints — avoiding investments that don’t fit set criteria.

A fund that is constrained has a narrower investment option set by definition. An unconstrained fund can mimic the strategy of the constrained one, but always have the freedom to deviate when tactical opportunities come its way. It seems illogical to say that the constrained fund can outperform the unconstrained one.

The argument against this seems to be that investments that meet ESG standards overcome companies’ natural tendencies to focus on short-term profits that cause longer-term problems. There may be something to this. Bonuses and other performance incentives must be specified in easily measurable terms and fit the normal remuneration cycle. Reward systems are much easier to use for short-term financial targets than objectives of 10 to 20 years with hard-to-measure outcomes like better relations with the local community.

Companies take higher risks and ignore long-term costs, resulting in rewards to managers but pain to shareholders when risks don’t pay off and long-term costs come to bite. So, by pushing a set of ESG objectives onto company managements, one overcomes the problems of short-term incentives leading to companies that create greater long-term value for shareholders.

This seems to be the argument that influential fund managers such as BlackRock advance in saying its “investment conviction is that sustainability-integrated portfolios can provide better risk-adjusted returns to investors”.

I can buy that ESG forces a greater alignment between managers and shareholders, but that is not meant to be the point of ESG. If ESG is just a management-discipline tool then we should call it that. But ESG is meant to be about stakeholder capitalism, ensuring that all interests of those affected by companies are considered. And it cannot be that shareholders are always going to be aligned with other stakeholders, unless there is some radical redefinition of what shareholders’ interests actually are.

If shareholders genuinely desire positive social outcomes, and not just good risk-adjusted returns, then there may well be the possibility of alignment. Shareholders’ return set would now consist of both financial and social returns. But if they value the social returns, they should be willing to give up some financial return in an effort to maximise both. We would then see the market reflecting these views, with prices rising for ESG investments, reducing yield on such funds. Again, it would be the case that financial returns were being sacrificed to achieve positive ESG outcomes.

Some impact investments make this explicitly clear. You can right now go and put your money into Kiva microloans, a nonprofit crowdfunding mechanism that provides loans to individual borrowers in emerging markets. You would get no interest on your loan, but the idea is to get your capital back and to help an identified individual (for example, you can chose a vulnerable refugee) whose progress you can track. Their success is the social return you get for sacrificing the financial return of interest you could have earned on your money.

When it comes to companies applying ESG criteria, I think it is important that companies are clear about where they are willing to give up financial returns if it has a big social impact. Banks, for instance, should be clear about reallocating capital to lending that might reduce yield but increase impact. That should be measured and communicated to stakeholders.

Institutional investors need to think through their mandates and alignment with their clients’ views on social impact. It is no longer acceptable to declare that fiduciary responsibility requires that risk and return be all that matters. We need to take social return seriously, gauging our clients desire for it, and then using it in decision making. We need to be honest that ESG strategies are not only about maximising financial return.

Theobald is chair at Intellidex. 

This is one of a series of columns that were produced for Moneyweb Investor in which Stuart Theobald explores the intersection of philosophy of science and finance. This followed an earlier series for Business Day Investors Monthly on the same theme. May 2016. 

The American economist Paul Krugman recently coined a useful phrase: “the politics of epistemology”. He was writing about the way American politics has distorted what it means to claim something is true. The primaries process has seen all sorts of bizarre claims from all sides. It struck me as a good way to make sense of South African politics right now.

Philosophers talk about epistemology as the as the study of what we know. It is contrasted with ontology, which is the study of what there really is. Ever since Descartes and Berkeley, we’ve been worried about whether what is inside our heads is at all related to what is actually in the world. That remains the case. For example, one live debate in the philosophy of science is whether a concept like a “quark”, and abstract entity proposed by theoretical physics but which we have never observed, is purely an epistemic concept or whether it is something that actually exists in the world – an ontological fact. It may be that theories in physics use concepts that are instrumentally useful like quarks and strings, because they allow for good predictions, but that don’t actually exist in the world.

The politics of epistemology concerns how political power can weigh in on what we see as true or false. So some in South Africa apparently believe a respected, high-achieving finance minister can have committed espionage (a crime which doesn’t actually exist under South African law), while a president who faces 783 counts of fraud and corruption has done nothing wrong. No one seems to care about what is actually true, but rather with what is politically useful to think is true. So we can all think president Zuma never said he wouldn’t pay back the money. Where your political colours are nailed determines what you think the facts are, and what you want others to think the facts are, and reality doesn’t matter. Sadly, some in the media are useful instruments in this effort at fact-making, faithfully reprinting unquestioned what they are fed, and then helping to make other people think they are true.

What has all this got to do with investing? Two things. First it helps to understand that in the political process, the facts don’t always matter. Second it helps to not be distracted and remember that it is the ontology of our economy that really matters to investment performance.

Making up facts works only to a point. The judicial system provides a line in the sand, a point at which epistemology has to meet ontology. Partly this stems from the political strategy of claiming things are contingently true up until a court rules. This is double edged sword for the erstwhile political epistemologist. It allows them to straight-facedly claim something is the case – say that Pravin Gordhan should be investigated – because ultimately it is a court that will decide whether he did anything wrong. That buys them space to spread the belief that he did wrong as part of a wider effort to discredit him, assisted by using the investigating resources of the state to intimidate him and add credibility to their efforts. But then, when a court does rule against them, a rapid damage control exercise has to be launched. So in the long run, as long as our judiciary remains independent, reality does matter.

But for investors, cold hard reality is what matters all of the time. South Africa’s unemployment rate has never been higher. Our economy will grow only half a percent this year, meaning we are poorer per head than we were last year, and significantly poorer in dollar terms. That has serious political implications – with everyone, on average, getting poorer, many social ills that were being tolerated suddenly won’t be.

But, on the other hand, the slight uptick in resources prices is shifting the economics of production for a large part of our economy. The tough recent times faced by mining companies have forced them to dramatically improve their efficiencies. They are now positioned for a sharp upswing in performance. The sharply weaker rand, helped down by the reality of our political dysfunction, has a strong stimulatory effect on some substantial parts of our economy, including what’s left of our manufacturing base. Despite a dramatic skills constraint, our services sector is also in rude health and can improve its own export capability.

The ratings agencies are keenly watching these facts. They are focused on whether South Africa will meet its debt obligations. That depends on the willingness to do so, and on the ability to do so. The first depends on our politicians while the second depends on our economic performance. So far, government has managed to convince the world that we have every intention of maintaining a sound fiscal stance and continuing to keep our debt serviced and under control. Moodys this month said it thinks economic performance will pick up next year. It well might, and the true facts are what we need to keep focused on to be able to tell. So despite the politics of epistemology, you are best served by keeping an eye on the numbers. And those are not all negative.

With SA at the jaws of the hippo, failure to fix our problems means that the IMF will shut the hippo’s jaws for us, says Intellidex’s Peter Attard Montalto. Featured in Daily Maverick. 

SA’s economic response has been haphazard, late and frankly poorly thought-out, says Intellidex’s head of capital markets research, Peter Attard Montalto. Featured in Bloomberg Quint.

We expect a very sluggish recovery from the Covid-19 crisis. National Treasury’s stimulus package will run its course, but unemployment will rise and credit conditions tighten. Intellidex is featured in Business Tech

This is one of a series of columns that were produced for Moneyweb Investor in which Stuart Theobald explores the intersection of philosophy of science and finance. This followed an earlier series for Business Day Investors Monthly on the same theme. This column was first published in March 2017. 

Is doing good profitable? Are companies that prioritise having a positive social impact also ones that make the biggest returns for investors? It would be very comforting if the answer was “yes”. It would mean that the decision over what to invest in can be made both by thinking about which companies are good for society and which companies are good for their financial returns. We wouldn’t have to choose one or the other. Unfortunately, it’s not that easy.

There are many technical developments that have supported investors in accessing socially responsible investments (SRIs). The JSE operates a “Responsible Investment Index Series” with Top 30 and general indices that include companies that meet the JSE’s responsible investment “ground rules”. They were introduced in 2015 to replace the JSE’s previous SRI index that used a different methodology. The exchange-traded fund market has also various options that allow investors to choose investments that meet certain social objectives, such as Absa Capital’s “NewSA” ETF or Grindrod’s CoreShares “Green” ETF. Oddly, there is not currently an ETF based on the JSE’s responsible investment index. Perhaps that is because support for the ETFs have been minimal, with the NewSA commanding assets of R36.7m and the Green ETF R45.7m. To put that into context, the Satrix 40 ETF has assets of R6.7bn.

There is no doubt, however, that social investing is a growing trend. According to a US-based study, socially responsible investments now account for 20% of global capital markets, with $30-trillion of assets based on SRI principles. A lot depends, however, on how SRIs are determined. I imagined that the important issues are sustainability, so wouldn’t expect mining companies among constituents, or avoiding socially harmful products, so wouldn’t expect cigarette companies. Yet in the JSE’s SRI Top 30, you’ll find both Anglo American, together with its platinum and iron ore subsidiaries, and British American Tobacco. The index is assembled by FTSE Russell, created by rating companies on environmental, social and governance measures (ESG), ranging from support for biodiversity and respect for human rights, to anti-corruption procedures. A company which does little for the health of its customers, can score on various other measures such that it makes the grade. It should be clear, however, that when comparing SRI-based investments to non-SRI investments, there might not actually be much difference beyond the application of the label “SRI”.

The argument that social returns and financial returns are congruent usually works by claiming that socially responsible companies have better relationships with their stakeholders. As a result, customers are more loyal, staff more content, and regulators and politicians more conducive to supporting a positive environment in which that company can profit. They are also more sustainable, so don’t exhaust the resources necessary to maintain profitability. Such arguments put profitability as the prime objective, essentially claiming that social responsibility is good because it’s profitable, and not because it is good in its own right.

The evidence is ambiguous. There have been many studies globally that compare SRI funds with general funds, usually finding that there hasn’t been much difference (though there are exceptions which have found SRIs outperform). This is largely because there’s not actually much difference in the underlying companies held in SRI and non-SRI portfolios. One study[1] applied a higher bar to see what would happen to performance. It considered three different ESG ratings providers (not FTSE Russell used by the JSE, but similar) and portfolios of high rated companies with low rated ones in the US. So this eliminates the overlap between ESG and non-ESG, effectively dividing the universe into two separate halves (or smaller fractions by pushing up the cut off for the high group, and down the cut-off for the low group). Even then, the study found that there was no material difference between the high and low rated portfolios, and that it would be impossible to create a sustainably outperforming investment strategy as a result. This did differ depending on the particular ESG rating system that was used, however, so there may be an argument that ESG outperforms, provided only that the right ESG measure is used. This ambiguity can be seen in the JSE’s indices too – the old SRI index underperformed the Top 40 index in the three years to the switch in 2015, since when the new SRI index has slightly outperformed.

The impact on profitability of ESG factors is at least partly a function of policy. If governments introduce carbon taxes, for example, carbon intensive industries are going to become less profitable. So the performance of high-ESG scoring companies may be the result of administrative fiat rather than normal market forces. This works the other way around too – promises by president Donald Trump that he will slash environmental and other regulations on American business have caused a share price rally, as lower ESG-scoring companies look set to benefit.

Even if we accept that SRI investments don’t consistently outperform non-SRI investments, it also follows that they don’t underperform them. If we accept that investing is not only about profit, the lesson we can take away from that is that SRI investing does not come at a cost. That is still true when more stringent ESG criteria are applied. That alone suggests SRI investing is at least as good as non-SRI investing, and probably better for other reasons.

However, even on future profitability, it seems hard to resist that as climate change forces environmental concerns up the agenda, and the growing middle class in emerging markets demand increased health interventions, policy is going to systematically favour higher ESG scoring companies. Trump may be a very short term bump in the road toward that outcome. SRI investing comes at no cost, and is effectively an option on the upside that regulation may induce. The trick, however, will be to figure out just which companies are going to thrive in such an environment, and standard SRI measures may well fail to capture it. There may be no short cut other than examining companies case by case and exercising judgement about their sustainability in an environment of ever-strengthening ESG regulation.

[1] Gerhard Halbritter and Gregor Dorfleitner. 2015. The wages of social responsibility — where are they? A critical review of ESG investing. Review of Financial Economics. Volume 26, September 2015, Pages 25–35.

This is one of a series of columns that were produced for Moneyweb Investor in which Stuart Theobald explores the intersection of philosophy of science and finance. This followed an earlier series for Business Day Investors Monthly on the same theme. This column was first published in March 2016. 

Just what is economics and how does it work? Pretty much everyone who studies a commercial degree in South Africa has to do some economics along the way. Many arts students pick it up too. Often they take just enough to get a rough idea of some big ideas in economics – demand and supply, micro and macro. Those certainly provide useful insights into the way economies work, but how?

Just about everything presented in those elementary courses comes in the form of “models”. Here are a few that may jog your memory: the “model” of demand and supply, with downward sloping demand curves and upward sloping supply curves, showing that higher prices induce greater production while lower prices induce more purchasing until they find an equilibrium. The IS/LM model shows how interest rates and money supply affect aggregate output, a graphical representation of Keynes’ general theory. The older Ricardian model of international trade, illustrates how countries that trade benefit because of “comparative advantage” even if one country is more efficient in every respect than another. Then there is the Lewis model of development showing how urbanisation draws labour from the agricultural sector.

All of these models are the basis for lots of debate when it comes to making sense of the world. Some apply quite clearly, illuminating trends we can see in actual economies, while other situations appear to not match at all. But what is notable is that economics uses this method of arguing through models.

Economics is not the only science to reason in this way. Physics also has many models, ranging from the solar system to the “standard model” of particle physics that proposes that the world is ultimately made up of quarks, photons and other elementary particles.

Often models are criticised for being “unrealistic” but that seems to miss something important. Models are useful precisely because they are simplified representations of systems. The social world is messy, even more so than the physical world. Physics models are also simplified, for example, assuming points, vacuums and dimensionless planes, all things that don’t actually exist. Economics does something similar by assuming things like perfect information, zero transaction costs and rational decision makers, all things that don’t really exist either. London’s underground map is an unrealistic model too – it has little resemblance to the actual distance between stations, but provides a good tool to understand how to navigate through the system to get where you want to go.

(Incidentally, some neuroscientists have recently made quite provocative arguments that our cognition of the outside world is really just a model. They are argue that evolution is efficient – it wouldn’t give our brains the ability to comprehend “reality” if an abstract model that required less cognitive machinery would serve just as well in our efforts to survive and procreate. This might be why our brains find it so hard to comprehend some arguments in physics, like the simultaneous wave/particle nature of light and the 10 dimensional space time proposed by superstring theory. Maybe our mind’s model of the world is unrealistic. Luckily it is still useful.)

The Harvard economist Dani Rodrik, who was a key advisor to the South African government during the economic policy debates of the 1990s, has recently published a fascinating book exploring the nature of reasoning with models (called Economics Rules). He argues that economics progresses horizontally by widening its library of models rather than vertically by developing ever more accurate models. That library of models can sometimes flatly contradict each other, but in figuring out which one to apply we learn things about the economy we are studying.

Ever more accurate models of a particular economy would be ever more complex, perhaps as complex as the whole economy itself. But such a model would be quite useless to an economist wanting to understand other economies. The more detailed a model becomes to fit the particular, the less useful it is to understand the general. Simplified models may give us more insight to understand novel situations. And the more models we can draw on to study how they may apply to a situation, the more “truth” we may be able to discover.

When it comes to investing, we rely on economic models to help understand trends in the broader economy, but we have models to understand investment principles too. The “mean variance optimisation” model of the 1950s tells us why we should invest in a diverse portfolio. The Capital Asset Pricing Model of the 1960s tells us we should demand higher returns from riskier assets. But models are only a reasoning tool. We have to still do the hard work of understanding investment opportunities directly. Models can sometimes lead us astray, as the disastrous “value at risk” models did before the financial crisis, which allowed central bankers to think all was ok with the financial system. By understanding just how economics reasons with models, we may be better at avoiding the pitfalls.

This is one of a series of columns that were produced for Moneyweb Investor in which Stuart Theobald explores the intersection of philosophy of science and finance. This followed an earlier series for Business Day Investors Monthly on the same theme. This column was first published in June 2016.

The UK Brexit decision and the rise of Donald Trump and Bernie Sanders represent a new era of anti-establishment politics. The target is the conventional political order, rather than a desire for particular policies. For financial markets this new era is dangerous. The destructive economic consequences of political decisions seem never to have mattered less.

The Brexit decision, most clearly, represents a thorough thrashing of the UK’s political, social and economic elite. Most politicians, economists, academics, business leaders, sports stars and other celebrities had publicly called for a remain vote. Brexit is a sound slap in the face.

This shouldn’t be unfamiliar to South Africans. In many respects the Brexit decision was strongly reminiscent of the 2007 ANC Polokwane conference which appointed Jacob Zuma as president. That was a decision based on rejecting the established order around Thabo Mbeki, perceived as aloof and technocratic. It was an emotional response, rather than a positive endorsement of any policy position Zuma represented. And like Brexit, it took established media commentators by surprise. Then and now the lesson was that the media is generally within the establishment and myopic when it comes to understanding those outside of it.

What is driving this new ethos? There are some intriguing theories. One is that the technology of public opinion has changed. Until the rise of social media, experts held significant power over the public space. Newspaper editors and radio and television producers had to choose whose opinions to share, and the perception of expertise was what mattered, and of course, who the decision makers agreed with. But in the era of social media, the exclusive access of experts has largely dissolved.

Social media works to different rules. Research by the Oxford Internet Institute has found that messages that arouse emotions such as anger and irritation spread rapidly and allow groups to coalesce into echo chambers in which the emotional temperature is compounded, attracting more to join while producing disciples. Political campaigns that are emotionally charged will gain greater social media traction than those which focus on fact-based argument. That was in evidence too after the Brexit vote, with social media aflame with emotional recriminations on both sides.

But reducing this new dynamic to a matter of emotional salience is also dangerously simplistic and belittles those whose pain is being made visible. The anti-establishment backlash is also motivated by the perception that elites have profited at the expense of ordinary people. For the blue collar workers of America’s Midwest, watching the closure of factories that have provided employment to generations of their families, the status quo sucks. They may have little genuine identification with Trump, but the fact that the elites hate him matters. In much of England, the European Union has damaged the social status of ordinary workers, with the economy and wealth shifting to services, especially financial services, while manual jobs are increasingly taken by EU immigrants. Globalisation has led to structural changes in many economies that may leave them overall better off, but have left swathes of discontent.

On both sides of the Atlantic the financial crisis remains a clear example of elites ripping off ordinary people. Being told by economists and other business leaders that a decision is not in your own best interest is received as both patronising and disingenuous. Many Brexit voters were aware that an economic recession is a likely price of leaving the EU, but simply didn’t care if it meant delivering a bludgeon to the largely London-based elite. It has the politics of the hunger strike or self-immolation about it, a political tactic that only works if you follow through. In its self-harm, it also strongly communicates how much you feel about the need for change. It can be a rational negotiating tactic, reflecting the fact that if elites suffer, even a little, they have an incentive to use their power to improve the situation faced by those with little ability to change things themselves.

Can it work? For the elites, Brexit and Trump have made one thing clear: you cannot ignore the plight of those hurt by change. While that may well force policy decisions that are net negative from an economic perspective, such as protecting industries that have become fundamentally uncompetitive, there has to be an evenness to economic development that has been lost. This is not just about inequality, but about protecting the psychological well-being of the members of a nation, giving them a sense that they have a stake in it.

But it also may not work. Brexit is going to hurt everyone and the when the political cards settle, it is not clear that the working classes who voted to leave are going to be better represented, or their interests more important. In fact the likely outcome of Brexit, namely ongoing membership of the common market with the required free movement of people, but without the EU’s development support or labour protections, will be worse than ever.

The Brexit ship has sailed, but others may learn from the experience. One in particular, Hilary Clinton, needs to be a quick study. It should be obvious to her now that a run for the White House needs to credibly promise a better lot for the disaffected, one that finds genuine emotional attachment. Without that she too risks facing the bludgeon.

For investors it is a new world in which it is hard to be brave. Political stability, and the stability of institutions and the policy environment, is less dependable. Inevitably financial assets will pay the price.

This is one of a series of columns that were produced for Moneyweb Investor in which Stuart Theobald explores the intersection of philosophy of science and finance. This followed an earlier series for Business Day Investors Monthly on the same theme. This column was first published in July 2016.

South Africa has a culture of seeking consensus when developing social policy. According to this culture, legitimacy is achieved when apparently conflicted parties come together and agree. This strategy is dubious philosophically, but moreover compromises evidence-based policy formation. It is not at all clear whose agreement should matter, and their agreement doesn’t mean the policy is the correct one anyway.

The clearest manifestation of this culture is the National Economic Development and Labour Council (Nedlac), which describes itself as a “consensus-seeking body acting to reach agreement through negotiation and discussion”. In theory, all policy setting legislation must go through a process at Nedlac, although some, controversially, skip this step to avoid delays.

The view of history as being the result of forces in opposition to each other, itself has a long history. It is often attributed to the Eighteenth Century German philosopher Hegel, though it has roots going back to Socrates and Aristotle. Hegel thought true, or at least better, propositions came from clashing views, called the thesis and antithesis, leading to the synthesis. That idea profoundly influenced Karl Marx and his dialectical materialism, which is the idea that economies are organised according to an evolving process of competing interests, principally those of capital and labour.

The South African dialectical process is essentially Marxist. We tend to think of society as broken up into “business” and “labour” and sometimes “civil society”. We assume that they have coherent interests, and policy should find a way to serve all of them. So embedded has this way of looking at the world become, that we think these interest groups are coherent agents.

There are several problems with this approach to policy formation. Firstly, the opposing forces that we create for the dialectic are fictions, made up entities. Hegel’s first dialectic was actually between the family and the state. Our Marxist division of business and labour might be appropriate when the issue in question is one that affects all businesses in one way, and all workers in another way, but there are very few, if any, such issues on which to divide interests. In fact, most issues affect everyone differently, and the coherent groups that might be affected in the same way might be completely different in each case. We often ignore important groups like consumers or, tragically, the unemployed, because they don’t fit our model of the dialectic.

Business is not a coherent agent. Companies are an organisational form that people can use in order to achieve a range of objectives. Generally, companies are useful because they have a legal person separate to that of their founders. Any one person has many different interests and reducing them to a single perspective because they happen to own a part of a company is silly. The companies that people create are anyway often in conflict with each other, in competition to try and out-innovate and take market share. There is no coherent “person” that is business as a whole, and there are no people who are just business people. The same is also true of wage-earners.

Often, in order to satisfy the dialectical mode, various organisations are invented that are then claimed to represent “business”. Nedlac’s business faction consists of Business Unity South Africa, an entity that is dominated by large, established businesses. Their interests are certainly not identical with those of all people who happen to be involved in the organisational form.

But the biggest problem is that a dialectic at best serves already existing entities. Critical to economic development is stimulating the creation of new entities such as entrepreneurs. This is a real problem. The radical failure of the dialectical approach was on display with the last iteration of the Mineral and Petroleum Resources Development Act amendment bill. After much negotiation, it protected the investments of existing mining companies, which grudgingly acquiesced to the legislation via the Chamber of Mines, but created a hostile environment for the nascent gas sector. Gas companies, because they don’t yet exist, had no sway in the dialectic, and the result was something that would ensure they won’t come into existence. That bill has thankfully been sent back for revision. But that’s far from the only negative impact of our dialectical culture – some legislation drafters have taken to staking out extreme positions, thinking that is an appropriate start for a process of antithesis leading to sensible synthesis.

This points to a fundamental problem with the dialectical approach: it is not evidence-based. It seeks consensus and makes the fallacious assumption that if we all agree then it must be best policy. Of course, we often don’t know what’s in our own interest. Sometimes, a policy like removing trade barriers appears to be contrary to our interest because it lets in low cost competing goods, but in the long run stimulates efficiencies that make the whole economy better off. No currently existing entities seem able to take climate change seriously, because it is future generations that will be worst affected. Economies are like ecosystems in that there are various agents and types of entities that are in constant tension leading to an equilibrium. Policy can affect different entities differently and shift equilibria, and render the ecosystem healthy or unhealthy. Understanding and anticipating the impact of policy is a difficult scientific matter. Pitting groups of agents in that ecosystem against each other to seek some sort of consensus is no way to answer the question.

Mature democracies don’t have consensus seeking fora. The institutions of democracy, such as a parliament with ultimate policy authority, are considered enough. They have research units that have teams of social scientists investigating different policy options. They can run trials, study the experiences of other economies, and develop models and complex computer simulations. We went this way with the process behind the National Development Plan. This was perhaps the greatest demonstration we’ve had in our history that we can employ strategies other than the dialectic approach. Instead of trying to agree, a team of expert commissioners was assembled to consider all of the available evidence and then chart an optimal policy strategy. Crucially, as the commissioners themselves argued, that plan should evolve as we learn from the process of implementation, and we must invest in research as we go.

Negotiation is important, particularly when it is about deciding the fundamental objectives of social policy, such as reducing poverty and inequality. It is also important to communicate the reasoning behind policy interventions with the public, so that people remain informed and able to exercise their democratic wishes. But with respect to particular policies, it seldom helps to set imagined factions of society against each other and wait for them to find some consensus

This is one of a series of columns that were produced for Moneyweb Investor in which Stuart Theobald explores the intersection of philosophy of science and finance. This followed an earlier series for Business Day Investors Monthly on the same theme. This column was first published in April 2014.

In interacting with first time investors, I’m often astounded by what people think a share price represents. Some tell me a share trading at R10 must be twice as expensive as a share trading at R5. By that logic the cheapest share in the market is always going to be 1c. Others are sure the share price represents the quality of management or how well known the company is.

Lesson number one on share prices is always a very simple rule: share prices are never anything but the present value of discounted future cash flows. A share is nothing but the right to receive future cash flows, and the value of that share is nothing but the quantum of those cash flows, discounted for how certain we are about them.

Seeing things this way helps to eliminate a lot of behavioural biases we are prone to when thinking about shares. Buying decisions should have nothing to do with how familiar we are with the company brands (recognition heuristic), whether we already own or don’t own them (endowment effect), or whether we just happened to hear about them most recently (recall bias). It also means the recent performance of a share price is only indirectly about the future anticipated cash flows. It also helps eliminate another classic confusion: when a share price falls after paying out a dividend. It should fall by the amount of the dividend exactly, but simultaneously changing views of future cash flows can mean the actual share price change is slightly different.

Of course, putting things this way is deceptively simple. In fact it is very difficult to know what the future cash flows to a shareholder will be. It is also difficult to know how much to discount them by. If we know for sure that we will receive R100 in a year’s time, and our cost of capital is 10%, the present value is a simple calculation (100/1.10 = R90.90). But company cash flows are much harder to predict. So the discount rate has to reflect two things: the interest rate, including what it may be in future, and the probability that the expected cash flow will materialise. It requires knowing what revenue the company can generate, but also what the value of its assets are because they could also be a source of cash flow. The world is a complex place, and companies have many moving parts with differing levels of certainty about the future.

This difficulty in seeing the future, however, doesn’t mean we should content ourselves with bad forms of reasoning about shares instead. That is equivalent to embracing some new age cult because science hasn’t answered every question. Instead we should redouble our efforts to research companies and understand the risks to their cash flows and what their earning power is. Usually we do this from a portfolio perspective, so risk has to be considered in the context of what other holdings we have. When we hold a diverse portfolio, a law of large numbers starts to apply, which means that our predictions about cash flows tend to average out to the mean.

Ultimately we rely on financial information about companies, and other data about the markets and economies they operate in, in order to make these predictions. There are also fierce arguments about just which data is important. We tend to think that company profitability is what matters, yet major corporate frauds like Enron and, locally, Tigon, Alliance Mining and Blue Financial Services show how good profits can be reported while the company is actually in big trouble. Indeed, accounting standards and the discretion that management and auditors are able to exercise in some circumstances makes it difficult to know just how much we can rely on financial statements. Many analysts think the cash flow statement is a good way to escape these problems, but even this is subject to problems. For instance, most accounting standards require allow for the indirect method of composing cash flow statements, which means they take the income statement as a starting point and then add back non-cash items such as depreciation or tax provisions and changes in working capital. They are not directly generated by adding up the cash receipts and cash expenditures of the company. Two fund managers and academics from Highstreet Asset Management in Ontario recently came up with a new direct cash flow template that aims to eliminate the anomalies of indirect approaches, and have found that their template makes for a better predictor of share price performance than a standard cash flow template does.

Given these difficulties it is not surprising that some investors can be persuaded by purported short cuts to share price predictions, usually offered by software systems that come at a price. The old aphorism that a fool and his money are easily parted, comes to mind. To the extent that there are other factors involved in share price movements, the “animal spirits” that John Maynard Keynes once wrote about, there is just as much debate over whether the consequences are any more predictable. As I’ve written in this column before, trading systems based on the anticipated impact of human psychological biases don’t seem to outperform other strategies either. There is, unfortunately, no substitute for hard work in investing, except for one: just passively track the market and free ride on everyone else’s active decisions.

This is one of a series of columns that were produced for Moneyweb Investor in which Stuart Theobald explores the intersection of philosophy of science and finance. This followed an earlier series for Business Day Investors Monthly on the same theme. This column was first published in January 2016. 

We are used to separating out investment products in terms of their riskiness – equities at one end, bank-guaranteed products at the other. But the real problem that hit investors during the financial crisis was complexity. Investors simply didn’t understand how their products worked.

Some academics are now suggesting that complexity should be an additional dimension to how we think about financial products, alongside the traditional considerations of returns and risk. Risk in finance has, rightly or wrongly, come to be seen simply as volatility of returns, measured by standard deviation. So a risky product is one whose price jumps around more than others. Returns are, of course, difficult to forecast at the best of times, but that is the art of financial analysis. Complexity, though, refers to something different: the ability to link an event to the value of the financial instrument. The more complex a financial instrument, the more difficult it is to understand how changes in the world affect the value of that instrument.

In part, complexity is an inevitable feature of financial market development. Think of the JSE, which not too long ago consisted only of cash equities. Now you can get all manner of derivatives from futures to swaptions. Those can then be factored into investment portfolios alongside other instruments with different features and return sources like scrip lending. With such complexity a simple question like, “how will that interest rate change affect the value of my investment” becomes bewilderingly complex to answer. The same trend is clear in exchange-traded funds, which started as simple trackers of established, well understood indices, and now include “smart beta” products that are much more complex.

One practical observation is that herding effects tend to be more pronounced for complex products. Because it takes longer to work through the implications of new information, investment decision makers are more prone to follow the signals emerging from others’ behaviour. One apparent example is the financial crisis, when investors chose “sell” rather than wait to figure out the implications of events for their holdings. In this case, complexity feeds into riskiness because volatility will be amplified by herding, suggesting that complexity is effectively just a component of risk.

One response, at least in the case of retail investors, is to simply declare complex products to be unsuitable for them. Globally, regulators have been concerned about suitability – placing retail investors into products with the wrong risk and return profile for them. In South Africa that demon frequently rears its head in the corridors of the Financial Services Board, as clients complain about products sold by advisors chasing high commissions rather than their interests. But the problem of miss-selling doesn’t map neatly on to the problem of complexity. In fact, a complex product can be made very simple for retail clients. Consider a market-linked capital guaranteed investment product. These can be created by taking an interest free deposit, using the foregone interest to purchase an out-of-the-money call option on a market index. The investors’ capital is guaranteed, but if the market performs well they will get a market-linked return. A fairly simple product to understand, though a complex product in structure.

The problem is best understood as a one of decision making. The normal story is that investors try to estimate returns and understand the riskiness of an investment in the context of their portfolios, and aim to maximise returns and minimise risk. Complexity is really an information constraint – it factors into the cognitive load that is needed to make decisions. Seen that way, it is clear that some products which are complex in structure are not complex in the sense relevant to decisions – being able to understand the risk/return profile, such as market-linked capital guaranteed products. The type of complexity that matters is that which lies beyond our mental capabilities, and there are no ways to frame it so that the decisions are simple. Seen that way complexity is apparent in cases like hedge funds, where the actual investment strategy is a proprietary secret. In such cases, investors simply don’t know how events will affect performance.

One solution is to rate complexity by five factors: layers that affect payoffs; expansiveness of derivatives used; amenability to valuation by standard valuation techniques; number of scenarios that affect return outcomes; amount and simplicity of language in disclosures required to assess the profile of a financial product[1]. These can be mapped onto a scorecard that allows for a metric to complement risk and return estimates. So a highly complex product would have several layers of derivatives which are highly responsive to price changes of underlying assets, depend on complex non-traditional valuation factors (like weather swaps), and have many pages of verbose disclosures. Such complexity makes decision making very difficult.

For the average investor, then, it is helpful when looking at a product to ask just how complex it is. Applying a “complexity threshold” may well be a wise move if you’re going to keep a tight control over your investment portfolio and not end up following the herd when things change.

[1] Suggested by Benedict S.K. Koh, Francis Koh, David Lee Kuo Chuen, Lim Kian Guan, David Ng, Phoon Kok Fai. A Risk- and Complexity-Rating Framework for Investment Products, Financial Analysts Journal

November/December 2015 | Vol. 71 | No. 6

This is one of a series of columns that were produced for Moneyweb Investor in which Stuart Theobald explores the intersection of philosophy of science and finance. This followed an earlier series for Business Day Investors Monthly on the same theme. This column was first published in February 2017. 

In South Africa’s fractious political atmosphere, land ownership looms large. “Give back the land” is a common rallying call. Today’s calls are part and parcel of economic redress for Apartheid, which compounded colonial dispossession and led to today’s massive skew in economic resources. But as economies shift increasingly into services, the arguments over land have become increasingly out of touch with actual economic activity. Consider that 80% of US GDP is generated from services rather than activity in which land is a key input. The figure is 68% for the world at large. In South Africa, the figure has risen from 61.3% at the end of Apartheid to 67.8% in 2014. The trend is clear: increasingly, economic activity is in services rather than manufacturing, agriculture or resources extraction. It follows that in debates about redistribution, land is increasingly less important.

Land stands out as a critical issue in seismic political shifts throughout history. Certain historic examples, such as the American and French revolutions, led to democratic republics with a much fairer distribution of resources. However, other revolutions such as China’s Cultural Revolution or Hugo Chavez’s Bolivarian Revolution in Venezuela led to bad economic outcomes. So revolution and the dispossession of historic land owners is not a sufficient cause of better economic outcomes. The details of the post-revolutionary state matter, and clear property rights, including the right to trade that property, seem important. The tension we see in modern South Africa is how to create a state in which people can rely on their property rights in order to confidently invest in creating infrastructure and new assets, while simultaneously redressing the skewed distribution of resources inherited from our past.

Philosophers have long argued about property rights and the distribution of land. One group of arguments focuses on welfare effects, that we should ensure land is distributed in such a way that the maximum possible benefit is derived by society at large. Another group focuses on questions of justice, over who has a just claim to property. Questions about justice often focus on property rights. These are argued to be valid because they result from voluntary exchanges between individuals, while dispossession is always involuntary. These two arguments are hard to reconcile because they are about different things. Given the wording often used in SA, “give back” then land, it seems to be the question of justice that is paramount, and therefore it is an argument about restoring previously just property rights. Often one hears the response that general welfare, including food security, is better protected leaving the distribution as it is, or leaving it to the market to redistribute. Both of these points of view may be true, that land may be illegitimately owned, but that redistribution would be damaging to social welfare (Zimbabwe is often quoted). There are no easy answers to what should be done in such cases.

Then there is a third type of argument that focuses on inequality, that anything but an even distribution of land is unjust. Redistribution is usually about violating property rights rather than restoring them, so restitution and redistribution are inconsistent objectives. Redistributionist arguments, however, often point to illegitimate initial distributions as a way of weakening claims to property rights protections today, but usually see land’s only legitimate distribution being when it is held in common or held equally by everyone.

What is clear is that as the services component of the economy grows, the arguments over land will shift. Restitution arguments, while no less legitimate, may not be advanced so vigorously when land is a relatively less valuable resource compared to others available. The arguments that need a deeper rethink, however, are those about equality. For those arguments, land will become increasingly irrelevant as it shrinks as a proportion of economic assets, and some of the premises used historically will no longer apply. Appealing to an unjust initial distribution of land will not be a good argument for the redistribution of things that have nothing to do with land, such as the intellectual output of a computer programmer. While computers certainly require some natural resources, for computers must be made of some stuff, in the economics of computer programming, the value added is all in the intellectual property end of the chain rather than the input of physical resources. Even if those physical resources were obtained through some unjust expropriation of land, the claim over the computer programmer is shrinking as the value added accumulates in the non-physical sphere. This is true of all economic activity.

Egalitarians might then continue to insist on redistribution, but instead of land the focus will be on wealth. One of the arguments for redistribution of land will no longer be available, that it is based on an initial unjust distribution. The assumption was that the initial ownership was based on some form of wrong, that the owner was not the legitimate beneficiary of the asset. Some people are born gifted and able to use those gifts to create valuable computer programmes. No one seems to have been dispossessed in this, and in fact we are all benefitted by the fact that the computer programme exists when it otherwise might not have. There is, nevertheless, an argument that it is unfair that the computer programmer has these talents while I do not. By appealing to this unfairness, I might be able to demand some form of redistribution of his wealth to me. Something like this argument is used to explain why we should invest in providing facilities for the disabled, like parking bays or purpose-designed lifts to access public buildings. We accept that it is unfair that disabled people are less able to access these otherwise. We accept that equality of outcomes is important. Maybe this is also true in services-based economies where the inequality consists in the distribution of talent.

This, however, leads us into trouble. Philosophers from Marx to Kant accept that “self-ownership” is important, that we have an inviable right to our own bodies and minds. Demanding that I have a right to a portion of the computer programmer’s wealth seems to be a demand to his talents, a demand to exploit him for my benefit. Self-ownership is surely a stronger claim to ownership than any physical property right, over land or any other physical thing. There would be something unjust about dispossessing people of their talents, even if we accept that there is something unfair about the initial distribution of talents.

These are arguments are very hard to settle, which is why we tend to end up with awkward compromises, recognising that individuals should have property rights, but should also be taxed to support some level of equality. What should be clear, though, is that the evolution of our economies into services will shift these debates, particularly when it comes to the distribution of land and other natural resources. The premise that we all have an equal claim to natural resources will become increasingly irrelevant when natural resources are a shrinking proportion of the economic pie.

This is one of a series of columns that were produced for Moneyweb Investor in which Stuart Theobald explores the intersection of philosophy of science and finance. This followed an earlier series for Business Day Investors Monthly on the same theme. This column was first published in February 2016.

Treasury has been forced into another two year delay in its efforts to change the treatment of provident funds on retirement. The main issue is that savers will be restricted to a lump sum payment of one third of their savings at retirement, with the balance used to purchase an annuity. While purchasing annuities generally makes sense, government’s move has come at a cost to provident fund savers. Analysing why provides important insights on the nature of insurance, which even the wealthy can learn from.

Provident funds are the retirement vehicle of choice particularly for lower income workers, so unions, including Cosatu affiliates as well as Amcu and Numsa, have been fighting hard over the change. The problem for their members is that their provident funds serve as security for borrowing. Currently, provident savers can withdraw the full balance of their savings on retirement. So the drop from the full amount to one third dramatically reduces their ability to offer security to lenders.

I am sympathetic to the unions’ point. From the point of view of option theory, provident fund members are losing optionality that has a value, value they are currently effectively able to monetize by obtaining cheaper finance. While the change includes a carrot in that contributions are going to become tax deductible, most such savers are below the tax threshold anyway. So for them, the change is entirely negative (though in a questionable strategic move for government, the tax deduction is not subject to the two year delay, so that carrot is gone in future negotiations over annuitisation).

All insurance is irrational in a sense. The probability of you incurring the insured loss weighed up by the value of the loss is always lower than the premium you will be paying (imagine a R100 000 car you have a 10% chance of writing off – the premium would be more than R10 000 else the insurer would make no profit). Usually we make investment decisions on the basis of expected returns, by which we mean the probability weighted return discounted for the time value of money. For instance, we’d pay some amount less than R50 000 for a 50% chance of getting R100 000; if you had to pay more than R50 000 it would be an irrational investment, yet that is effectively what we are doing when we pay insurance premiums.

But just how important is it to buy an annuity? The answer is, very. An annuity is effectively a reverse life insurance policy: it pays out if you don’t die. That’s a flippant way of saying they are good for dealing with longevity risk – the risk that you will outlive your savings in retirement. An annuity continues paying you an income, no matter how long you live. Of course, the inverse is also true – if you die early, you effectively are denying the next generation an inheritance by using your savings to buy an annuity, a less plausible argument the unions have also made. Insurers will adjust the monthly annuity payments according to their perception of risk – if you are a smoker, for instance, you’ll get a bigger monthly cheque than if you are not.

Some insurance does actually provide us with economic value. An insurance company is able to pool risks in order to get portfolio benefits and has a large balance sheet so it can withstand surprises. We have small balance sheets and large assets are a big part of our wealth, so the volatility of cash flows around insurable events is much higher than for the insurance company. Some negative outcomes would wipe us out. It is best, then, to think of all insurance as against economic ruin rather than the risk of any particular insured thing. One obvious insight is that it never makes sense to insure small value losses. An extended warranty on a TV for instance, is an absolute waste of money. You will not be financially ruined if your TV, phone, fridge or other appliance dies. It also follows that the wealthier you are, the less insurance you need. At a certain point of base wealth it makes no sense to insure your own car for example (though 3rd party cover, subject to a high excess, may make sense because those losses could theoretically be infinite). Of course, this doesn’t apply if you know that you are a much higher risk than the average – though your insurer is likely to figure that out eventually.

It’s worth thinking about this in the context of your own investing behaviour. If you have a pool of investments, you could get a better expected return by cancelling insurance policies and redirecting the premiums to your portfolio, effectively self-insuring. If an insurable event happens, you can settle it from your portfolio, but the probabilities are in your favour, just as they are in any other investment decision. You get the profits your insurance company would be getting.

When you apply these lessons to longevity risk, the case to be insured becomes much clearer. You have a single risk, that of outliving your savings. Your ability to self-insure declines as your savings are disbursed in living costs. Unless your savings are very large, such that expenditure falls below what you could spend such that you could afford to live beyond the most optimistic life span, an annuity makes sense.

For low income retirees, it is unlikely that expenditure will be lower than what their savings can support. So the benefit to being insured through an annuity clearly increases as they age. It is one type of insurance that absolutely makes sense.

That is true whether government makes it law or not. But the law removes the option of using savings as loan security. Provident savers effectively sell that option to lenders in return for cheaper debt, but are repaid it when they settle the debt. No retiree should reach retirement with debt, but the ability to sell the option makes debt cheaper for them earlier in their lives. Government has delayed the new rules for two years. It needs to rethink them

This is one of a series of columns that were produced for Moneyweb Investor in which Stuart Theobald explores the intersection of philosophy of science and finance. This followed an earlier series for Business Day Investors Monthly on the same theme. This column was first published in August 2017. 

Since its launch in The Investor, this column has been a space to connect ideas from the academic world to the real world of investors. The topics have ranged from behavioural finance to studies of the impact of media on share prices. Of course, the academic world of finance was given a bloody nose by the financial crisis, and it is still trying to recover its reputation. But I believe it remains very important to continue interrogating ideas in academia from the perspective of practice and in my concluding column for this magazine, I want to provide something of a defence for academic finance.

The financial crisis was in part the result of the inappropriate use of ideas from academia. For example, academics had created several models to illustrate how financial returns are a function of risk. One important and typical one is the Capital Asset Pricing Model, which shows that particular instruments have to be priced such that the returns to owners justify the risk that the particular instrument brings to a portfolio. There is solid reasoning to the idea – it seems clear that no rational investor would want to own assets that increase the risk of a portfolio without also believing that it will increase the returns. The Capital Asset Pricing Model provides an elegant mathematical depiction of this relationship, by seeing risk as volatility in returns.

This is not unlike many other models in economics. The Hotelling Location Model, for instance, explains why companies tend to cluster in particular areas. It argues that consumers consider the price of goods and the transportation costs. Companies maximise profits by being just a little closer to the consumer than a competitor. Because every company thinks the same way, they tend to end up being in almost the same place. Usually this model is illustrated by imagining a single road. If there are four consumers spread equally along the road, who will go to whichever firm is nearest, each firm has an incentive to move closer to the other firm to eat up its market share, until both are in the middle of the length of road.

Now, no one thinks that the single road interpretation of the Hotelling Model, which also has some elegant mathematics, is a good formula for companies to use in deciding where to open their businesses, largely because cities don’t consist of single roads. It does, though, get at something important about the reason competitor retailers end up clustering together and may well support a rule of thumb for businesses in that they should open up where their competitors are. The lesson they provide is about a general tendency at work in the complex real world. In the same way, the Capital Asset Pricing Model also gets at something important about prices in financial markets, in that they must somehow reflect investors’ beliefs about the contribution to overall risks that they face. But just as real cities are not a single road, risk is not volatility. Volatility gets at something about the nature of risk, but it is not the whole story. It is useful shorthand, an abstraction, that makes the maths tractable. It helps the model do the academic job of explaining something about the messy world in an un-messy way.

The problem is the leap from academic models to practice where they become a calculating device to make decisions or to use in designing institutions. In those circumstances, the abstractness of the model is forgotten. We suddenly behave as if we live in a world where we have one-road cities and where volatility is a sufficient notion of risk. So we ended up using computers to calculate the volatility of complex portfolios held by banks and using those results to manage their risk. Fund managers used volatility and back-testing to convince themselves they have a low-risk strategy. We treat the model as if it is a faithful representation of the world, rather than an abstraction designed to illustrate something about it. We also use the model as a blue print for institutions, hardwiring them to deliver returns appropriate to the risk, when risk is measured as volatility. In doing that, the logic of the models in the academic world is turned into something quite different. In academia the models aim to fit the world, but in practice we were busy making the world fit the models. Of course, models are useful in practice too, but they are usually quite different. When we engineer new aircraft or bridges we test them in wind tunnels. We build prototypes and subject them to all kinds of stresses and strains to see how they’ll work. We often build in levels of redundancy so they’ll survive far worse than what we throw at them. We don’t take the abstract drawings and decide that because they are neat and tidy they’ll work in the real world.

We have in part learned this lesson. We now “stress test” banks in way that is vaguely analogous to testing scale models. We also sometimes run experiments on designs of new institutions to see how they’ll work, though it is difficult to get such experiments right. We still, however, confuse the logic of the academic setting. We fail to appreciate that its aim is to explain tendencies in the world, not to give us designs for how it should work. In that we remain at risk of getting lost in translation, of embracing academic work in finance but doing it in an entirely inappropriate way, leaving us with vulnerable institutions and weak risk management.

This is one of a series of columns that were produced for Moneyweb Investor in which Stuart Theobald explores the intersection of philosophy of science and finance. This followed an earlier series for Business Day Investors Monthly on the same theme. This column was first published in April 2017.

It’s become popular to think investors are irrational. A growing hoard of behavioural economists are employed to explain biases in investment decision making. Saying one should use classic financial theories like the Efficient Markets Hypothesis and the Capital Asset Pricing Model will often get you laughed out of the room.

Except that the reality is loads of investors do use them. And if you want to know what “the market” is “thinking” then you have to use them as well. This isn’t to say that those theories are fundamentally right, but only that if everyone else uses them, then you need to too. Else you won’t know what is causing prices to move.

The CAPM is a theoretical model that allows you to calculate what sort of return you should expect from a share. It considers the volatility of the share price compared to the market, and basically says that it if it’s more volatile than the market then you should get a higher return for investing in it. This is a kind of equilibrium condition – you wouldn’t invest in a stock if there was a less risky alternative with the same return, so returns have to adjust to match the risk. In the model, risk is treated as volatility. When people deride finance theories, the CAPM usually comes in for much abuse. It has been shown to be a poor predictor of market returns, with Nobel prize winner Eugene Fama championing the empirical challenge.

But, while CAPM may be weak at predicting long term price trends, it may be exactly the right way to decide what to invest in. If everyone believes it’s the best model then it becomes true that it’s the best model. It’s like the little book of second hard car prices that every dealer consults when figuring out what to offer you for your car. It makes it true that the price in the book is an accurate figure for what you’d get for it, because it was in the book in the first place. In the same way, the fact that everyone uses the CAPM makes it true that it is a good guide to the prices in the stock market. Of course, new information may come out later which ends up making it a bad or better-than-expected investment, but at the time the little book was the best price you had.

There have been various studies that asked financial managers how they make their investment decisions, and the CAPM has come up often as an answer. The answer from the behaviourists is that people may often say they’re being rational, but then make decisions that are quite different. The gap between peoples’ reported behaviour and actual behaviour is well documented. But a recent study of market prices provides strong evidence that investors really are using CAPM[1].

The authors studied cash flows in mutual funds. The idea is that investors into such funds decide which fund to put their money in on the basis of its relative performance. If it is outperforming the market it will attract inflows, but cash will walk out the door if it is underperforming. The useful thing about mutual funds is that cash flows don’t affect prices – the price of the fund is a function of the underlying investments, not the cash flows. That makes it feasible to isolate investor decisions from pricing data – they are technically independent, unlike in the case of normal stock prices which are affected by supply and demand. The key question to test for is whether investors choose funds not just on their over- or under performance in terms of returns, but also on the basis of their historic volatility and correlation with market returns as the CAPM would say they should. In other words do investors pick funds according to CAPM or some other theory?

The authors tested the CAPM against several other decision making models, including the famous Fama and French multifactor model. Turns out the CAPM explains investor behaviour better than any of the alternatives. They did not test any explicit behavioural rules. Most behavioural analysis explains exceptions rather than providing a comprehensive standalone decision rule so I’m not aware how one could test such a rule. But from what was tested – blindly going to whatever fund has the highest returns, using CAPM, or using Fama & French, the CAPM was the top performer. It only accounted for about 63% of the decision making so there may well be a better model out there, but so far we don’t know what it is.

I like studies like this because they demonstrate that we have to be careful with how persuaded we are by behavioural and other accounts of stock market returns. I often think that those who roundly dismiss rationality in financial markets are moving too quickly. CAPM may be a case of what sociologists call “performativity”, the idea that a theory makes itself true by directing how everyone should behave. Alternatively, it may be something that must be true if it is simply encapsulating the idea that investors rationally trade off risk and return. Whatever the reality is, investors would be wise to be well aware of the CAPM expected returns. Everyone else in the market is.

[1] Jonathan B. Berk and Jules H. van Binsbergen. “How Do Investors Compute the Discount Rate? They Use the CAPM”. Financial Analysts Journal Second Quarter 2017. Vol. 73. No. 2

This is one of a series of columns that were produced for Moneyweb Investor in which Stuart Theobald explores the intersection of philosophy of science and finance. This followed an earlier series for Business Day Investors Monthly on the same theme. This column was first published in April 2016. 

Financial analysts often talk of “intrinsic value” when it comes to analysing shares and other financial assets. But just what is that? I find it a rather perplexing notion. I know what the price of an asset is – an amount that someone will pay me for it or sell it to me for. I more or less also know how much I value an asset – so the subjective value that I place in it. But when we talk of “intrinsic value” we seem to mean something different to both these things, something that is a “real” feature of the asset, distinct from both my own subjective view of it and the market price.

The story goes that prices will converge to intrinsic value, because, we like to think, prices are rational and reflect all available information, at least in the long run. Prices can diverge for short periods, creating opportunities to buy or sell. Intrinsic value is often talked about by analysts who focus on the “fundamentals” and like to call themselves “value” investors. They try to ignore the price, which they consider to be the source of much distraction and panic, and focus on the fundamental operations of the company and come to a decision on what it’s worth.

I find this odd, because in one sense it is unscientific. Science is largely about empiricism (not entirely, but let’s not complicate things). Scientists disdain talk of invisible things that can’t be detected. Scientific claims should be about facts in the world that we can, at least in theory, go out and try to find evidence for. In the realm of human behaviour, economists have spent a century trying to shape their science in that same image. The famous American economist Paul Samuelson reviled speculation about what people were really thinking, arguing that the only thing that mattered was what they revealed through their behaviour. This could be measured; what’s in people’s heads can’t be. And when it comes to the value of assets, the only thing that reveals what people are thinking is the price.

Some analysts might respond that they are working off the basis of real facts, and then deduce the intrinsic value. This is true for certain kinds of assets. Some derivatives, like futures, are a mechanical function of the price of the underlying asset, the time to expiry, and the time value of money. While we often use the term “intrinsic value” for such calculations, it is misleading because such processes are just a mechanical extrapolation from the spot price of the underlying asset. This is based on a “no arbitrage” strategy, which works because we know that the price of the future must be such that it is impossible to earn risk-free profits. Such intrinsic values are, a philosopher might say, a priori, analytic facts. The prices are necessarily true, given the price of the reference asset.

Analysts may argue that this is basically what they are doing whenever they calculate intrinsic value. Instead of price, time to expiry and time value of money, they are determining cash flows and discounting these by a discount factor, or calculating a sum of the parts by looking at what prices are visible. But this is only a chimera of objectivity. Future cash flows are uncertain. The discount factor is meant to be a way of dealing with this – basically, that we should be compensated if the cash flows are uncertain. But this depends on a particular notion of uncertainty – that it is itself some measurable thing that can be determined. Well it isn’t. The best we can say of probabilities in this sense is subjective – the credence, or degree of belief, we have in the likelihood of a predicted outcome becoming true. This is an entirely different notion of risk than we typically have in finance – the volatility of prices, a measurable property of historic prices. When we are determining the probability of our estimated cash flows coming true, we are back at that subjective notion of value. It is that invisible thing inside our heads.

Some analysts try to avoid this repugnant conclusion by coming up with hard-wired models that mechanically take inputs and produce an output at the other end. There are many underlying strategies that can be employed – ones that rely on statistical regularities, others that rely on models of causes and mechanisms. However, again in such cases, the can is being kicked up the subjective road. The work is now being done at the level of calibrating the model and choosing the inputs.

What’s the point of all this navel gazing? Fundamentally (that word again) intrinsic value is not a very useful concept. When I see it being used in marketing literature for financial products, I have a flush of revulsion. It is a weasel term, used to obscure the fact that what is happening is nothing more than subjective judgement. It pretends to be a scientific notion but it cannot ever be that. It is ultimately based on the invisible beliefs of an analyst, as unscientific as one can get.

I’m all for wise judgement. But using the term “intrinsic” just obscures what’s really going on, serving as a cover for what in fact may be very unwise judgement indeed.

This is one of a series of columns that were produced for Moneyweb Investor in which Stuart Theobald explores the intersection of philosophy of science and finance. This followed an earlier series for Business Day Investors Monthly on the same theme. This column was first published in November 2015.

The rise of exchange-traded funds (ETFs) is a worldwide phenomenon. The first only came into existence in Canada in 1990, but 25 years later they are ubiquitous and now also encompass several other asset classes.  The JSE now sports 46 different ETFs and another 27 exchange-traded notes (which are just like ETFs but reference an index instead of replicating the index). Collectively they are worth R76bn, a drop in the ocean relative to the overall market capitalisation of R11-trillion, but more than doubt what they were four years ago and 10 times 10 years ago. Internationally, growth has been even more rapid, with $2.9-trillion now held by ETFs and ETNs worldwide in over 5 000 individual ETFs, according to research by the CFA Institute.

ETFs are a disruptive innovation that is affecting the business models of many operators in the financial markets. Chief among those will be actively managed funds such as the unit trusts have for decades been the mainstay of the South African retail savings industry. ETFs are both easier to use and cheaper, with costs generally all below 1% a year, while unit trusts are typically around 2%, with additional upfront costs.

ETFs themselves have emerged in response to two other developments in financial markets. First is the growth of indexation. ETFs are index funds in that they invest in all the securities held in an index. ETNs pay a return based on a reference index, but rather than invest in a portfolio, the returns are guaranteed by a large credit worthy institution. ETFs have tracking risk in that the buying and selling of securities in the index may not match the movement of that index perfectly, while ETNs are designed to track the reference index perfectly. The creation of indices has become increasingly sophisticated, allowing for the isolation of specific instruments and features such as high dividend paying stocks (like the Satrix Divi+), or stocks with good black empowerment status (Absa NewFunds NewSA).

The second is the intellectual foundation for ETFs, the efficient markets hypothesis. This is the idea that markets efficiently capture all new information into prices. It follows that actively picking and choosing stocks is a waste of time and effort – you don’t know anything more than the market does. The efficient markets hypothesis is an idea many like to lampoon. We know in fact that market prices can be irrational, depending on just how you define “irrational”. The problem is that we’re only good at determining that in hindsight. When it comes to picking stocks and how they perform in future active picking is time and again shown to be no better than simply following the market.

These two factors, the technology of indexing and the intellectual basis of the efficient markets hypothesis, have been the main drivers of the explosion of ETFs. Their low cost has also helped wide-spread adoption as has the fact that they are listed on an exchange, and therefore can be bought and sold all day with liquidity and live pricing, further advantages over their unit trust cousins.

In South Africa another important helping hand to the growth of ETFs (though not ETNs) has been National Treasury’s decision to allow them to qualify for tax-free savings accounts (TFSAs). Stockbrokers are among institutions that can offer TFSAs, but those using them can only invest in qualifying ETFs and not individual equities. This was Treasury’s way of preventing overly risky behaviour, but will also have the effect of normalising ETFs as an investment destination among the public at large, much how unit trusts have been.

There are a few drawbacks to ETFs. The indexes they are based on are by definition less flexible than an actively managed portfolio can be. So they may not suit some retail clients if, for example, they have substantial existing exposures that need to be diversified away through a carefully constructed portfolio. Other issues may arise if ETFs continue their rise to dominate the market. The biggest potential risk is that price discovery is blunted. For the efficient markets hypothesis to work, prices have to move in response to new information. That requires active decision makers buying and selling. ETFs are effectively getting a free ride on these active decisions. But there is a long way to go in growth before that would become a real problem and there should anyway be a self-correcting mechanism. As the proportion of ETFs grows, tracking error would grow as price volatility increases. ETFs effectively heard in following price movements, so amplifying them. That leads tracking error to become an invisible cost so the returns to active investing would increase again.

On the whole, ETFs are the financial innovation of our generation. They should be a critical part of your investing strategy.