Would you rather have someone giving you advice to be independent or disinterested? The Oxford English Dictionary (OED) definitions suggest some crossover but ultimately quite distinct meanings for the two words:


  1. not influenced by considerations of personal advantage
  2. having or feeling no interest in something


  1. free from outside control; not subject to another’s authority
  2. not depending on another for livelihood or subsistence
  3. capable of thinking or acting for oneself; not influenced by others; impartial
  4. not connected with another or with each other; separate; not depending on something else for strength or effectiveness; free-standing

I would opt for a disinterested adviser rather than an independent one every time. After all, you don’t want an adviser who is not connected with another or with each other. Those are normally the reported attributes of someone who has just done something terrible. And requiring your adviser to be neither subject to another’s authority nor depending on another for livelihood or subsistence probably means restricting yourself to people working on their own with no clients.

In opting for disinterested as a better adjective for advisers to shoot for, I am excluding the second definition here (some will argue that this is uninterested in any case, but 20% of the usage of the word disinterested is in the uninterested sense). Although many people giving advice will find their interest in advising anyone ever again for the rest of their lives waning at times, most of them return to being interested after a few days away from it, particularly if they have just enjoyed a holiday benefiting from the freely dispensed advice of their nearest and dearest.

However the definition of disinterested only takes us so far. You could be not influenced by considerations of personal advantage and yet still not be working in someone else’s best interests.

The Actuaries’ Code states that a conflict of interests arises if a member’s duty to act in the best interests of any client conflicts with:

a) the member’s own interests (ie you would not be disinterested by the OED definition); or

b) an interest of the member’s firm; or

c) the interests of other clients (you can’t provide full-blooded no-holds-barred advice to a client if you are also advising a company who is trying to buy them, sell them, merge with them or has different interests within the same organisation).

Consideration b) of this list then introduces a requirement on actuaries to take reasonable steps to ensure that they are aware of any relevant interest, including income, of their firm. And with this awareness comes the same responsibility to deal with any conflict arising as a result. However the Code is very much aimed at individual actuaries rather than their firms.

The Law Society’s practice note on conflicts of interest takes a similar line, recognising two types of conflicts of interest: own interest conflict (which includes the lawyer’s own interests and those of the lawyer’s firm) and client conflict. However it goes further by making it clear that the note applies to individuals and to firms collectively. Conflicts of interest are also regulated by the Solicitors Regulation Authority (SRA) within an overall framework of regulation that has two elements: firm-based requirements and individual requirements. It focuses on the practices of regulated entities as well as the conduct and competence of regulated individuals. This approach allows the SRA to take regulatory action against firms or individuals, or both, in appropriate cases.

All of this is fine as far as it goes, but I wonder if a process that relies on individuals effectively acting as investigators within their own firms to dig up instances where either the spirit or letter of some code is infringed is ever going to prevent deeply embedded practices on its own. It is very difficult to call time on arrangements which are making people money, particularly when you are dependent on the people making the money for your job.

Perhaps another way to go (or an additional one, as in this case I don’t think there is a conflict involved!) would be to recognise the meaning of the Latin root of the word conflict, which is conflictus, meaning contest. Wouldn’t it be helpful to individuals trying to avoid conflicts of interest if the companies they worked for operated a conflict of disinterest? Where firms competed with each other to demonstrate how disinterested they were. Where firms felt it gave them a competitive advantage to show how the only thing they had at stake in taking on a client or a project or any other piece of work was the agreed fee.

For a firm actively engaging in a conflict of disinterest, the individuals working for it wouldn’t have to knock down several doors to raise their concerns, they would find they were regularly being asked about the status of potential conflicts of interest, in case they in turn were in conflict with the firm’s client agreements and promotional material. The markets clients worked in would be regularly scanned for intelligence on deals in the pipeline and the firm’s own client lists would be scrutinised for potential implications.

So how could such a conflict of disinterest be brought about? By campaigning for it. If this is how we want business to be done we need to ask for it. If a change in public expectations of corporate tax management practices can lead to significant changes in those practices, the same could be achieved on conflicts of interest.

Because currently they are everywhere. At one end is the chimney sweep who brought a pile of soot down onto my new carpet and then turned to me and told me not to worry as he also ran a carpet cleaning business. At the other are the ratings agencies, paid by the firms they are rating, who both give credit ratings on financial instruments and advise individual firms on how to construct those financial instruments so as to score the highest possible ratings, which ultimately contributed significantly to the market crash and subsequent economic recession we have still not recovered from.

So declare a conflict of disinterest today and let’s start a movement.



There’s certainly a great deal of uncertainty about.

In Nate Silver’s book, The Signal and the Noise, there is a chapter on climate change (which has come in for some criticism – see Michael Mann’s blog on this) which contains a diagram on uncertainty supposedly sketched for him on a cocktail napkin by Gavin Schmidt. It occurred to me that this pattern of uncertainty at different timescales was more generally applicable (it describes very well, for instance, the different types of uncertainty in any projections of future mortality rates). In particular, I think it provides a good framework for considering the current arguments about economic growth, debt and austerity. Some of these arguments look to be at cross-purposes because they are focused on different timeframes.

uncertaintyIn the short term, looking less than 10 years ahead, initial condition uncertainty dominates. This means that in the short term we do not really understand what is currently going on (all our knowledge is to some extent historical) and trends which might seem obvious in a few years are anything but now. Politics operates in this sphere (long term thinking tends to look two parliaments ahead at most, ie 10 years). However, the market traders who by their activities move the markets and market indices on which we tend to base our forecasts and our economic policies are also working in the short term, the very short term (ie less than 3 months to close off a position and be able to compare your performance with your peers), even if they are trading in long term investments.

So both the politics and economics is very short term in its focus, and this is therefore where the debate about growth and austerity tends to be waged. The Austerians (which include the UK Government) claim to believe that debt deters growth, and that cutting spending in real terms is the only possible Plan A policy option. The Keynesians believe that, in a recession, and when interest rates cannot go any lower, demand can only be revived by Government spending. This argument is now well rehearsed, and is in my view shifting towards the Keynesians, but in the meantime austerian policies (with all the economic destruction they inevitably cause) continue in the UK.

However, there are other groups seemingly supportive of the UK Government’s position in this argument for altogether different reasons. Nassim Nicholas Taleb argues that high levels of debt increase an economy’s fragility to the inevitable large devastating economic events which will happen in the future and which we cannot predict in advance. He therefore dismisses the Keynesians as fragilistas, ie people who transfer more fragility onto the rest of us by their influence on policy. These concerns are focused on the structural uncertainty which is always with us and is difficult to reduce significantly. It is therefore important to reduce (or, if possible, reverse) your fragility to it.

At the longer term end are the groups who believe that we need to restrict future economic growth voluntarily before it is done for us, catastrophically rapidly, by a planet whose limits in many areas may now be very close to being reached. They are therefore implacably opposed to any policy which aims to promote economic growth. These concerns are focused where there are many possible future scenarios (ie scenario uncertainty), some of which involve apocalyptic levels of resource depletion and land degradation.

These different groups are tackling different problems. I do not believe that those concerned with the structural fragility of the economy really believe that the people paying for the restructure should be the disabled or those on minimum wage. Similarly, there is a big difference between encouraging people to consume less and move to more sustainable lifestyles and recalibrating down what is meant by a subsistence level of existence for those already there.

We do need to worry about too big to fail. Our economy houses too many institutions which appear to be too large to regulate effectively. We do need to reduce levels of debt when economic activity has returned to more normal levels. We will need to restructure our economy entirely for it to make long-term sense in a world where long term limits to growth seem inevitable. But none of these are our immediate concern. We need to save the economy first.

hammer and cushion

skin in the gameIn my previous post, I looked at some of the reasons why we are so useless at making economic predictions, and some of the ideas for what might be done about it. One of the key problems, raised by Nassim Nicholas Taleb most recently in his book Antifragile, is the absence of skin in the game, ie forecasters having something to lose if their forecasts are wildly off.

But what if all forecasters had to have something to lose before they were allowed to make forecasts? What if every IMF or OBR forecast came with a bill if it was seriously adrift? What if you knew whenever you read a forecast in a newspaper or on a television screen that the person making that forecast had invested something in their belief in their own forecast?

Betting on events dates back at least to the 16th century, but prediction markets (also known as predictive markets, information markets, decision markets, idea futures, event derivatives, or virtual markets) have developed most strongly over the last 25 years or so (the University of Iowa launched its first electronic market as an experiment in 1988). Intrade, which describes itself as the world’s leading prediction market, is now a little smaller than it was following the news just before Christmas last year that it would no longer let Americans trade on its site. It had been sued by the US regulator of the commodities derivative markets for breaking a commitment not to allow trading on the constituents of those markets.

A paper on prediction markets earlier this year called Prediction Markets for Economic Forecasting by Snowberg, Wolfers and Zitzewitz suggests there are 3 main types:

·         Winner takes all. If the event you have bet on happens you win. If not, you lose your stake. Intrade is this type of prediction market: you pay a proportion of £10 a share based on the average probability of the event happening (according to the market participants) and get £10 back if it happens, nothing if it doesn’t. The Iowa Electronic Market current offerings, on congressional elections and US federal monetary policy, are also winner takes all. The price of the bet at any time should reflect the market’s view of the probability of the event happening.

·         Index. The amount paid out is unknown but tied to the variable you are betting on, eg the number of seats won by a party in a particular parliamentary election, or the value of an index at close of business on a particular date. The price of the bet at any time should reflect the market’s view of the expected value of the outcome.

·         Spread betting. Most commonly found on sports betting sites, the amount bet and the amount paid out are fixed, but the event that leads to a pay out (eg number of goals scored in a match more than x) changes until the numbers of buys and sells match (a “buy” in this example is betting the number of goals will be above x, a “sell” is betting the number of goals will be below y, a number less than x. The spread, on which the betting site makes its money, is the difference between x and y. This could equally be applied to the values of an index at a particular date (eg Spreadex offer just such bets on several major share indices as well as currency exchange rates). Depending on the relationship between the pay out and the bet, the value of the spread points at any time should reflect the market’s view of a particular point in the probability distribution of the event, eg if the pay out is twice the bet, this would be the median (ie a 50% chance of the outcome being higher or lower).

As we saw in my previous post, currently economic predictions are largely blown off course by either:

  • Over-confidence in the information used to make them; or
  • The difficulty in standing out against a market which is making everyone a lot of money (buying has limited downside, selling limited upside); or (another possibility I haven’t mentioned before)
  • Bias in individual “expert” judgements, eg those with reputations at stake may want to keep their assumptions somewhere in the middle of the pack rather than standing out most of the time as this is less risky (hence the obsession with “benchmarking” assumptions in the actuarial world for instance).

Prediction markets can help with all of these problems:

  • Having to bet on your opinion should cause you to weigh the evidence backing it more carefully. Also, once a market is established and attracting a lot of bets, the range of evidence on which opinions are being based should expand. Prediction markets also appear to be quite difficult to manipulate or arbitrage.
  • Prediction markets can respond very rapidly to changes in the information available. As an example, within 25 minutes of Donald Rumsfeld’s former chief of staff tweeting about the death of Osama Bin Laden, the market view of the probability of this event on a prediction market rose from 7% to 99%.
  • Betting can take place anonymously. So, although the betting site knows who you are, no one else does, and the data from the voting therefore gets out into the public domain without any individual being accused of talking down a market or risking their reputation.

For these reasons, amongst others, forecast accuracy for established prediction markets might be expected to outperform that of professional forecasters. The paper of Wolfers et al suggests that this is the case.

There are still problems. The markets need to be popular to be much use for predictions, so the questions need to be interesting enough for mass participation. Secondly, a market could theoretically be undermined (although not necessarily to the detriment of its predictive ability) by traders with inside information. However, there are quite a few safeguards in place against this type of activity. Intrade, for instance, requires a photo ID and two proofs of address before it registers anyone to trade on their site. And Spreadex are regulated by the Financial Conduct Authority. A third problem is referred to as the “longshot bias”, which is observed on all types of betting markets. People tend to over-bet on events with long odds against them and under-bet on events which are fairly likely (which explains the narrowing of the odds as the starting gun approached on that horse you bet on just because of its name in the Grand National a couple of months ago). This is a problem of the winner takes all type of market, seemingly related to behavioural factors around the difference between how we view winning and losing, and it is difficult to see how it could be avoided completely. Care may need to be taken therefore when interpreting prediction markets on events which are seen as having fairly low probabilities.

But overall, prediction markets would seem to offer a way of significantly improving economic predictions, so why not make them compulsory for people who want to make such forecasts? By putting a cost on such predictions (a minimum bet could be set based on the size of the organisation making it), it would remove the casual forecasting we currently see too much of, and encourage people to review their beliefs rather more carefully. It would also ensure that the markets were popular enough to be effective. It may be that economic forecasting will always be far from perfect, but this seems a good place to start if we want, in Nate Silver’s words, to be “less and less and less wrong”.

A tax on economists? Not at all. But it might mean that we all have skin in the right game.

The main reason I set up this website was to draw more attention to the fact that we are fairly useless at making economic predictions. The graph I use as a logo is just one of many comparisons of economic projections with reality which could be shown to demonstrate just how useless. The problem is that there is then a bit of a void when we are looking for ways to support economic decision making. Nassim Nicholas Taleb and Nate Silver are, in different ways, exploring ways to fill this void.

Taleb, in his book Antifragile, links the fragility of the economic system, amongst other things, to an absence of “skin in the game”, ie something to lose if things do not go to plan. Something is fragile if it is vulnerable to volatility, robust if it is relatively unaffected by it, and antifragile if it profits from volatility. If decision makers gain an upside when things go right, but are effectively bailed out from the downside when they don’t by others who then suffer the downside instead, they will have no real incentive to be sufficiently careful about the decisions they take. This makes the chance of a downside for everyone else consequently greater. Taleb refers to people in this position, championing risky strategies (or, more often, strategies where the risks are not really known) without facing the risks personally, as “fragilistas”. He suggests instead a system of “nonpredictive decision making under uncertainty” on the basis that “it is far easier to figure out if something is fragile than to predict the occurrence of an event that may harm it”.

Silver, in his book The Signal and the Noise, suggests the main reason why economic predictions are routinely so awful, even when the forecasters are trying to be accurate rather than making a splash, is that the events forecasters are considering are often out of sample, ie the historical data they are considering to make their forecasts do not include the circumstances currently being faced, but that the forecasters are confident enough to make predictions despite this. This explains, for instance, the failure in the US to predict the housing crash (there had never been such a boom before), the failure of the ratings agencies to understand how risky mortgage-backed securities were (they were in new more complex forms) and the failure to predict that the housing market would take the rest of the economy down with it (much more trading betting on house price rises that did not materialise than had ever been seen before).

Silver cites the economist Terence Odean of the University of California at Berkeley, whose paper Do Investors Trade Too Much shows that equity traders trade excessively in the sense that their returns are, on average, reduced through trading (due to transaction costs), and suggests that this is partly due to overconfidence in the constant stream of information in the media drawing their attention from one possible model to another. This effect can be modelled to show that markets behave irrationally in the presence of overconfident decision making, even when decision-makers are otherwise completely rational.

However, when we are looking at the calls made by traders there are other forces at work that make things even worse. Silver’s book advances the theory that it is not so much an absence of skin in the game that leads traders to continue betting on rising markets when bubbles have started to develop, but skin in the wrong game (at least from the point of view of the rest of us fragile people). He gives the example of a trader looking a year ahead to make a call on whether the market will crash or not. If he buys and the market rises everyone is happy. If he buys and the market crashes, he will be in the same boat as everyone else and will probably keep his job if not his bonus. If he sells and the market crashes he will be seen as a genius, but the tangible rewards of this beyond his current position might not be life changing. However, if he sells and the market rises he may never work in the industry again.

For a trader who wants to keep his job and remain popular with his colleagues, selling therefore has limited upside and unlimited downside, to analyse it in a Talebian way. Buying on the other hand has potentially unlimited upside while the music is playing and limited downside when it stops. So these traders do have skin in the game, which keeps them buying even when they can see the iceberg approaching, and does not particularly reward accuracy in forecasting. It’s just a different game to the one the rest of us are playing.

For these amongst many other reasons, economic forecasting (Silver differentiates forecasting – meaning planning under conditions of uncertainty – from predicting – meaning calling the future correctly) is unlikely ever to be very accurate. But whereas Taleb believes that planning for the future must be nonpredictive to avoid making suckers of us all, Silver believes there may be some scope for improvement. This brings us to the idea of prediction markets and their ability to introduce some of the right skin in the right game, which I will discuss in my next post.

My post on 24 April suggested that the threat posed by EIOPA’s proposals for occupational pension schemes (or IORPs, as they call them) went well beyond increases to funding targets, specifically setting out tougher regulation on:

  • Governance requirements;
  • Fit and proper requirements of pension scheme trustees;
  • Risk management requirements; and
  • The establishment of own risk solvency assessments.

“Solvency II” type funding targets have now been postponed, but the other threats remain. So what is the true nature of this threat?

It is easy to portray “Europe” as some massive irresistible force which can only be opposed by an increasingly immovable UKIP-type object. However, occasionally the curtain gets whipped away to reveal, Wizard of Oz style, a few technocrats frantically pulling the levers up and down to maintain the illusion of unquestionable authority.

Gabriel Bernardino, the Wizard of EIOPA, certainly appears to be feeling the strain of maintaining this illusion. Last week he suggested that EIOPA needed more power and more money, some of which needed to come from levies on “the industry”, ie individual pension schemes.

Coincidentally, the Pensions Regulator has also issued a report on occupational pension scheme governance in the UK. There are 128 tables in its accompanying technical report but, picking out one or two statistics on each of the four of EIOPA’s focus areas I have highlighted, it suggests that meeting the tougher regulations on governance and risk management is likely to cause UK pension schemes considerable problems.

For instance, the 70% of small and over 50% (I’m assuming this, the Regulator’s summary of DB/Hybrid medium schemes’ responses only total to 90%) of medium schemes which have trustee meetings less frequently than once a quarter are unlikely to be seen by EIOPA as adequately providing “continuous operational governance”. As EIOPA’s advice recognises (the italics are mine): “many IORPs do not have truly continuous operational governance (e.g. IORP governing bodies that meet monthly or less frequently), so their operational characteristics fundamentally differ from insurance entities”. And the 3% or so of medium-sized schemes who admit to never having had a trustee meeting at all would I assume be seen as not providing operational governance at all.


Next up, if the requirements to establish that trustees are fit and proper persons to govern pension schemes were a worry, the revelation that 57% of small schemes and 41% of medium schemes have no training plan in place for its trustees will not help matters.


Meanwhile, it comes as a bit of a shock to those of us who thought that the Pensions Act 2004 did away with actuaries and other advisors acting as judge, jury and executioner of policy decisions for the pension schemes they represented, that 26% of small, 17% of medium and 18% of large schemes generally let their advisors take the lead on making decisions. Again this is not going to help trustees establish that they are fit and proper to govern their schemes.


It might be hoped that trustees could have a reasonable stab at meeting the risk management requirements of their schemes. However, a stubbornly persistent 13-15% of small and medium schemes (both defined benefit and defined contribution) who have at the very least some form of risk register review it less than once a year.


Finally, there are those who believe that the kicking of a new capital requirement for defined benefit pension schemes into the long European grass, if not the Eurasian Steppe, will just lead to the beefing up of the proposal of a pension scheme own risk solvency assessment along the same lines as insurers are currently developing, ie expecting each pension scheme to develop its own solvency target (which may introduce something equivalent to the holistic balance sheet by the back door) and a reasonably plausible account of how they expect to get there. The nearest thing we have to this in the UK at the moment is for those schemes who are developing a ‘flight path’ to buy out or ‘self-sufficiency’ (itself a concept which may not survive the Wizard of EIOPA). Over half of small and medium schemes have no such plan.


So much to be concerned about here, and none of it without cost. The Wizard may feel he needs help to wiggle levers to maintain an illusion of European managerial competence, but few people the other side of the curtain believe in this any longer. And, with the loss of this illusion, EIOPA’s ability to bully schemes into measures not previously thought necessary in the UK despite nearly 20 years of increasing domestic regulatory hyperactivity in this area recedes. If Bernardino can get the Pensions Regulator to implement all of this and get it to pay EIOPA for the privilege of being more intrusively regulated into the bargain, he will be a wizard indeed.