Guessing and Predicting

There is little difference between guessing and predicting, ie

- guessing (what I don't know, but what somebody else may know)

- predicting (what has not taken place yet)

Giving people more information does not necessarily improve the decision-making. People will select information that confirms their point of view (confirmation bias) and will suffer from belief perseverance (the tendency not to change opinions we already have). Many experts are narrowly-focussed people who suffer from a combination of confirmation bias and belief perseverance.


"...The problem with experts is that they do not know what they do not know..."

Nassim Taleb, 2007

In fact, many experts are worse predictors than amateurs!!!!!

"...experts were lopsided: on the occasions when they are right, they attributed it to their depth of understanding and expertise; when wrong, it was either the situation that was to blame, since it was unusual, or, worse, they did not recognize that they were wrong and spun stories around it. They found it difficult to accept that their grasp is a little short......humans are the victims of an asymmetry in the perception of random events. We attribute our successes to our skills, and our failures to external events outside our control, namely their randomness..."

Nassim Taleb, 2007


"...statistically sophisticated or complex methods do not necessarily provide more accurate forecasts than simpler ones......the problem is that we focus on the rare occasions when these methods work and almost never on their far more numerous failures..."

Nassim Taleb, 2007

Linked with tunnel vision or 'tunnelling' is anchoring, ie

" lower your anxiety about uncertainty while producing a number, then you anchor onto it......use reference points in our heads.....start building beliefs around them because less mental effort is needed to compare an idea to a reference point than to evaluate it......we cannot work without a point of reference..."

Nassim Taleb, 2007

In summary, when looking at history we suffer from randomness (incomplete information) or "triplet of opacity", ie

"...a. an illusion of understanding, or how everyone thinks he knows what is going on in a world that is more complicated (or random) than he realizes;

b. the retrospective distortion, or how we can assess matters only after the fact, as if they were in a rearview mirror (history seems clearer and more organized in history books than in empirical reality); and

c. the over valuation of factual information and the handicap of authoritative and learned people, particularly when they create categories..."

Nassim Taleb, 2007

  • Many organisations need to review their mindsets and practices to help them survive in uncertain times. With an increasingly unpredictable, complicated and volatile environment, many accepted practices and core businesses (products and/or services) need reviewing. Beware of making decisions which are based on old assumptions, eg high barriers to entry, high transaction costs, few capable competitors, growing and increasingly affluent markets, restricted information flows.
  • Generally human beings have a tendency to embrace information that reinforces their pre-existing views, while challenging or rejecting information that questions these views.

Many established management tools, such as net present value, are built on a foundation that assumes certainty, ie forecasting likely cash flows and discounting them. In a volatile business environment, this thinking is not advisable

Our traditional approach to handling uncertainty and the resultant chaos is to introduce more rules and regulations !!!!!!! This does not work.

One way to handle uncertainty and unexpected events is to have a wide spread, or diversification, of your exposure to risk, ie a small percentage in risky and speculative ventures and the balance in less risky and more conservative activities.

Furthermore, you need to develop ways to work around the inherent unpredictability and even exploit it, ie handle the unknown unknowns. Some recommendations include

- make a distinction between positive and negative contingencies - negative ones can hit hard and hurt severely, eg a big budget movie that is a box office failure. Positive ones can involve losing small to gain big, eg a new, cheap book that has the potential to be a bestseller. You need to know where your ignorance lies and have a precise understanding of the structure of uncertainty.

- don't look for the precise - remember that chance favours the prepared, and invest in preparedness, not the prediction. Making predictions tends to narrow our focus and makes us more vulnerable to the events that we do not predict.

- be very opportunistic - strenuously chase opportunities and maximize exposure to them. This stresses the importance of networking.

- avoid people who make predictions and be wary of planners - remember that planners, especially governments and their public servants, are not good at making accurate predictions


"...I will never get to know the unknown since it is unknown. However, I can always guess how it might affect me, and I should base my decisions around that......the probability of a very rare event is not computable; the effect of an events on us is considerably easier to ascertain......we can have a clear idea of the consequences of an event, even if we do not know how likely it is to occur......this idea that in order to make a decision you need to focus on the consequences (what you can know) rather than the probability (which you cannot know) is an essential idea of uncertainty..."

Nassim Taleb, 2007

People like Warren Buffett (Barrie Dunstan, 2009) observed that the lesson learned from experience is that we learned nothing from experience!!!!!!! By the time the lessons are needed, a new generation has either forgotten them or not been taught them. Furthermore, this leads into the phenomenon "creeping determinism", ie

"...the sense that grows on us, in retrospect, that what has happened was actually inevitable - and the chief effect of creeping determinism...... is that it turns unexpected events into expected events..."

Malcolm Gladwell, 2009

The GFC has discredited most mathematical models that endeavour to forecast the future, especially those that used the activities of the past to predict the future and have not incorporated the psychological elements of human behaviour in decision-making. This is linked with the rational-irrational dichotomy and optimistic-pessimistic distinction. We tend to swing from irrational-pessimism, ie doom and gloom, to irrational-optimism, ie exuberance that encourages uncontrollable speculation and risk taking. Furthermore some of the assumptions are not valid, eg most macroeconomic frameworks have treated institutions, like Fannie Mae and Freddie Mac, as neutral. Based on what has happened in GFC, these institutional frameworks are far from neutral in their impact. Fannie Mae and Freddie Mac handle around 50 percent of all mortgages in the United States and they got into financial strife during the GFC.

Some more thoughts on the deficiencies of conventional, traditional financial modeling, ie

i) markets are not efficient despite the use of frameworks around the efficient market hypothesis (EMH), such as capital asset price model, the Black-Scholes option pricing model, modern risk management techniques, market-to-market accounting, market cap indexing, concept of shareholder value. Even the US Federal Reserve Bank fell under the spell of "markets know best".

ii) evaluating relative performance, via the use of, for example, alpha and beta (active return and market return), etc results in managers' tendency to over-diversify because of their fear of underperforming against the benchmark. The aim should be to maximize total returns after-tax and should be to maximize rather than to benchmark. The only way to produce a superior performance is to do something different

iii) this time it is different - remember that no one has the ability to predict the future with accuracy. Furthermore, a behavioural bias that we can influence the outcome of uncontrollable events, interpreting information in a way that supports self-interest and with a common focus on the short-term, will provide an illusion of control

iv) valuation matters - indicators such as price/earnings ratio are useful, eg buy stock when ratio is low, and sell when ratio is high. Need to keep emotions and sentiment away from decision-making as that swings from greed to fear

v) adopt a disciplinary approach - be patient and wait for the best time to buy rather than chasing every swing

vi) be careful of leverage - it can turn a good investment bad.

vii) complex mathematical models can hide the real risks - this results in obsession with needless complexity, ie

"... mathematics is......considered as producing precise and dependable results: but in the stockmarket the more elaborate and abstruse the mathematics, the more uncertain and speculation are the conclusions..."

Benjamin Graham as quoted by Barry Dunstan, 2010

viii) macro picture matters - need to understand macro and micro approaches

ix) cheap insurance - this is useful in a portfolio as it protects us from the known unknowns, such as inflation, bad monetary policy, poor government decisions, etc

x) most models are based on assumptions that are generally assumed to be fixed and stable. If these assumptions are taken to be random and/or changeable, most conventional models are of limited use. For example, the notion of competitive advantage, ie countries should focus on what they do best. Yet if commodity prices fluctuate, this competitive advantage might no longer be advantageous. Furthermore, the notion of competitive advantage is a basis for globalisation, ie efficiency, but in reality the systematic imperfections can distort this.

Another example is the attitude to debt. A positive attitude towards debt implies confidence in the future and a high degree of reliance on forecast. Yet

"...forecasting is harmful since people (especially governments) borrow in response to a forecast (or use the forecast as a cognitive excuse to borrow)...... borrowing makes you more vulnerable to forecast error..."

Nassin Taleb, 2010

Need to be careful of the concept of socialisation of losses and privatisation of gains. Alternatively, if a bank needs to be bailed out it should be nationalised; otherwise banks should be free, small and risk-bearing.

Furthermore, according to Taleb (2010), we

- need to make sure that any incentive or bonus system includes a disincentive for poor performance. Currently incentives system are asymmetrical, ie reward positive performance but no disincentives for poor performance.

- the complexity from globalisation and highly networked economic life needs to be countered by simplicity in financial products. Most complex financial products (eg hedging products) are not fully understood, and as a result should be banned

- governments should not need to restore confidence; the system should be robust enough to handle adverse rumours

- need to be careful of using leverage to handle our debt crisis as it is not a temporary problem; rather it is a structural one

- the market is not the final arbitrator

- need to look at converting debt into equity, marginalizing the economics and business school establishments, banning leverage buyouts, reducing the bonus system, reducing risk-taking amongst bankers, educating people to handle uncertainty and not allowing organisations to become too big to fail

The GFC highlighted the concept of some financial institution being 'too big to fail' (The Economist, 2013a), ie

- GFC started in USA (2008) with Lehman Bros going bankrupt & Barclays buying its US operations; Merrill Lynch absorbed by Bank of America; AIG & Citigroup bailed out, etc

- spreading to European economies, ie Greece, Spain, Ireland, Iceland, Italy, etc

- Citigroup accepted US$143 b loan losses; Deutsche Bank raised US$3.8 b

- bank revenue fell by 1/3 (about $100 b); staff pay fell; employment plunged; more complicated regulation, ie limit bonus payments & hold more capital

- by 2013, European banks were suffering, ie UBS, Credit Suisse; with US's JPMorgan Chase, Goldman Sachs & Citigroup dominating in Europe

Mother Nature is a complex system that has developed ways to handle the unknowns. It is a

"...webs of interdependence, non-linearities and a robust ecology (otherwise it would have blown up a long time ago)..."

Nassin Taleb, 2010

- it has developed backups, eg in the human body we have 2 eyes, 2 lungs, 2 kidneys, etc. These backups are insurance, eventhough there are obvious inefficiencies in costs and energy usage in maintaining these spare parts.

- does not like over-specialization as it limits evolution and weakens the system

- works against largeness. For example, if one removes a large land animal like an elephant, the whole eco-system does not collapse. Yet the fear that one large bank failure (Lehman Brothers) could bring down the entire system was obvious in 2008.

- robustness is important as we are unable to correct mistakes and eliminate randomness from social and economic life. The challenge is to confine this like Nature does.


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