Some thoughts on the inherent limitations in trying to outguess or beat the market

Active investing has a lot to do with all types of ‘predictions & forecasts’-especially when the objective is to beat the market (index).

For example stock pickers have to ‘predict’ and therefore identify a couple of stocks with higher future rates of return...this has to be done from among the large number of companies typically listed on a stock exchange...and do this in competition with numerous contemporaries attempting a similar exercise.

Similarly manager pickers have to predict (from a large pool) the few managers who they believe will pick stocks with a higher rate of return-and in the process beat the market and other managers (also) attempting a similar exercise.

Predictions can extend to attempting market timing i.e. a great time to enter the market and then exit it.

Forecasts in active investing normally also extend to macro-economic domain such as predicting interest rates, government action affecting an economy, oil prices, and global cues and so on and so forth.

This narrows down the debate to understanding the difference between ‘physical / natural’ sciences and ‘social’ sciences.

Natural sciences such as physics, astronomy, medicine, engineering, chemistry etc deal with the natural phenomena found in our universe. On the other hand social sciences are the study of human interaction as individuals and as groups-for example their choices, preferences and so on.

‘Prediction’ is easier in natural sciences, e.g. an engineer can use a mathematical model to predict the stresses in a concrete structure such as a dam or a bridge or a skyscraper...similarly an aeronautical engineer can predict the impact of natural forces on an aircraft in flight via simulations in a wind tunnel or on a computer.

Likewise, medical sciences such as cardiology are moving towards ‘predicting’ heart attacks before they can occur in (otherwise) perfectly healthy people. For example, huge advances in cardiac imaging technology can pick up heart blockages in infancy and with a high level of accuracy-thereby the risk of a future stroke can be ‘actively predicted’ beforehand and necessary lifestyle changes be suggested to a possible future victim i.e. ‘in advance.’

Prediction is therefore easier with physical phenomena because they work according to a predictable past pattern and in accordance with natural laws.

Such ‘prediction’ luxuries may not be available to social sciences e.g. economics and investments.

This is because it involves human interaction, emotions, choices, perception & behaviour-which are relatively difficult to ‘forecast and predict’ (in advance) by using mathematical models or commonly tools such as charts (using past price patterns) or discounted cash flow models and so on! In other words past data can be of little predictive value going forward.

For example, in the stock markets it is rather difficult to arrive at the fair price of a security by making use of the usual tools of active management. Price at any given point in time is a reflection of what thousands and thousands of market participants are ‘thinking’-it is an estimate of what people collectively believe & perceive!

Likewise it is extremely difficult to figure out short-term market movements by using past patterns. Mr Market is almost like a human being whose thoughts change very often and hence making predictions & forecasts is tedious.

Price movements are impacted by ‘news’ or arrival of ‘fresh’ information and how numerous market participants respond / react to it (almost instantly)...I cannot think of any tool available that can accurately ‘predict’ this phenomena in advance. Fresh information could be anything-right from company specific to something like economic crises in Greece.

Arrival of fresh information / news is ‘random’ causing a random walk in prices.

Even if we assume the market is making mistakes-those errors, if any, will be accurately ‘predicted’ in hindsight.

Let me reproduce, as an example, two predictions that went horribly wrong and were highlighted in the book Black Swan, the words from the book are,

Thomas Watson, the founder of IBM, once predicted that there would be no need for more than a just handful of computers.

...Likewise, we are not spending long weekends in space stations as was universally predicted three decades ago. In an example of corporate arrogance, after the first moon landing the now defunct Pan Am took advance bookings for round-trips between earth & the moon.

Nice prediction, except the company failed to foresee that it would be out of business not long after.

The above examples represent human choices & behaviour-not easy to predict or foresee-unlike engineering problems that are easier to ‘predict’ and solve by using mathematical equations.  

Investors, often confuse between ‘natural & social’ sciences-what works for the former may not work in the latter.

We (often) erroneously believe there are ready made tools, also available in ‘social sciences’-which when used by experts can help us (easily) in beating the market-by predicting (in advance) mispricing that maybe caused due to human behaviour, choices and interaction!

Hence, the market price is closest to what we call as ‘fair estimate’ of a security’s value. Passive indexing makes no attempt to outguess market prices.

It is important to understand the inherent limitations in attempting to outguess the market (consistently)-let me end with some words from the book Black Swan,

What is surprising is not the magnitude of our forecast errors, but our absence of awareness of it.