Dafni Serdari, Market Analyst, InterTrader

The first piece of advice usually given to an aspiring trader is the well-worn phrase “The trend is your friend”. Trend following traders identify one-way patterns and attempt to ride them for as long as possible. According to most seasoned veteran traders countertrend trading is irrational and it is usually associated with novice trader’s practices. One of the fiercest advocates of the countertrend strategy is the well-known trader, who coined the “Black Swan” term and introduced probabilistic thinking in the financial markets, Nicholas Nassim Taleb. The objective of the countertrend approach in a nutshell is to experience a large number of trades with relatively small losses in order to catch a change in the existing trend, based mainly on the idea that if a market moves in the opposite direction to what is largely expected, it could move significantly.

Most academic theories considered as modern finance assume symmetry in market returns and are based on the idea that investors are rational and markets are efficient. Investors may be perfectly rational when they examine charts and develop strategies on the weekend, but once they enter a trade things are quite different. Risk measurement based on academic theory defines risk as volatility, regardless of direction, and uses annualized standard deviation of historical returns. Standard deviation assumes that market returns conform to a normal bell-shaped distribution. Symmetry focused investors plot risk and return profiles in Gaussian normal distribution histograms, but market returns don’t fall into a symmetrical distribution and asymmetric return distributions can show asymmetry on both sides, both gains and losses. This type of investors may get excited after larger than usual gains, but it takes only a 50% decline to wipe out a 100% gain and a 50% loss requires 100% just to break even.

**Probability v. Expectation**

What makes a distribution asymmetric is the fact that the probabilities of each event and the magnitude of each outcome are not equal. Let’s examine the mathematics that lies behind that idea by means of a gambling example. We employ a strategy that has a 99.9% chance of making £1 (event A) and a 0.1% chance of losing £10.000 (event B). The probability of gain or loss in itself is meaningless, unless it is examined in connection with the magnitude of the outcome.

**Event Probability Outcome Expectation**

Event A: 99.9% +£1 £0,999

Event B: 0.1% -£10,000 -£10

Total -£9,001

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In this case my expectation is a loss of almost £9 and although odds favour event A, it is not such a good idea after all. The same mathematics applies to the financial markets as well. It is not about how likely an event is, but rather how much is made when the event actually happens. It seems that investors tend to get euphoric when they get it right, but what counts at the end of the day is not how many times you were right or wrong, but rather how much profit you made. (Nassim Nicholas Taleb, Fooled by Randomness, 2004:99)

**Psychology v. Statistics**

Psychologists have found evidence that people tend to get primarily affected by the occurrence or non-occurrence of a given event rather than its magnitude, i.e. a loss is firstly perceived as a loss and only later are the real implications considered. The same applies to profits. Considering now that according to psychologists an unpleasurable moment, i.e. the acceptance of a loss, takes two pleasurable moments, i.e. the realisation of a profit, to balance out, the individual would inherently tend to focus on minimizing the number of losses instead of optimizing the total performance.

Markets have always been marked by rare and unpredictable events and the question you should ask yourself is whether these events are fairly valued.