Whichever method someone uses to trade the financial markets, whether it be mechanical, automated or discretionary, they will almost always be involved in making predictions about the future.

Usually those predictions are based on what has happened in the past whether it be from hard data of the fruits of experience. Normally past patterns are extrapolated into the future, as in: “X has tended to follow Y in the past therefore if X occurs again we know that there is a N% chance of Y following. “  In a sense to extrapolate from the past is a habit we get into because it is fundamental to our way of knowing the world. This approach above all gives us psychological assurance that the future will be like the past, e. g “I know the sun rose this morning and that it has risen every morning of my life, therefore there is an almost 100% chance of it rising tomorrow morning. . “  This approach may work for most physical phenomena but when it comes to the financial markets it does not work so well. For example, I once developed what I thought was a highly profitable strategy, which when back-tested made lots of money – but not long after I implemented it started to lose money. In the end I lost so much money I had to switch it off.

Here is another story: in the 1970s people made fortunes trading beans using a 10 day moving average but it wouldn’t be possible to do that now. Why? The simple answer is because the markets change – they lack the predictability of the sun, even though our wishful thinking would rather they didn’t.   Actually, in truth I have found that in financial markets it is often the case that the future will be the direct opposite of the past.  In fact the principle underlies already accepted notions of technical analysis, such as for example the idea that a strong thrust tends to follow the completion of a triangle pattern, or the idea of wave 2 and 4 alternating in Elliot wave analysis.   The starkest example I can find shown in the chart below of EUR/CHF.   During Phase A the market’s directional movement almost grinds to halt. This is then followed by Phase B during which the pair experiences one of the strongest periods of trending activity in its history. The two phases are extreme opposites.   The only way to predict the second phase would have been to look for the opposite of its governing characteristic of the first phase, which was lack of directionality.

Perhaps this might develop into an alternative method of analysis in which the analyst looks for the ‘governing characteristic’ of the market at the time and then proceeds to predict a future market in which the governing characteristic is the complete opposite.

The principle underling this new method of predicting market behaviour seems to make complete sense to me since it implies that extreme states alternate perhaps balancing each other out in the process, which is the way nature tends to work, seesawing in a constant flux in an effort to achieve balance.

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