“History doesn’t repeat itself but it does rhyme. — Mark Twain”
Mark Twain could have been a trader – i.e. if he had followed his own advice and not become an investor in new inventions and technology, which bankrupted him.
Successful market participants believe not in Efficient-Market Hypothesis (EMH) but in their abilities to profit from moving market. They find and exploit ‘the edge’ to beat the market. Their edge is the anti-thesis of EMH and Random Walk Theory.
For an ‘edge’ to consistently generate profits means that it should produce demonstrably predictive outcomes with high probabilities. This can only happen if history gives sufficient clues to be projected or in another words it needs to rhyme if not repeat.
A close observation of stock and other markets’ performances over an extended period convinces us that this is the case. Existence of many successful investors and traders who have consistently produced profits for many years also augments this hypothesis.
Prices of all assets are primarily driven by fundamental factors. Other factors – technical, psychological, market sentiments – are derivatives of fundamental influences in some shape or form. Seasonal analysis also has its roots in fundamental causes. Consider retail stocks, a sector heavily influenced by the consumer buying pattern, which in turn is swayed by holidays, weather, college/school calendars etc. This means that the retail demand depends upon many seasonal activities and, by direct association, so do sector’s sales, profits and stock prices. Similarly seasonal-trend cases can be made for agricultural commodities and stocks, which depend upon harvesting seasons. Capital investment and expenses are driven by financial calendars and weather drives many other industries too.
The bottom line is that seasonal causes do impact an asset class’ fundamental landscape. It does not mean that they have identical affect every time they occur but that the forces swaying fundamentals do appear regularly albeit with differing intensity and magnitude.
During certain periods and for certain asset classes, this produces opportunities that could be traded to generate significant profits with high degree of predictability.
By employing a variety of technical analysis and risk management techniques, the overall risk exposure for these trades could be maintained at a low level relative to the overall market risk. Such a system generates a positive expectancy, on a risk-adjusted basis, that is substantially better than the broader market performance.
We have analyzed the seasonality tendencies of markets to identify criteria for reliable, profitable trades from more risky, less reliable trades. By employing a variety of technical analysis and risk management techniques, we maintain the overall risk exposure of these trades at a low level relative to the overall market risk. Over a considerable period, our system has generated a positive expectancy, on a risk-adjusted basis, that is substantially better than the broader market performance.
Seasonal propensities of asset classes act only as a reference guide as we do not take position solely on the seasonality. Other criteria that we include to identify potentially profitable trades include technical patterns, fundamental influences, market sentiments and general market outlook.
Caveat Emptor: The trading results do suffer from the common problems that pester many quantitatively derived trading systems – namely the system is back tested using the same data that was used to develop the system criteria. However, we have taken pains to cross validate results and tested the system also on securities not used to develop the criteria. These securities are not identical but related, so some shavings of the aforementioned problem do remain. Hence, to realize the expected results in the future, one has to believe that future price fluctuations will resemble past gyrations.