WHY TRADING SYSTEMS DON'T WORK

I am a retired market strategist, technical analyst and developer of trading systems. Kindly do not identify me and I will be happy to share my experience.

Long term market analysis shows that one-third of the time a market (regardless if the instrument is stocks, bonds, currencies or softs) will trend, one-third of the time the market will be affected by cycles, and one-third of the time is undecipherable (what geeks call noise or perhaps the market is undergoing a transitional phase) when the wise will not trade.

The most common failing of market trading systems is that they take a run of some data usually without much regard if the period is truly representative and attempt to fit some signals (like oscillators) which may make some profits on their model, say for instance a 60% ratio of wins to losses and hopefully that the net loss amounts do not exceed the net profits. When market characteristics change these systems fail. For about ten years there have been adaptive models available. These systems continually analyze the markets and the trading signals continually adapt to changing market conditions. This is based on the simple fact that the most recent inputs are the most valuable, not for instance a cycle or trend that happened a long time ago.

An analogy would be a missile defense system that spots a missile tracking in a straight line for a period, and then the missile starts to turn. The most recent data is clearly the most valuable info for predicting the intended target or for that matter the trajectory of a stock, bond, gold, currency, etc. John Ehlers developed MESA or Maximum Entropy Spectral Analysis which has been tested as giving the best long term results as a trading model and which is based on algorithms similar to those used in complex systems such missile defense and seismographic analysis. T

he best results have been in bonds and currencies, though other instruments do well. There is a similar system for very short term traders. A few words of advice: Moving averages define the trend and oscillators such as stochastic, RSI, and MACD as signals work best when used with the trend. On other words if the trend is up, sell signals based on oscillators do not work well, and buy signals work well. In a market that is affected by cycles and the m/a's are flat both buy and sell signals work.

Needless to say if after some trending and an overbought or oversold condition has developed and if the m/a's flatten and oscillators diverge with price, look for a change in trend. The market usually sends signals that the unwary ignore. A perfect oscillator trading signal can be defined as a half cycle. If for instance the 18 trading day cycle (nine days up and nine days down) in stocks is the most prevalent cycle, a 9 day oscillator is perfect for timing buys and sells.

However any attempt to stay in tune with the market helps. If your analysis is off by as much as 20% as to cycle length the trading signals will still be efficient. If this has not already confused you, there are cycles overlaid on each other within a trend that are visible in the charts to the naked eye with a little practice. For instance within an 18 day cycle there can be 4 to 5 day cycles that you can trade if you are shorter term oriented, best done with the trend. Pattern recognition such as Japanese Candlesticks used in conjunction with the above gives good results.

This article appeared in Urban Survival


				*FACTS THE BROKERS , AND THE FINANCIAL PRESS, WON'T TELL YOU!* *WHY TRADING SYSTEMS DON'T WORK*



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		I am a retired market strategist, technical analyst and developer of trading systems. Kindly do not identify me and I will be happy to share my experience. Long term market analysis shows that one-third of the time a market (regardless if the instrument is stocks, bonds, currencies or softs) will trend, one-third of the time the market will be affected by cycles, and one-third of the time is undecipherable (what geeks call noise or perhaps the market is undergoing a transitional phase) when the wise will not trade. The most common failing of market trading systems is that they take a run of some data usually without much regard if the period is truly representative and attempt to fit some signals (like oscillators) which may make some profits on their model, say for instance a 60% ratio of wins to losses and hopefully that the net loss amounts do not exceed the net profits. When market characteristics change these systems fail. For about ten years there have been adaptive models available. These systems continually analyze the markets and the trading signals continually adapt to changing market conditions. This is based on the simple fact that the most recent inputs are the most valuable, not for instance a cycle or trend that happened a long time ago. An analogy would be a missile defense system that spots a missile tracking in a straight line for a period, and then the missile starts to turn. The most recent data is clearly the most valuable info for predicting the intended target or for that matter the trajectory of a stock, bond, gold, currency, etc. John Ehlers developed MESA or Maximum Entropy Spectral Analysis which has been tested as giving the best long term results as a trading model and which is based on algorithms similar to those used in complex systems such missile defense and seismographic analysis. T he best results have been in bonds and currencies, though other instruments do well. There is a similar system for very short term traders. A few words of advice: Moving averages define the trend and oscillators such as stochastic, RSI, and MACD as signals work best when used with the trend. On other words if the trend is up, sell signals based on oscillators do not work well, and buy signals work well. In a market that is affected by cycles and the m/a's are flat both buy and sell signals work. Needless to say if after some trending and an overbought or oversold condition has developed and if the m/a's flatten and oscillators diverge with price, look for a change in trend. The market usually sends signals that the unwary ignore. A perfect oscillator trading signal can be defined as a half cycle. If for instance the 18 trading day cycle (nine days up and nine days down) in stocks is the most prevalent cycle, a 9 day oscillator is perfect for timing buys and sells. However any attempt to stay in tune with the market helps. If your analysis is off by as much as 20% as to cycle length the trading signals will still be efficient. If this has not already confused you, there are cycles overlaid on each other within a trend that are visible in the charts to the naked eye with a little practice. For instance within an 18 day cycle there can be 4 to 5 day cycles that you can trade if you are shorter term oriented, best done with the trend. Pattern recognition such as Japanese Candlesticks used in conjunction with the above gives good results. This article appeared in Urban Survival RETURN TO THE FACTS PAGE!



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