Why Most Indicators Will Never Work

Most indicators and trading systems have serious design flaws, they only work in perfect market conditions and on top of that for a very short time. After the perfect market conditions are over they lose money faster than you can imagine.

From my experiences as a trader and back testing, most indicators are 100% random. That is exactly why nobody is willing to show back test results except for me! As a former professional trader I do not know of a single trader who could make any indicator work and if they did they probably are broke now. Most professional traders trade from either a bar chart with volume or just a price quote and nothing more. That is it and there is a good reason why they do what they do. When I tested the following indicators all I got was random results that lose no matter if you buy or short the trade signal the trade is a loss.

  • ADX
  • ADXR
  • Bollinger Bands
  • Commodity Channel Index
  • DMI
  • Moving Averages
  • RSI
  • MFI
  • %R

After back testing for years I could not find a single indicator or any combination (for example ADX rising with Moving Averages crossover) that works the least or can give a consistent result. Every indicator out there falls into two categories: average (trend following) or oscillator (counter trend trading). All of the indicators out there are just different variations of a couple of main indicators designed by the same people years ago. My conclusion is they are all random and that is exactly what Nobel Prize Winning Economists have been saying for decades. Who are you going to trust on this? Self proclaimed chat room guru or a Nobel Prize Winning Economist?

Measuring Price and Trend Changes is a Science

Before I begin I need you the reader to understand that indicators and technical analysis need to be viewed as measuring tools. There is no magical formula, secret setup’s or Ancient Holy Grails of trading. There are traders who make millions of dollars a year and they do not use a single indicator. What they know how to do is measure price changes by feeling out normal price activity from unusual price changes. The truth is all measuring tool (scales, tape measures, etc….) require that any type of data or information you input IS the correct data if you want an accurate reading. If you measure the wrong data in the wrong way you can only expect the wrong answer.

The Average True Range Issue

GE verse GOOG Average True Range Comparison

GE verse GOOG Average True Range Comparison

The main problem with technical analysis today is nobody counts or considers the ATR or Average True Range of a bar chart. To start you need to understand what the Average True Range is and how it affects measuring price changes or trend.

The Average True Range or ATR is a Volatility measures tool. The formula is the High – Low and then it is averaged out to the length or input that is specified. All it does is tell you the average trading range of each bar. The ATR is an instruments natural trading range for a specific time frame.

What the Average True Range creates is a statistical analysis of the average range of each bar. It does not measure trend or direction in any way. It simply returns an average range of the bars on a chart. The ATR is specific to a instrument and each time frame is different. For example the ATR of GE stock on a 10 minute chart is going to be a lot less then GOOG stock at the same time frame. The picture on the right shows the ATR for GOOG to be in dollars ranges and for GE on the same time frame it is cents. The ATR creates a lot of issues for technical analysis and it also provides the solutions. The three main issues are:

  • Random Data
  • Signal Delay
  • Benchmark or Normal Bar Range Comparison

Random Data

If you focus on the closing price as most books and trading methods suggest then you are dealing with a piece of data that is always changing. Think about it! You are trying to measure a price that changes every time a trade is higher or lower than the previous price. That is insanity and it only took me about 15 years to figure it out. Think about this: Could you image trying to measure your weight on a scale while jumping around? That is what the closing price does. It moves around so much that you could never get a proper measurement! This all comes back to the back testing and consistency. You need a consistent result in order to be able to measure price changes. If the results are not consistent, then how would you expect to figure out how what needs to be done?

Signal Delay

Old Data Lagging Current Price

Do YOU Really Want to Make Trading Decisions Based on Old Data?

Signal delay happens because most indicators rely on an average over so many past bars or just the closing price alone. Since I figured out Shift Theory™ I have no idea why someone would want to make a trading decision based on an indicator that relies on prices from a 14 bar ago average. That is old news! Literally!

A proper price measurement needs to be in the moment. No system or indicator can predict the future but proper measurement can alert you to change. That is the best anyone could hope for from technical analysis! It is all about reacting to change! That is what traders do! Let’s compare the average closing price data to a car driving down the road.

Driver A can sees 2 cars behind in his rear view mirror. Driver A drives down a curvy road while looking in his mirror 2 cars behind him for directions. All of a sudden driver A comes to a crash from hitting a tree on a curve. Driver A was looking so far behind, that the curve in the road could not be seen and that driver could not react in time. That is what happens when you trade from old data!

Driver B can see just 5 feet in front of the car hood while driving. Driver B can navigate a curvy road because when the curve is hit driver B can react. It does not mean driver B knows how long the curve in the road is! Driver B just knows how to react like a trader because there was enough warning to do so!

The whole point about signal delay is you cannot react to old news and that is what most technical analysis wants you to believe. Now combine the signal delay with random data and you have a recipe for failure!

Benchmark or Normal Bar Range Comparison

Moving Average False Signals

Moving Average False Signals

The biggest issue and solution the ATR creates is every bar on a chart has a open, high, low, and close. The closing price is what creates all of the other data points. So that makes the closing price a moving target that is difficult to measure. This comes back to the random data because the closing price created all of the other points of data. The opening price is just a carryover from the previous bars close but it can serve as a good reference point for some indicators.

Back to the main data points of the ATR, the high and the low. The high and the low are what define the ATR and they also define what the average buyer and seller cycle go through during that time frame. Everything in between the high and low of a bar is noise. What the high and low do create is a perfect benchmark to gauge price changes against. There are a couple of undeniable mathematical facts about price changes and trend and they are:

  • Price cannot go high unless it makes a new high.
  • Price cannot go lower unless they make a new low.
  • Choppy or sideways markets rarely make new highs or lows.

Most indicators do not measure the difference between each bars highs or lows. The main problem that the ATR creates is also the solution for a benchmark that Shift Theory Ratios™ rely on. Unless you have benchmarks to compare the current data to then they is no way to measure change. The ATR helps separate noise from unusual price changes by relying on mathematical facts such as a price cannot go higher unless it makes a new high. Think about this. Let’s say you are buying a car and you think you got a great deal. How do you know you really got a good deal. The answer is you need to know what the other people paid for that same car and that is what the ATR lets you do. The problem with most technical analysis techniques is they do not consider the high and low of every bar compared to the previous bar and that results in random measurements because you have noting to compare too.

The Conclusion

Until main stream Wall St considers the ATR, technical analysis will always be random and nothing more than snake oil for sale. Every professional trader that I know does not use traditional technical analysis and that includes me. Success in trading comes from being able to recognize a certain type of behavior in the price. It is no different than a cop looking at the people passing by and determining who is just doing their every day thing and who is up to no good. As traders we are all looking for aggressive buyers, sellers and times to just act like market makers.

 

HYPOTHETICAL PERFORMANCE RESULTS HAVE MANY INHERENT LIMITATIONS, SOME OF WHICH ARE DESCRIBED BELOW. NO REPRESENTATION IS BEING MADE THAT ANY ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFITS OR LOSSES SIMILAR TO THOSE SHOWN. IN FACT, THERE ARE FREQUENTLY SHARP DIFFERENCES BETWEEN HYPOTHETICAL PERFORMANCE RESULTS AND THE ACTUAL RESULTS SUBSEQUENTLY ACHIEVED BY ANY PARTICULAR TRADING PROGRAM.

ONE OF THE LIMITATIONS OF HYPOTHETICAL PERFORMANCE RESULTS IS THAT THEY ARE GENERALLY PREPARED WITH THE BENEFIT OF HINDSIGHT. IN ADDITION, HYPOTHETICAL TRADING DOES NOT INVOLVE FINANCIAL RISK, AND NO HYPOTHETICAL TRADING RECORD CAN COMPLETELY ACCOUNT FOR THE IMPACT OF FINANCIAL RISK IN ACTUAL TRADING. FOR EXAMPLE, THE ABILITY TO WITHSTAND LOSSES OR TO ADHERE TO A PARTICULAR TRADING PROGRAM IN SPITE OF TRADING LOSSES ARE MATERIAL POINTS WHICH CAN ALSO ADVERSELY AFFECT ACTUAL TRADING RESULTS. THERE ARE NUMEROUS OTHER FACTORS RELATED TO THE MARKETS IN GENERAL OR TO THE IMPLEMENTATION OF ANY SPECIFIC TRADING PROGRAM WHICH CANNOT BE FULLY ACCOUNTED FOR IN THE PREPARATION OF HYPOTHETICAL PERFORMANCE RESULTS AND ALL OF WHICH CAN ADVERSELY AFFECT ACTUAL TRADING RESULTS.