Look through the windshield and into the rear-view mirror on each new setup. Every good analysis should validate current conditions through both forward (strength) oscillators and backward (momentum) indicators. Look ahead with popular oscillating tools, such as Relative Strength Index (RSI) and Stochastics, to identify overbought-oversold markets. Moving Averages and Moving Average Convergence-Divergence (MACD) provide the horsepower to look back and measure momentum change.

Particular indicators never answer all of the important questions for each trade of interest. As this limitation adversely affects performance, develop customized views of market activity that reflect and support unique strategies. Start by using what already exists. Build powerful math functions with pieces of popular tools already in existence. More importantly, learn to articulate exactly what new data will support evolving tactics. Identify the missing information first and then compose an original way to uncover it.

Study the construction and use of popular indicators in detail. The central data point invariably focuses on a very narrow subset of vital information. Calculations then pass through a sequence of smoothing averages, sometimes one embedded within the other. This final output plots on a X-Y axis with the points connected in sequence. You can learn how any indicator reacts by making small changes to the parameters and noticing the effects on the subsequent graph. Even tiny variations will emit very different results.

Core Elements of Popular Indicators:
1. ADX	Bar Range
2. Chaikin Oscillator	Volume
3. Commodity Channel Index	Price Deviation
4. Historical Volatility	Price Deviation
5. MACD Histogram	Price Moving Average
6. McClellan Oscillator	Daily Breadth
7. MoneyFlow	Up Closes vs. Down Closes
8. Rate of Change	Price
9. RSI	Up Closes vs. Down Closes
10. Stochastics	Bar Close vs. Bar Range

Build custom indicators in block components. First identify the need that the indicator will address. Then build this narrow function into a core data calculation. Test many variations before moving on to the next step. Once in place, find optimum smoothing averages through trial and error. Finally, examine the new indicator with a systems-testing program such as TradeStation. These heavy duty software programs take complex data sets and run them through numerous markets to measure how well they signal primary buy and sell zones.