The Strategic Trader
Detailed Strategy Evaluation

Bollinger Bands

Simple Profitable Strategy: Part 1 (Design)

In this article series we are going to take what we have learned from RSI, MACD, Bollinger Bands, and Aroon Oscillator to build a simple yet profitable strategy. For validation, the strategy testing period will exclude 1/1/2000-6/1/2001 and 1/1/2011 – present. This will allow us to perform sanity checks in later phases to avoid curve fitting.

The goal is to build a strategy that is still profitable after taking out both slippage and commissions. Since most of our articles to date have dealt with the 5 minute time frame on ES, we will continue using those parameters.

The Setup:

In order to build a strategy, we have to have a place to start. For this strategy, we will start by combining the best aspects of each of the trading methods we have tested thus far. Starting with the most recent Aroon Oscillator method.  We identified AroonOscillator(8) crossing below -80 as possessing a slight edge, so we will put a stick in the ground here.

Initial Results (Pre commission/Slippage):

Profit: +$54,987
PF: 1.20
Max DD: -$4,662
Sharp: .58
Trades: 6925
Win %: 58.51%
Average Trade: +$7.94


This is a good start, but far from profitable once commissions and slippage are applied.

Before we move on to filtering out trades or tweaking the exits we need to add more potential “entry conditions”. In this step we go back through all the indicators that showed a slight edge and see if an optimized parameter combination for it improves overall performance.

The main purpose of this phase is to get as many entries as possible while still remaining over our “statically significant” thresholds. Each individual entry criteria does not need to remain above the threshold, but as a whole when used in an if/or combination the strategy needs to at least exceed on percent profitable or pure profit.

  1. Additional Aroon Oscillator Parameter Combinations
    • No additional combinations improved results significantly. AroonOscillator(27) <-99 helped, but not enough to justify inclusion
  2. Cross below Bollinger Lower Band
    • Bollinger(2.5,7) was added to the strategy
  3. MACD cross below signal line
    • MACD(2,12,4) was added to the strategy
  4. RSI Hidden Divergence
    • RSI Hidden Divergence 29,10,4 was added to the strategy
  5. RSI Hidden Divergence
    • RSI Hidden Divergence 14,22,6 was added to the strategy
  6. RSI Hidden Divergence
    • RSI Hidden Divergence 18,6,2 was added to the strategy
  7. Aroon Hidden Divergence
    • Aroon Hidden Divergence 12,17,4 was added to the strategy


Profit: +$81,925
PF: 1.15
Max DD: -$4,700
Sharp: .59
Trades: 13600
Win %: 57.32%
Average Trade: +$6.02

trading strategy development


Several key metrics decreased from the initial entry condition, but this is to be expected. Now we have a basic set of entry conditions providing over 13,000 trades. In the next several articles we will look at different ways of filtering out the non-performing trades, and implement an exit that makes more sense than a static 5 bar exit.

Eventually we will incorporate advanced concepts such as data mining and neural networks to improve the final product.



Trading Methods Using Bollinger Bands

Bollinger bands consist of 3 lines. A moving average in the middle, an upper band (avg + x standard deviations), and a lower band (avg – x standard deviations). Commonly the upper band is thought of as overbought territory and the lower band oversold. In this article we will explore several uses of Bollinger bands:

  1. Buying when the price crosses below the lower band
  2. Buying when the price crosses above the upper band
  3. Buying when the price crosses back above the lower band
  4. Buying when the price crosses back below the upper band

Test #1: Buy on cross below lower band

This method tested out well. There were a few parameter combinations that narrowly exceeded our profit and percent profitable targets set for 5 bar exits. The best parameter combination was 1.5 standard deviations and 4 for the lookback period. Here is the equity curve achieved:

Test 2: Buy on cross of upper band

This method did not yield a single profitable result.

Test 3: Buy when price crosses back above lower band

This method is similar to test #1 except we wait for confirmation of price turning around by crossing back above the lower band. Common sense would dictate this strategy should perform well. However, the actual results were closer to Test #2 than Test #1.

Test 4: Buy when price crosses back below the upper band

This strategy was unable to exceed our preset thresholds. Attached is the equity curve for the best parameter combination: 2.5 std, 24 period


We discovered that buying on oversold bollinger band conditions can be a viable strategy. However, more work is needed to fully exploit this potential edge.

Source Code:

Download Source



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