## 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.

**Additional Aroon Oscillator Parameter Combinations**- No additional combinations improved results significantly. AroonOscillator(27) <-99 helped, but not enough to justify inclusion

**Cross below Bollinger Lower Band**- Bollinger(2.5,7) was added to the strategy

**MACD cross below signal line**- MACD(2,12,4) was added to the strategy

**RSI Hidden Divergence**- RSI Hidden Divergence 29,10,4 was added to the strategy

**RSI Hidden Divergence**- RSI Hidden Divergence 14,22,6 was added to the strategy

**RSI Hidden Divergence**- RSI Hidden Divergence 18,6,2 was added to the strategy

**Aroon Hidden Divergence**- Aroon Hidden Divergence 12,17,4 was added to the strategy

#### Results:

**Profit:** +$81,925

**PF:** 1.15

**Max DD:** -$4,700

**Sharp:** .59

**Trades:** 13600

**Win %**: 57.32%

**Average Trade:** +$6.02

#### Summary:

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.

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## RSI Part 9: Risk/Reward

Before temporarily moving away from RSI, I want to evaluate each method one more time using the risk/reward test discussed in this article: Risk/Reward Testing

**Crossing Above a Threshold:**

Surprisingly many parameter combinations performed very well. Unfortunately, no combinations were able to exceed our desired targets.

**Crossing Below a Threshold:**

This method performed horrible based on this metric. This is what I thought might happen, and the reason I wanted to perform this test. Buying when oversold is a high percentage play if your nimble. But from a risk/reward standpoint its a hard strategy to trade.

**Normal Divergence:**

This method still did not contain any tradeable edge. Performs very poorly.

**Hidden Divergence:**

No combination was able to exceed our lofty targets, however several combinations missed by only fractions of a percent. This further underscores the fact that RSI Hidden Divergence contains a tradeable edge.

**Related Posts:**

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## RSI Part 8 – Short Strategies

In previous articles we have identified two methods that provide an edge on the long side (Bullish Hidden Divergence and Buying on oversold conditions). Before reading this article, its recommended you read the following two articles:

1. Buying on “Bullish Hidden Divergence

2. Buying when oversold

For this article we tested the same two concepts to see if they also had an edge when traded from the short side. The first method we looked at was “Bearish Hidden Divergence”. The testing strategy was very similar to the one used in “Bullish Hidden Divergence”. It was immediately apparent that this strategy had a significant edge just like its bullish counterpart.

Several combinations easily exceeded our target values when predicting 3 bars into the future. However, when predicting 5 bars into the future the results were not quite as clear. Several strategies came extremely close, but failed to exceed our targets. In some cases missing by fractions. Because this strategy easily blew past our targets for 3 bars into the future, we know the general concept has an edge. Its likely the edge degrades fast when trading short though. When we explore exit strategies in a future article we will need to take this into account. Here is a screenshot from one of the 3 bar combinations:

Next we tested selling short when RSI crosses above a given threshold (overbought). This strategy also clearly contains a statistical edge. Many combinations for both 3 and 5 bars into the future were profitable. Here is an example of one such combination:

The next step will be to create a “combination” strategy using several parameter combinations each exhibiting a statistical edge to see if the combined edge is maintained.

**Source Code:**

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## RSI Part 7 – Bullish Regular Divergence

In this article we will be testing Bullish Regular Divergence using RSI.

**Bullish Regular Divergence**

Price: Lower Low

RSI: Higher Low

Using *Bullish Hidden Divergence* we were able to significantly exceed our targets and prove that there exists a statistical edge when using that method. However, the same can not be said for regular divergence. The strategy produced several combinations which were profitable, but all of the returns were well below our targets. Therefore we can not rule out random chance accounting for those results. Here is a P/L chart from the best combination:

Notice how “random” and volatile the results appear? When compared to the chart produced from the *Hidden Divergence *article, you can clearly see the difference. Here is a P&L chart from the *Hidden Divergence* article.

**Related Posts:**

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## RSI Part 6 – Bullish Hidden Divergence

A common technique for trading oscillators such as RSI is to use divergence. There are two types of divergence, regular and hidden. Regular divergence is commonly used to signal trend changes, and hidden divergence is used to signal trend continuation.

**Bullish Regular Divergence**

Price: Lower Low

RSI: Higher Low

**Bearish Regular Divergence**

Price: Higher High

RSI: Lower High

**Bullish Hidden Divergence**

Price: Higher Low

RSI: Lower Low

**Bearish Hidden Divergence**

Price: Lower High

RSI: Higher High

In this article we will be testing Bullish Hidden Divergence. This method is commonly used when a stock is in an uptrend and pulls back to test support. To find divergence we need to look at the lows of both RSI and price. Since RSI moves smoother than price, I used it as a way of finding lows. Once a low has been identified in RSI, I start looking for another potential low. If one is found I compare the price of the stock at the time of the first RSI low to the value of the stock now. I then compare the first RSI low with the new potential low. If RSI has made a lower low and price has made a higher low I continue. Next, I check to see how many bars have passed since the first RSI low. This is to help ensure that enough distance has been created between the two valleys.

I optimized the strategy on 3 parameters:

1. RSI Period

2. Number of bars to look back when calculating a low

3. Number of bars to pass between lows

Initial (5 bar) results were decent. Most optimized pairs performed very well. However, only one combination was able to exceed our target value on both percent and profit. The strategy used a 9 bar RSI, 3 bar look-back, and required at least 9 bars between low points.

The (3 bar) results also did well. The same combination that exceeded our targets for 5 bars also exceeded for 3 bars. Here it the PL screenshot.

**Further Enhancements:**

Commonly Bullish Hidden Divergence is used to continue an uptrend. Therefore, I tried to only take trades when the stock was in a confirmed uptrend such as above a moving average etc. This method did not result in any performance gain. As we explore more indicators and determine which are ideal for identifying trend we can revisit this strategy.

**Source Code:**

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## RSI Part 5 – Optimized Thresholds

In this article I want to explore which threshold values are the most significant (long only) and also see what happens when applied to other markets. To test this, I optimized the strategy on both threshold and RSI period while counting the number of times the resulting combination exceeded our statistically significant levels for both percent profitable and net profit.

**Results for 5 Bars Into Future:**

First I looked at the various threshold values and how often when using the threshold I was able to surpass either our target percent profitable or target profit levels. Threshold values of 25 and 30 seemed to be the most robust.

Threshold |
Count Beat Percent |
Count Beat Profit |

10 | 0 | 0 |

15 | 1 | 0 |

20 | 3 | 1 |

25 | 3 | 2 |

30 | 2 | 3 |

35 | 2 | 0 |

40 | 4 | 0 |

45 | 6 | 0 |

Each of the above threshold values were used against various RSI periods ranging from 2-30. Below is a table outlining which periods resulted in surpassing our targets. Interestingly the lower periods 2-5 performed the best. I believe this may have something to do with our target holding time. Since we are only looking 5 bars into the future, the smaller RSI periods reflect the upcoming moves more accurately.

RSI Period |
Count Percent |
Count Profit |

2 | 2 | 2 |

3 | 4 | 1 |

4 | 3 | 2 |

5 | 1 | 2 |

6 | 1 | 2 |

7 | 0 | 1 |

8 | 0 | 1 |

9 | 0 | 1 |

10 | 0 | 1 |

19 | 0 | 2 |

30 | 0 | 1 |

The combination of RSI(3) < 30 was the only pair to result in both a beat on percent profitable as well as target profit level. I wanted to see how robust this pair actually was, so I ran it against all 30 of the DOW stocks. The method was profitable on 25 of the 30 stocks. With PG performing the best, and CAT performing the worst. Over 436 thousand trades were recorded during this test, resulting in 54.2% profitable trades.

The strategy was able to beat the target percent in 17 of the 30 stocks, and beat the target profit in 7 of the 30 stocks. Considering the period/threshold combination was optimized on a different market, I believe these results are very promising.

Next I wanted to see what happens if I flip the combination and entered long when RSI(3) > 70. The results were horrible as expected. Further lending support to their being an edge when below a threshold as opposed to above a threshold. Only 6 of the DOW 30 was profitable in this test. With a combined 50.06% profitable trades.

**Results for 3 Bars Into Future:**

The same methods used for 5 bars into the future were used for 3 bars. Here are the two resulting tables:

Threshold |
Count Beat Percent |
Count Beat Profit |

10 | 3 | 1 |

15 | 7 | 2 |

20 | 7 | 1 |

25 | 11 | 0 |

30 | 12 | 3 |

35 | 24 | 4 |

40 | 23 | 0 |

45 | 12 | 0 |

The results stayed similar to what we saw with 5 bars. Thresholds between 25-35 do very well. One thing to note is using 3 bars into the future we are having a lot more values beat our targets. This may indicate predicting 3 bars into the future is easier than 5 when using RSI.

RSI Period |
Count Percent |
Count Profit |

2 | 11 | 1 |

3 | 11 | 1 |

4 | 9 | 1 |

5 | 6 | 1 |

6 | 5 | 0 |

7 | 2 | 1 |

I had way too many RSI periods beat our targets. Therefore, I am displaying only the top performers. The lower periods seem to predict better than the higher periods for this time frame.

**Summary:**

It looks like any threshold between 25-35 is ideal with a period less than 5. I would like to point out that while I am only showing the count that beat our targets that this does not mean the other combinations did not fare well. In fact, combinations in the ranges I outline were uniformly great. We have strict requirements in the targets we are after. This is to ensure the results produced are not due to random chance. Its hard to go wrong when predicting either 3 or 5 bars into the future using a threshold of < 40.

The RSI(3) < 30 combination performing as well as it did against the DOW 30 stocks is very reassuring.

**Related Posts:**

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## RSI Part 4 – Moving Average Strategy

Our next strategy will explore what happens when RSI crosses above/below a moving average. In RSI part 2 we discovered that the RSI is effective at predicting the future when below a threshold. Now we need to determine if we can eliminate the need for pre-set threshold values and just rely on being below a moving average instead.

**Test 1: RSI above its moving average (long only)**

This test will be conducted by optimizing on two variables. One variable representing the look-back period used in the RSI calculation, and one variable representing the bars used in calculating the moving average. The strategy will enter long when above its moving average. Based on prior results, we would expect this strategy to be sub-par.

**Results: **

As expected the strategy performed horrible. No variable pairs resulted in producing a profit.

**Test 2: RSI below its moving average (long only)**

This test will be conducted by optimizing on two variables. One variable representing the look-back period used in the RSI calculation, and one variable representing the bars used in calculating the moving average. The strategy will enter long when below its moving average.

**Results:**

Most variable combinations resulted in profit. However, neither profit nor percentage was high enough to meet our standards. Because nearly every combination resulted in profit, it appears there may be a slight edge here. We will need to look closer at how we can better exploit this edge to meet our requirements.

**Test 3: RSI crosses below its moving average (long only)**

This test will be conducted by optimizing on two variables. One variable representing the look-back period used in the RSI calculation, and one variable representing the bars used in calculating the moving average. The strategy will enter long when RSI crosses below its moving average.

**Results:**

The results were very similar to what was seen in (RSI Part 3). The percent profitable as well as profit factor remained fairly stable. Only thing that changed was the number of trades taken.

**Source Code:**

**Download Source**

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## RSI Part 3 – Threshold Cross

In this article we aim to discover the significance of actually crossing a threshold. Because RSI is a momentum based indicator it stands to reason that the actual act of crossing a threshold may signal a better trade.

*(Comparison Results With RSI Part 2 – Long Only)*

Method: RSI(3) < 10

Percent Profitable: 60.36%

Net Profit: +12,100

Trades: 1559

**Conclusion:**

Requiring an actual cross only seems to decrease the number of trades. Profit factor and percent profitable remain nearly unchanged. Therefore we can conclude that the act of being below a threshold as seen in “RSI Part 2″ is sufficient and that watching only the cross is not required.

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## RSI Part 2 – Oversold Strategy

In the last article, we looked at RSI when it is above a threshold. This time we will explore what happens when RSI is below a threshold. To test this, we will optimize on two variables. One variable representing the look-back period for RSI and one variable to represent the threshold to cross below.

*(Example results looking 3 bars into future – Long Only)*

Method: RSI(3) < 10

Percent Profitable: 60.15%

Net Profit: +36,550

Trades: 5069

**Conclusions:**

Dozens of parameter combinations surpassed our targets on both percent profitable and/or on net profit. Especially combinations that involved RSI being below 20. This was seen in both 3 and 5 bars into the future. These findings suggest that there may be a statistical advantage when RSI is below certain thresholds.

In a future article we can explore which threshold values are significant and if there are any values that remain significant across multiple markets. We will also explore if there is a difference when RSI crosses above/below a threshold instead of just being below that threshold.

**Source Code:**

**Download Source**

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## RSI Part 1 – Momentum Trading

RSI is a momentum based indicator which stands for (Relative Strength Index). Because it gauges momentum, people recommend using RSI when it crosses above a threshold. Hopefully the stock’s momentum will continue to carry it higher.

To test this we created a strategy with 2 inputs. One input for the RSI look back period, and one for the threshold. We then ran an optimization against our 5 minute ES data.

**Results looking 5 bars into the future (Long Only): **

*(Best Percent)*

Percent Profitable: 53.06%

Trades: 35,073

Profit: -$43,275

*(Best Profit)*

Percent Profitable: 51.09%

Trades: 9,594

Profit: +$3,900

**Results looking 3 bars into the future (Long Only): **

*(Best Percent)*

Percent Profitable: 54.44%

Trades: 59,890

Profit: -$16,525

*(Best Profit)*

Percent Profitable: 52.96%

Trades: 22,748

Profit: +$6,037

**Conclusion:**

Trading RSI based on being above a threshold does not provide any statistical advantage. Most of the results were actually below the results obtained through random testing. This indicates that being below a threshold may perform better. We will explore this option in our next segment.

**Source Code:**

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