Trading Idea #010 – TASC Optimized CCI

This idea is from Technical Analysis of Stocks & Commodities (TASC) magazine’s website.  This is the second in a series of three system ideas that TASC features on their website.  This system uses Commodity Channel Index (also known as CCI trading), which is an indicator that shows when the market may be overbought and oversold.  This indicator was developed by Donald Lambert in 1980.  As the name suggests, it was originally designed for commodities, but it has been used in equities, currencies, and other financial instruments.   

The rules they provide are somewhat vague, since CCI trading is used in various ways: 

For this system, all CCI numbers from 2 to 100 were tested over a lookback period of 500 days. Buy signal is triggered when CCI reaches -100. Sell signal is triggered when CCI reaches +100. Tested on daily price data.

 I interpret these rules to be as follows:

  • Optimize the CCI Length from 2 – 100
  • Buy when CCI crosses over -100 (moving up)
  • Sell when CCI crosses under 100 (moving down)

The first TASC system I tried, the Optimized Moving Average, bombed.  One of the difficulties I had was trying to replicate the results on  Without knowing the start dates for optimization and trading, it was nearly impossible.  My goal here is to see if this idea works at all, irrespective of the results on their site

Phase 1: Plan & Design

1. Trading Idea

The idea is simple:

  • Buy when the CCI indicates we are moving out of the oversold area
  • Sell short when the CCI indicates we are moving out of the overbought area
  • This is an ‘always in’ system

CCI length will be optimized.  I will be looking for the ideal in-sample/out-of-sample periods, between 200 to 500 trading days.  There are no stop losses or profit targets.

I will only test on equities, as their system does.

2. System Definition

Position Sizing:

I will use the following position sizing:

  • Stocks/equities: # shares = $10,000 / Close price, rounded down


  • Long:
    • If CCI crosses over -100
    • Buy next bar at market
  • Short:
    • If CCI crosses under 100
    • Sell short next bar at market
  • Profit targets: None
  • Stop Loss: None

Parameters (Default):

I will use the following parameters:

  • CCILength

Challenges: None. 

This system is pretty easy to develop.

3. Performance Objectives

The system will meet the following objectives:

System Type (trend, mean-reversion, day, swing, etc.)Trend following
Walk-forward Efficiency> 50%
Risk of Ruin0%
Profit Factor>= 1.5
Win Percent>= 30%
Max Drawdown %< 35%
Profit/Drawdown Ratio>= 2.0
Ready Date2021/03/12

I added Walk-forward Efficiency, as I am finding this to be a useful measure of the effectiveness of the optimized values.  50% may be too low, but I need to start somewhere with this. 

This idea is S.M.A.R.T.: Specific, Measurable, Achievable, Realistic, Time-bound

4. Market Selection


EnergiesCurrenciesFixed IncomeAgricultureMetalsSoftsIndexesEquities


Market SectorInstrumentSymbolComments
EquitiesRandom equities from S&PCAT, CL, COP, CPB, CVS, CVX, D, DE, DHI, DHR, DRI, DTE, ED, EIX, ES, ETN, ETR, EXC, F, FCX, FE, FITB, GD, GE, GLW, HAL, HBAN, HIG, HOG, HSY, HUM, IBM, IP, JNPR, K,  KMB, KO, KR, KSS, L, LEG, LHX, M, MAR, MCK, MCO, MET, MKC, MMM, MO, MRK, MS, MSI, MTBI picked a random selection of equities that have been active over the past 20 years.

Chart Type, Timeframe, Session, Time Zone:

Chart TypeRegular CandlestickCharting is only useful for validating entry and exit signals
Timeframe / Interval(s)Daily 
Time ZoneExchange 

Phase 2: Build

5. Manual Test

I walked through some symbols and this worked well enough to proceed.

6. Build

Process Diagram


Sweet and simple.

7. Unit Test

The unit test went fine, and everything works as expected.  I have a concern about when the CCI crosses over 100 or -100, generating a sell or buy signal, but then crossing back over the same line.  It is possible to be on the wrong side of a trend and get stuck there.  Below is an example of this phenomenon:

I do not have an answer for this since our rules are clear.  The other cross-overs in this case is just whipsaw, but ultimately we are on the wrong side, at least for now.


Note: Unit Test verifies that the CCI trading system is executing the trading rules correctly.  It is, essentially, quality control.

Phase 3: Test

8. Optimization

I optimized one input parameter:

  • CCILength: range 2 to 100, step 1

9. Walk-Forward Analysis

None of the symbols passed, failing one or both of these two data points:

  • Walk-forward Efficiency
  • Profit Factor

Do you remember the Performance Objectives section, where I added Walk-forward Efficiency?  Why did I do that?  Let me explain why I am starting to think this is an important metric:

If Walk-forward Efficiency is 100%, that means that the out-of-sample testing results worked exactly as the optimized parameter(s) suggested they would.  If it was 0%, then it was as effective as a monkey beating orders into our order entry application.  50% means the optimized parameters were right only about half the time.  A coin flip, if you will.

I may be wrong about this, but I will continue to refine my thinking around this.  

However, one instrument caught my eye MET (Metlife):

  • It had a fairly steady equity curve
  • It had the best Walk-forward Efficiency, at 46.3%
  • Profit Factor: 1.91

I am going to advance this to Monte Carlo to see what it looks like.  I think it will perform well, given its past performance.

10. Monte Carlo Simulation

This is how MET performed in Monte Carlo simulation: 

One of my objectives is to have a Risk of Ruin at 0% for a given system, which is very strict, but it is what I require.  Although the Median Return and Return to Drawdown ratio is very good, it still does not meet my criteria and does not advance to the next.

Is this untradable? No.  I could probably trade it and make money with it, but it did not meet my Risk of Ruin goal, so it does not advance to incubation.

11. Incubation

We did not make it this far.  I ran MET through incubation anyhow, and it is +$400 (marked-to-market) for the past 6 months, but the current position is in a -$2,300 drawdown.

Phase 4: Deploy

We did not make it this far.

Notes and Commentary

Another TASC system failed to pass through our development process.  I believe the issue I uncovered in Unit Testing shows the main weakness of the CCI trading system.  I have learned from experienced systems traders, those working at successful hedge funds and CTA’s (Commodity Trading Advisor), that simple systems are the best.  My best system has one entry rule and two exit rules.  This system is a little too simple. 

MET is a good example of this.  Over a six week period in 2021, February to March, the CCI trading system oscillated around the 100 line (using the optimized CCI Length of 21), all while being stuck in a short position since January.

You can see there were six signals to go short (blue line), but the instrument was in a consolidation phase.  The red line, a 9 period moving average of the CCI, is given for reference.

Can this system be improved?  Perhaps.  Here are some ideas for future systems:

  • Use a moving average or other smoothing method on CCI trading to reduce the choppiness; John Ehlers developed an Adaptive CCI which I will consider using
  • Use a stop-and-reverse method when caught on the wrong side
  • Use a stop, such as ATR, to determine when we are caught on the wrong side and stay flat until the next signal
  • Try it on futures or forex

That is all for this system. 

One big takeaway is that you cannot just take someone else’s system idea and start trading it.  Algorithmic, quantitative, and systematic trading allows us to see if an idea is valid with a certain amount of confidence.  A system may work for 6 months, 1 year, or two years.  I am looking for system robustness.  MultiCharts, one of my trading platforms, has a great walk-forward feature that measures system robustness, based on user-selected metrics (fitness functions such as profit factor, drawdown, etc.).  It simply gives a pass/fail grade, which I have found to be very helpful.  We are looking for robustness, something that we expect to perform well over a very long time.

I sincerely thank you for taking the time to read this article.  If you want to stay informed about each new trading idea I test, subscribe to my semimonthly newsletter (below).  If you have an idea you would like to build and test, feel free to leave a comment or reach me on the Comments page and we can discuss.

Next trading idea: Connors RSI 2 – RSI mean-reversion revisited… you will not want to miss this one!

Trading System Result: FAIL


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