Kaufman’s 6 patterns were named Key Reversal, Island Reversal, Outside Days, Wide Ranging days, 3-Day Compression, and Gap opening. All are calculated from the previous 3 or 4 candles or price ranges. All but one are symmetric, meaning they deliver bullish and bearish signals. And because I’m a bit on the evil side, I added a 7th pattern that I just invented: TotalRandom.

Here’s how the patterns look as indicators in C:

// a higher high followed by a lower close. 
var cdlKeyReversal()
{
  if(priceHigh(0) > priceHigh(1) && priceLow(0) < priceLow(1)) {
    if(priceClose(0) < priceLow(1)) return -100; // sell
    if(priceClose(0) > priceHigh(1)) return 100; // buy
  } 
  return 0;
}


// recent 3 days each have a true range smaller than the 4th previous day.
var cdl3DayCompression()
{
  vars TRs = series(TrueRange(),4);
  if(TRs[0] < TRs[3] && TRs[1] < TRs[3] && TRs[2] < TRs[3])
    return 100;
  else
    return 0;
}

// a gap higher followed by a lower close, but not filling the gap. 
var cdlIslandReversal()
{
  if(priceLow(0) > priceHigh(1) && priceClose(0) < priceOpen(0)) 
    return -100; // sell
  if(priceLow(1) > priceHigh(0) && priceClose(0) > priceOpen(0)) 
    return 100; // buy
  else return 0;
}

// a higher high and a lower low, close in upper or lower 25% of the range.
var cdlOutsideDay()
{
  if(priceHigh(0) > priceHigh(1) && priceLow(0) < priceLow(1)) {
    if(priceClose(0) < 0.75*priceLow(0) + 0.25*priceHigh(0)) 
      return -100; // sell
    if(priceClose(0) > 0.25*priceLow(0) + 0.75*priceHigh(0)) 
      return 100; // buy
  } 
  return 0; 
}

// same as outside days, but true range must exceed 1.5 × 20-day ATR
var cdlWideRangeDays()
{
  if(TrueRange() > 1.5*ATR(20))
    return cdlOutsideDay();
  else
    return 0;
}

// gap must be larger than 0.5 × 20-day ATR.
var cdlGapOpening()
{
  var Ratio = (priceOpen(0) - priceClose(1))/ATR(20);
  if(Ratio >= 0.5) return 100;
  if(Ratio <= -0.5) return -100;
  return 0; 
}

// just enter a trade when you feel lucky
var cdlTotalRandom()
{
  int Pattern = random(100);
  if(Pattern > 90) return 100;
  if(Pattern < 10) return -100;
  return 0;
}

Following the convention of the classic candle pattern indicators from the TA library, the pattern functions return +100 for a bullish pattern, -100 for a bearish pattern, and 0 for no pattern.

We’re now putting them to the  test. We want to trade the patterns with IWM, AAPL, AMZN, GE, WMT, and TSLA stocks, with SPY and QQQ index ETFs, and with and without an additional trend filter. For any detected pattern, we’re entering a long or short position depending on if it’s bullish or bearish. We always invest the same amount, regardless of the price of the stock. The position is closed after 1, 2, 3, 4, or 5 days. For any asset and any exit type we’ll export the number of trades and the total win and loss to a table in HTML format. That is convenient for me because I can paste it directly in this blog article.

The test script:

var pattern();

function run()
{
  pattern = cdlKeyReversal;
  bool WithTrend = 0;
  string Name = "KeyRev";

  BarPeriod = 1440;
  StartDate = 20100101; // TSLA went public in 2010
  EndDate = 2020; // test until 2020
  var Investment = 10000;
  TradesPerBar = 40; // 8 assets * 5 algos

  char File[100];
  if(is(EXITRUN)) {
    sprintf(File,"Log\\%s.htm",strf("%s%s",
      Name,ifelse(WithTrend,"WithTrend","NoTrend")));
    printf("\nStoring results in %s",File);
    file_write(File,strf("<p>%s:</p>\n<table><tr>",File),0);
// write the table header
    file_append(File,"<td>Asset</td>",0);
    file_append(File,"<td>Long/Short</td>",0);
    file_append(File,"<td>Day 1</td>",0);
    file_append(File,"<td>Day 2</td>",0);
    file_append(File,"<td>Day 3</td>",0);
    file_append(File,"<td>Day 4</td>",0);
    file_append(File,"<td>Day 5</td></tr>",0);
  }

  assetAdd("SPY","STOOQ:*.US"); // load price history from Stooq
  assetAdd("QQQ","STOOQ:*.US");
  assetAdd("IWM","STOOQ:*.US");
  assetAdd("AAPL","STOOQ:*.US");
  assetAdd("AMZN","STOOQ:*.US");
  assetAdd("GE","STOOQ:*.US");
  assetAdd("WMT","STOOQ:*.US");
  assetAdd("TSLA","STOOQ:*.US");

  while(asset(loop("SPY","QQQ","IWM","AAPL","AMZN","GE","WMT","TSLA"))) {
  vars Trend = series(SMA(seriesC(),80));
  while(algo(loop("Day1","Day2","Day3","Day4","Day5"))) {

  Lots = Investment/priceClose();
  LifeTime = Itor2+1; // life time in days
  int Signal = pattern();
  if(Signal > 0 && (!WithTrend || rising(Trend)))
    enterLong();
  else if(Signal < 0 && (!WithTrend || falling(Trend)))
    enterShort();
  if(is(EXITRUN)) {
    if(Algo == "Day1") // first loop run
      file_append(File,strf("\n<tr><td>%s</td><td>%i/%i</td>",
        Asset,NumWinLong+NumLossLong,NumWinShort+NumLossShort),0);
    string Color = ifelse(WinLong-LossLong+WinShort-LossShort > 0,
      "bgcolor=\"lime\"","bgcolor=\"red\"");
    file_append(File,strf("<td %s>%.0f/%.0f</td>",
      Color,WinLong-LossLong,WinShort-LossShort),0);
    if(Algo == "Day5")
      file_append(File,"</tr>",0);
  }

  }} // loops
  if(is(EXITRUN)) {
    file_append(File,"</table>",0);
    file_append(File,strf("<p>Total Profit: %.0f (%.0f%%)</p>",
      WinTotal-LossTotal,100*(WinTotal-LossTotal)/Investment),0);
  }
}

Some explanations about the code. At the begin of the run() function the pattern and the trend mode are set up. For convenience we’re using a function pointer that is set to the pattern function to be tested. Afterwards, when it’s the last run, the table header is written into the HTM file. A char array (File) and the sprintf() function is used for the file name instead of the more convenient strf(), because we need to keep the file name for later writing into the table.

The test uses two nested loops, first for selecting the stocks, second for selecting the trade life time to get the results from a 1-day trade up to a 5-days trade. The predefined Itor2 variable is the iterator of the second loop and runs from 0 to 4, so we just use it to set the LifeTime variable for the subsequent trade. The results are printed in the EXITRUN at the last day of the simulation.

The numbers in the tables are the results from long/short trades. A winning pattern is displayed in green, a losing pattern in red. Transaction costs are considered.