Category Archives: back testing

Portfolio Strategy Based On Accumulation/Distribution

back testing, ETFS, indexes, portfolio management, Stocks & Commodities traders tips

The AIQ code based on Domenico D’Errico’s article in the August issue of Stocks & Commodities magazine, “Portfolio Strategy Based On Accumulation/Distribution,” is shown below.

“Whether you are an individual trader or an asset manager, your main goal in reading a chart is to detect the intentions of major institutions, large operators, well-informed insiders, bankers and so on, so you can follow them. Here, we’ll build an automated stock portfolio strategy based on a cornerstone price analysis theory.”

!Portfolio Strategy Based on Accumulation/Distribution
!Author: Domenic D'Errico, TASC Aug 2018
!Coded by: Richard Denning 6/10/18
!www.TradersEdgeSystem.com
!Portfolio Strategy Based on Accumulation/Distribution
!Author: Domenic D'Errico, TASC Aug 2018
!Coded by: Richard Denning 6/10/18
!www.TradersEdgeSystem.com

!SET TO WEEKLY MODE IN PROPERTIES
!ALSO VIEW CHARTS IN WEEKLY MODE

!INPUTS:
rLen is 4.
consolFac is 75. ! in percent
adxTrigger is 30.
volRatio is 1.
volAvgLen is 4.
volDelay is 4.

!CODING ABREVIATIONS:
H is [high].
L is [low].
C is [close].
C1 is valresult(C,1).
H1 is valresult(H,1).
L1 is valresult(L,1).

!RANGE ACCUMULATION/DISTRIBUTION:
theRange is hival([high],rLen) - loval([low],rLen).
Consol if theRange < consolFac/100 * valresult(theRange,rLen).
rRatio is theRange/valresult(theRange,4)*100.

!AVERAGE TRUE RANGE ACCUMULATION/DISTRIBUTION:
avgLen is rLen * 2 - 1.	
TR  is Max(H-L,max(abs(C1-L),abs(C1-H))).
ATR  is expAvg(TR,avgLen).

ConsolATR if ATR < consolFac/100 * valresult(ATR,rLen). atrRatio is ATR / valresult(ATR,4)*100. !ADX ACCUMULATION/DISTRIBUTION: !ADX INDICATOR as defined by Wells Wilder rhigh is (H-H1). rlow is (L1-L). DMplus is iff(rhigh > 0 and rhigh > rlow, rhigh, 0).
DMminus is iff(rlow > 0 and rlow >= rhigh, rlow, 0).
AvgPlusDM is expAvg(DMplus,avgLen).
AvgMinusDM is expavg(DMminus,avgLen).           	
PlusDMI is (AvgPlusDM/ATR)*100.	
MinusDMI is AvgMinusDM/ATR*100.	
DIdiff is PlusDMI-MinusDMI. 		
Zero if PlusDMI = 0 and MinusDMI =0.
DIsum is PlusDMI+MinusDMI.
DX is iff(ZERO,100,abs(DIdiff)/DIsum*100).
ADX is ExpAvg(DX,avgLen).

ConsolADX if ADX < adxTrigger. !CODE FOR ACCUMULATIOIN/DISTRIBUTION RANGE BREAKOUT: consolOS is scanany(Consol,250) then offsettodate(month(),day(),year()). Top is highresult([high],rLen,^consolOS). Top0 is valresult(Top,^consolOS) then resetdate(). Bot is loval([low],rLen,^consolOS). AvgVol is simpleavg([volume],volAvgLen). Bot12 is valresult(Bot,12). BuyRngBO if [close] > Top
and ^consolOS <= 5 and ^consolOS >= 1
and Bot > Bot12
and valresult(AvgVol,volDelay)>volRatio*valresult(AvgVol,volAvgLen+volDelay).
EntryPrice is [close].

Sell if [close] < loval([low],rLen,1).
ExitPrice is [close].

Figure 9 shows the summary backtest results of the range accumulation breakout system using NASDAQ 100 stocks from December 2006 to June 2018. The exits differ from the author’s as follows: I used two of the built-in exits — a 20% stop-loss and a profit-protect of 40% of profits once profit reaches 10%.

Sample Chart

FIGURE 9: AIQ. Here are the summary results of a backtest using NASDAQ 100 stocks.

Figure 10 shows a color study on REGN. The yellow bars show where the range accumulation/distribution shows a consolidation.

Sample Chart

FIGURE 10: AIQ. This color study shows range consolidation (yellow bars).

—Richard Denning

info@TradersEdgeSystems.com

for AIQ Systems

A Technical Method For Rating Stocks

back testing, EDS, Stocks & Commodities traders tips, technical indicator
The AIQ code based on Markos Katsanos’ article in this issue, “A Technical Method For Rating Stocks,” is shown below.
Synopsis from Stocks & Commodities June 2018
I’s it possible to create a stock rating system using multiple indicators or other technical criteria? If so, how does it compare with analyst ratings? Investors around the world move billions of dollars every day on advice from Wall Street research analysts. Most retail investors do not have the time or can’t be bothered to read the full stock report and rely solely on the bottom line: the stock rating. They believe these ratings are reliable and base their investment decisions at least partly on the analyst buy/sell rating. But how reliable are those buy/sell ratings? In this article I will present a technical stock rating system based on five technical criteria and indicators, backtest it, and compare its performance to analyst ratings.
!A TECHNICAL METHOD FOR RATING STOCKS
!Author: Markos Katsanos, TASC June 2018
!Coded by: Richard Denning, 4/18/18
!www.TradersEdgeSystems.com

!INPUTS:
  MAP is 63. 
  STIFFMAX is 7. 
  VFIPeriod is 130. 
  MASPY is 100. 
  MADL is 100.
  SCORECRIT is 5.
  W1 is 1.
  W2 is 1.
  W3 is 1.
  W4 is 1.
  W5 is 2.
 
!VFI FORMULA: 
  COEF is 0.2.
  VCOEF is 2.5.
  Avg is ([high]+[low]+[close])/3.
  inter is ln( Avg ) - ln( Valresult( Avg, 1 ) ). 
  vinter is sqrt(variance(inter, 30 )).
  cutoff is Coef * Vinter * [Close].
  vave is Valresult(simpleavg([volume], VFIPeriod ), 1 ).
  vmax is Vave * Vcoef.
  vc is Min( [volume], VMax ).
  mf is Avg - Valresult( Avg, 1 ).
  vcp is iff(MF > Cutoff,VC,iff(MF < -Cutoff,-VC,0)).
  vfitemp is Sum(VCP , VFIPeriod ) / Vave.
  vfi is expavg(VFItemp, 3 ).

!STIFFNESS 
  ma100 is Avg. 
  CLMA if [close] < MA100.
  STIFFNESS is countof(CLMA,MAP).

!CONDITIONS:
 ! MONEY FLOW:
   COND1 is iff(VFI>0,1,0). 
 !SIMPLEAVG:
    SMA is simpleavg([close],MADL).                              
    COND2 is iff([close]>SMA,1,0).  
 !SIMPLEAVG DIRECTION:                       
    COND3 is iff(SMA>valresult(SMA,4),1,0).  
!STIFFNESS:                          
    COND4 is iff(STIFFNESS<= STIFFMAX,1,0).  
!MARKET DIRECTION:
    SPY is TickerUDF("SPY",[close]).
    COND5 is iff(EXPAVG(SPY,MASPY)>= 
 valresult(EXPAVG(SPY,MASPY),2),1,0).            

SCORE is  W1*COND1+W2*COND2+W3*COND3+
   W4*COND4+W5*COND5.

 buy if Score>=SCORECRIT and hasdatafor(300)>=268.
Figure 11 shows the summary results of a backtest using NASDAQ 100 stocks during a generally bullish period from April 2009 to April 2018. Figure 12 shows the backtest using the same list of NASDAQ 100 stocks during a period that had two bear markets (April 1999 to April 2009). The average results are similar except that there are fewer trades during the period that contained the two bear markets. Both backtests use a fixed 21-bar exit.
Sample Chart

FIGURE 11: AIQ, BULL MARKET. Here are the summary results of a backtest using NASDAQ 100 stocks during a generally bullish period from April 2009 to April 2018.
Sample Chart

FIGURE 12: AIQ, BEAR MARKET. Here are the summary results of a backtest using NASDAQ 100 stocks during a period from April 1999 to April 2009 that contained two bear markets.
—Richard Denning info@TradersEdgeSystems.com for AIQ Systems

A Candlestick Strategy With Soldiers And Crows

back testing, EDS

ndle reversal patterns—a bullish one white soldier and a bearish one black crow—that requ

The Expert Design Studio code for Jerry D’Ambrosio and Barbara Star’s article, “A Candlestick Strategy With Soldiers And Crows,” in Stocks & Commodities October 2018 issue is shown below.”Among the more well-known candlestick reversal patterns are soldiers and crows. These occur in a three-candle pattern such as three white soldiers or three black crows. Recently, on the website Candlesticker.com, we learned of two other candle reversal patterns—a bullish one white soldier and a bearish one black crow—that require fewer candles. ”

!A CANDLESTICK STRATEGY WITH SOLDIERS AND CROWS
!Author: Jerry D'Ambrosio & Barbara Star, TASC Oct 2017
!Coded by: Richard Denning 8/05/2017
!www.TradersEdgeSystems.com

!CODING ABBREVIATIONS:
O is [open].
O1 is valresult(O,1).
C is [close].
C1 is valresult(C,1).
C2 is valresult(C,2).
H is [high].
L is [low].
V is [volume].

!INPUTS:
minPriceBull is 1.
minPriceBear is 10.
minVolume is 1000. !in hundreds
volAvgLen is 50.
dayCount is 5.
longExitBars is 7.
shortExitBars is 1.

okToBuy if simpleavg(C,50) > simpleavg(C,200) or CminPriceBull and simpleavg(V,volAvgLen)>minVolume.
BullWS if C1C1 and C>O1 and O= longExitBars.

okToSell if simpleavg(C,50) < simpleavg(C,200) or C>simpleavg(C,200)*1.1.
okToSellMkt if TickerRule("SPX",okToSell).
PVfilterBear if C>minPriceBear and simpleavg(V,volAvgLen).
BearBC if C1>C2 and C1>O1 
     and OO1 
     and countof(C1>C2,dayCount)=dayCount
     and PVfilterBear and okToSellMkt.
ExitShort if {position days} >= shortExitBars.
I ran several backtests using the NASDAQ 100 list of stocks over the period from 8/04/2000 to 8/04/2017. I varied the following inputs to find the optimum set of parameters for the candlestick patterns. For longs, the “dayCount” = 5 with an “longExitBars” = 7 produced the best results, which is shown in Figure 5. For shorts, the “dayCount” = 5 with a “shortExitBars” = 1 produced the best results, which is shown in Figure 6. Neither commission nor slippage were subtracted from the results.

Sample Chart

FIGURE 5: WINWAY. EDS summary report for longs only.

Sample Chart

FIGURE 6: WINWAY. EDS summary report for shorts only.
—Richard Denning
info@TradersEdgeSystems.com
for TradingExpert Pro

ire fewer candles. “

System Development Using Artificial Intelligence

back testing, EDS, Stocks & Commodities traders tips
The AIQ code based on Domenico D’Errico and Giovanni Trombetta’s article in August 2017 Stock & Commodities issue, “System Development Using Artificial Intelligence,” is shown here. You can also download the EDS file from here

Are humans or computers better at trading? This question has been around on many fronts since the era of punch cards, and as technology advances, you question whether machines have limits. It’s the same with trading, and here’s an algorithm that may shed some light on which performs better…

!ARTIFICAL INTELLIGENCE FOR SYSTEM DEVELOPMENT
!Authors: Domenico D'Errico & Giovanni Trombetta, TASC August 2017
!Coded by: Richard Denning, 6/08/2017
!www.TradersEdgeSystems.com

!INPUTS:
O is [open].
C is [close].
H is [high].
L is [low].
exitBars is 8.
exitBarsP is 6.
enterGap is -0.08.

!CODE:
AvgP is (O+C+H+L)/4.
MedP is (H+L)/2.
MedB is (O+C)/2.

AvgP1 is valresult(AvgP,1).
AvgP2 is valresult(AvgP,2).
AvgP3 is valresult(AvgP,3).

MedP1 is valresult(MedP,1).
MedP2 is valresult(MedP,2).
MedP3 is valresult(MedP,3).
MedP4 is valresult(MedP,4).

MedB1 is valresult(MedB,1).
MedB2 is valresult(MedB,2).
MedB3 is valresult(MedB,3).
MedB4 is valresult(MedB,4).

!ENTRY & EXIT RULESl
Gandalf if 
  (AvgP1exitBars-1)
 or ({position days}>=exitBars-1)
 or ({position days}>=exitBarsP-1 and (C-{position entry price}>0)).

EntryPr is min(val([low],1) + enterGap,[open]).

Buy if Gandalf and [low] <= EntryPr.
See Figure 10 for how to set up the pricing in a backtest.
Sample Chart

FIGURE 10: AIQ. This shows the EDS backtest settings for entry pricing.
—Richard Denning
info@TradersEdgeSystems.com
for AIQ Systems

Detecting Swings

back testing, EDS

The AIQ code based on Domenico D’Errico’s article in the May 2017 issue of Stocks & Commodities issue, “Detecting Swings,” is provided here.

I tested the author’s four systems using the NASDAQ 100 list of stocks on weekly bars, as did the author, from 3/16/2005 through 3/14/2017. Figure 7 shows the comparative metrics of the four systems using the four-week exit. The results were quite different than the author’s, probably due to a different test portfolio and also a 10-year test period rather than the author’s 20-year period. In addition, my test results show longs only, whereas the author’s results are the average of both the longs and shorts.

Sample Chart

FIGURE 7: AIQ. As coded in EDS, this shows the metrics for the author’s four systems run on NASDAQ 100 stocks (weekly bar data) over the period 3/16/2005 to 3/14/2007.

The Bollinger Band (Buy2) system showed the worst results, whereas the author’s results showed the Bollinger Band system as the best. The pivot system (Buy1) showed the best results, whereas the author’s results showed the pivot system as the worst. I am not showing here the comparative test results for the Sell1 thru Sell4 rules, as all showed an average loss over this test period.

!DECTECTING SWINGS
!Author: Domenico D'Errico, TASC May 2017
!Coded by: Richard Denning, 3/15/17
!www.TradersEdgeSystems.com

!Set to WEEKLY in properties

Low is  [low].
Low1  is valresult(Low,1).
Low2  is valresult(Low,2). 
High is [high].
High1  is valresult(High,1).
High2  is valresult(High,2). 
PivotLow if Low1 &lt; Low2  and Low1 &lt; Low.
PivotHigh if High1 &gt; High2  and High1 &gt; High.

Buy1 if  PivotLow.  
Sell1 if  PivotHigh.    

!Set parameter for bollinger bands to 12 with 2 sigma (weekly) in charts:
Buy2 if [close] &gt; [Lower BB] and valrule([close] &lt;= [Lower BB],1).
Sell2 if [close] &lt; [Upper BB] and valrule([close] &gt;= [Upper BB],1).

!Set parameter for Wilder RSI to 5 (weekly) in charts:
Buy3 if [RSI Wilder] &gt; 40 and valrule([RSI Wilder] &lt;= 40,1).
Sell3 if [RSI Wilder] &lt; 60 and valrule([RSI Wilder] &gt;= 60,1).

Buy4 if [RSI Wilder] &lt; 40  And Low &gt; Low1.
Sell4 if [RSI Wilder] &gt; 60  And High &lt; High1.    

Exit if {position days} &gt;= 4.

The code and EDS file can be downloaded from http://aiqsystems.com/detectingswings.EDS

—Richard Denning

info@TradersEdgeSystems.com

for AIQ Systems