Category Archives: EasyLanguage

Super Combo Day Tradng System A 2020 Redo!

If you have some time on your hands and you want to build your own Frankenstein monster from a parts bin, here is your chance.  The Super Combo Day Trading System was originally published in my “Building Winning Trading Systems” book back in 2001.  I designed it to be more of a tutorial than a pure trading system.    You should be able to get the spare parts you need to create your own day trading system.  Back in 2001, I wanted to show how to control and monitor different entry and exit techniques in one complete algorithm.  The system was designed to day-trade the big SP and the results at the time looked promising.  Since the transition to the ES and the higher levels of volatility that we have seen over the years and the adoption of overnight trading,  the system hasn’t fared that well, but the concepts are still viable as an instructional tool today as they were 20 years ago.  EasyLanguage has been improved over this time period so the coding for the Super Combo can definitely take advantage of the new enhancements.

Here are the main premises of the logic:

  • take advantage of a buyEasier and shortEasier pattern setup
  • incorporate daily and 5-minute time frames in one chart
  • include a breakOut, failedBreakOut and reverseOnLiquidation trade entry techniques
  • monitor which signal is currently online and apply the correct exit signal
  • monitor profit and incorporate a break even stop
  • monitor time and incorporate a trailing stop
  • provide an interface into the logic via inputs

Okay here we go – there is quite a bit of code here so let’s divide an conquer by examining just one module at a time.  This first module includes the inputs and variables section plus once per day calculations.

[LegacyColorValue = true]; 

{Super Combo by George Pruitt - redo 2020
This intra-day trading system will illustrate the multiple data
handling capabilities of TradeStation. All pertinent buy and sell
calculations will be based on daily bars and actual trades will be
executed on 5-min bars. I have made most of the parameters input
variables}

Inputs:waitPeriodMins(30),initTradesEndTime(1430),liqRevEndTime(1200),
thrustPrcnt1(0.30),thrustPrcnt2(0.60),breakOutPrcnt(0.25),
failedBreakOutPrcnt(0.25),protStopPrcnt1(0.30),protStopPrcnt2(0.20),
protStopAmt(3.00),breakEvenPrcnt(0.50),avgRngLength(10);

Variables:averageRange(0),canTrade(0),buyEasierDay(FALSE),
sellEasierDay(FALSE),buyBOPoint(0),sellBOPoint(0),longBreakPt(0),
shortBreakPt(0),longFBOPoint(0),shortFBOPoint(0),barCount(0),buysToday(0),
sellsToday(0),mp(0),longLiqPoint(0),shortLiqPoint(0),
longLiqPoint1(0),shortLiqPoint1(0),intraTradeHigh(0),intraTradeLow(999999);


{Just like we did in the psuedo code -- let's start out with the daily
bar calculations. If Date <> Date[1] -- first bar of day}
if(Date <> Date[1]) then {save time by doing these calculations once per day}
begin
averageRange = Average(Range,10) of Data2; {Data 2 points to daily bars}

canTrade = 0;
if range of data2 < averageRange then canTrade = 1;

{use close of data2 - seems to be more accurate than CloseD(1)
buyEasierDay =Close of Data2 >= Close[1] of Data2;
sellEasierDay = Close of Data2 < Close[1] of Data2;

buyBOPoint = Open + thrustPrcnt1*averageRange;
sellBOPoint= Open - thrustPrcnt2*averageRange;

if(sellEasierDay) then
begin
sellBOPoint= Open - thrustPrcnt1*averageRange;
buyBOPoint = Open + thrustPrcnt2*averageRange;
end;

longBreakPt = HighD(1) + breakOutPrcnt*averageRange;
shortBreakPt= LowD(1) - breakOutPrcnt*averageRange;

shortFBOPoint = HighD(1) - failedBreakOutPrcnt*averageRange;
longFBOPoint= LowD(1) + failedBreakOutPrcnt*averageRange;

{Go ahead and initialize any variables that we may need later on in the day}

barCount = 0;
buysToday = 0;sellsToday = 0;{You can put multiple statements on one line}
end;
First Modules of SuperCombo 2020

Here I am just setting up the inputs and variables that I will need to execute the algorithm.  If you are using .D data then the code

if date <> date[1] then

is a valid test for the first bar of the day.  A new date will represent the beginning of the next day.  The code controlled by this if-then construct is only executed one time per day.  So if you can put the lion’s share of daily calculations here, then it should speed stuff up.  The first thing I do is calculate the average range of the last 10 daily bars.  I access this date from data2.  Can you build a loop and accumulate the difference between the HighD and LowD function calls?

  1. for i = 1 to 10 begin
  2.      sum = sum + (HighD(i) – LowD(i));
  3. end;

The HighD() and LowD() functions are EasyLanguage enhancements that can help eliminate the need for a multi-data chart.  However, if you do this, you will get an warning message that its not a good idea.  I have done this and it seems to work, but to be safe just use Data2.    Next I determine if there has been a narrow range or range compression by comparing yesterday’s range to the averageRange.  If so, then I allow trading.  This is an old filter that looks for range expansion after compression.  The concept of a buyDay and sellDay was originated in the 1930s by George W. Cole (correct me if I am wrong here).  I use this idea by comparing the prior two bars closing relationships.  If there has been an up close, then I consider the next day to be a buyEasier day.  If the opposite is true, then its a sellEasier day.   This system isn’t unidirectional and does allow buying  and shorting in the same session – hence the word easier.   Continuing I calculate the levels that if the market reaches will hopefully trigger a short term trend in that direction.  This is the once highly respected open range break out or ORBO.  This methodology has lost its luster over the last 10 years or so due to overnight trading and allowing pent up buying and selling to be expressed in the overnight sessions.  Twenty years ago it was still viable.  The next bit of code creates the break out levels based on the buyEasier or sellEasier days.   The thrust is calculated by multiplying the range by thrustPrcnt1 and thrustPrcnt2.

So that is method 1 – break out.  Hope the market breaks out and continues to the close.  I wish it were this easy.  Since its not, the second methodolgy, FailedBreakOut, is calculated.  This is also known as the “ClearOut” trade.   The market is pushed to take out all the buy stops and then pulled back for the professionals to feast on the amateurs.  SuperCombo tries to take advantage of this by calculating the two points to determine a failed break out.  On the long side, it is the two points the market rises up to and then falls back to.  If the market breaches the longBreakPt, then look to sellShort at the shortFBOPoint.    Here is the next module

{Now lets trade and manage on 5-min bars}

barCount = barCount + 1; {count the number of bars of intraday data}
if(barCount >= waitPeriodMins/BarInterval and canTrade = 1) then {have we waited long enough}
begin
if(MarketPosition = 1) then buysToday = 1;
if(MarketPosition =-1) then sellsToday= 1;

if(buysToday = 0 and Time < initTradesEndTime) then
Buy("LBreakOut") next bar at buyBOPoint stop;

if(sellsToday= 0 and Time < initTradesEndTime) then
SellShort("SBreakout") next bar at sellBOPoint stop;

if(highD(0) > longBreakPt and sellsToday = 0 and Time < initTradesEndTime) then
SellShort("SfailedBO") next bar at shortFBOPoint stop;
if(lowD(0) < shortBreakPt and buysToday = 0 and Time < initTradesEndTime) then
Buy("BfailedBO") next bar at longFBOPoint stop;
Monitor Market Action and Place Trades Accordingly

 

if(barCount>= waitPeriodMins/BarInterval and canTrade = 1) then

Forces the logic to flow only if canTrade is 1 and we have waited for amateur hour to be completed – well 30 minutes to be accurate.  Is the first hour really amateur hour?  I don’t think this applies, but if you think it does this is how you control trading prior to the completion of this period.  By dividing by BarInterval and counting each bar you can generalize this code for any time resolution.   If MarketPosition is 1 then you know you entered a long position and the opposite is true for short positions.  Only place the break out orders if time is less than initTradesEndTime.  If the market penetrates the long and shortBreakPts, then prepare to take advantage of a failed breakout.  Only go short if a short position has not already been entered – same for longs.  So, this logic places the breakOut and failedBreakOut orders.  Now for the last module.

{The next module keeps track of positions and places protective stops}

mp = marketPosition;
if(MarketPosition = 1) then
begin
longLiqPoint = EntryPrice-protStopPrcnt1*averageRange;
longLiqPoint = MinList(longLiqPoint,EntryPrice - protStopAmt);
longLiqPoint1 = EntryPrice - protStopPrcnt2*averageRange;
longLiqPoint1 = MinList(longLiqPoint1,EntryPrice - protStopAmt);
if Maxpositionprofit >= breakEvenPrcnt*averageRange*bigPointValue then
begin
longLiqPoint = EntryPrice; {Breakeven trade}
longLiqPoint1 = EntryPrice; {Breakeven trade}
end;
if(Time >= initTradesEndTime) then
begin
longLiqPoint = MaxList(longLiqPoint,Lowest(Low,3)); {Trailing stop}
longLiqPoint1 = MaxList(longLiqPoint1,Lowest(Low,3)); {Trailing stop}
end;
if(Time < liqRevEndTime and sellsToday = 0 and
longLiqPoint <> EntryPrice and BarsSinceEntry >= 4) then
SellShort("LongLiqRev") next bar at longLiqPoint stop;

Sell("LongLiq-BO") from entry("LBreakOut") next bar at longLiqPoint stop;
Sell("LongLiq-FBO") from entry("BFailedBO") next bar at longLiqPoint stop;
Sell("LongLiq-RLoss") from entry("ShortLiqRev") next bar at longLiqPoint1 stop;
end;
if(MarketPosition =-1) then
begin
shortLiqPoint = EntryPrice+protStopPrcnt1*averageRange;
shortLiqPoint = MaxList(shortLiqPoint,EntryPrice + protStopAmt);
shortLiqPoint1 = EntryPrice + protStopPrcnt2*averageRange;
shortLiqPoint1 = MaxList(shortLiqPoint1,EntryPrice + protStopAmt);
if maxPositionProfit >= breakEvenPrcnt*averageRange*bigPointValue then
begin
shortLiqPoint = EntryPrice; {Breakeven trade}
shortLiqPoint1 = EntryPrice;
end;
if(Time >= initTradesEndTime) then
begin
shortLiqPoint = MinList(shortLiqPoint,Highest(High,3)); {Trailing stop}
shortLiqPoint1 = MinList(shortLiqPoint1,Highest(High,3)); {Trailing stop}
end;
if(Time < liqRevEndTime and buysToday = 0 and
shortLiqPoint <> EntryPrice and BarsSinceEntry >= 4) then
Buy("ShortLiqRev") next bar at shortLiqPoint stop;

BuyToCover("ShortLiq-BO") from entry("SBreakOut") next bar at shortLiqPoint stop;
BuyToCover("ShortLiq-FBO") from entry("SFailedBO") next bar at shortLiqPoint stop;
BuyToCover("ShortLiq-RLoss") from entry("LongLiqRev") next bar at shortLiqPoint1 stop;
end;
end;
SetExitOnClose;
TradeManagement (Enter on Stop Loss or Not?)

This code looks a little hairy, but its not.  Let’s just look at the long side logic to save time here.  First let’s calculate the LongLiqPoints (1 and 2.)  Twenty years ago I thought it would be better to have a smaller stop for entries that occurred on a LiquidationReversal.  Oh yeah that code is in here to.  Back in the day I wanted to make sure the stop was at least 3 handles – ha, ha, ha – no really I am serious.  Really.  Stop laughing!! That code could be eliminated.  After calculating these two points I start to monitor profit and if it reaches a predetermined level I pull the the longLiqPoints toa  BreakEven stop.  If you are fortunate to still be in a trade after initTradesEndTime, then I start trailing the stop by the lowest low of the last 3 five minute bars – I don’t want to turn a small winner into a loser.  Now this is the fun stuff.

  1. if(Time < liqRevEndTime and sellsToday = 0 and
    longLiqPoint <> EntryPrice and BarsSinceEntry >= 4) then
  2.      SellShort(“LongLiqRev”) next bar at longLiqPoint stop;

If time is less than liqRevEndTime and BarsSinceEntry, then reverse and go short at the longLiqPoint stop.  Do this instead of liquidating.  I thought if the market reversed course quickly, then I wanted to take advantage of this counter trend move.  Eliminating this to see if it has any impact would be where I would start to play around with the template.  Okay now the liquidations based on from Entry take place next.  If I am long from a “ShortLiqRev“, then I use longLiqPoint1 instead of longLiqPoint.  Okay that last part was the kitchen sink.  Now you have enough code to make your own day trading system – really too much code, but you should be able to hobble something together from these parts.  Let me know if you can create your own Frankenstein monster.  I will update the parameters to see if there is any hope to the system as a whole.  Keep checking back for updated performance metrics.  Best to all and be safe!

 

 

A Quant’s ToolBox: Beautiful Soup, Python, Excel and EasyLanguage

Many Times It Takes Multiple Tools to Get the Job Done

Just like a mechanic, a Quant needs tools to accomplish many programming tasks.  In this post, I use a toolbox to construct an EasyLanguage function that will test a date and determine if it is considered a Holiday in the eyes of the NYSE.

Why a Holiday Function?

TradeStation will pump holiday data into a chart and then later go back and take it out of the database.  Many times the data will only be removed from the daily database, but still persist in the intraday database.  Many mechanical day traders don’t want to trade on a shortened holiday session or use the data for indicator/signal calculations.  Here is an example of a gold chart reflecting President’s Day data in the intra-day data and not in the daily.

Holiday Data Throws A Monkey Wrench Into the Works

This affects many stock index day traders.  Especially if automation is turned on.  At the end of this post I provide a link to my youTube channel for a complete tutorial on the use of these tools to accomplish this task.  It goes along with this post.

First Get The Data

I searched the web for a list of historical holiday dates and came across this:

Historic List of Holidays and Their Dates

You might be able to find this in a easier to use format, but this was perfect for this post.

Extract Data with Beautiful Soup

Here is where Python and the plethora of its libraries come in handy.  I used pip to install the requests and the bs4 libraries.  If this sounds like Latin to you drop me an email and I will shoot you some instructions on how to install these libraries.  If you have Python, then you have the download/install tool known as pip.

Here is the Python code.  Don’t worry it is quite short.

# Created:     24/02/2020
# Copyright: (c) George 2020
# Licence: <your licence>
#-------------------------------------------------------------------------------

import requests
from bs4 import BeautifulSoup

url = 'http://www.market-holidays.com/'
page = requests.get(url)
soup = BeautifulSoup(page.text,'html.parser')
print(soup.title.text)
all_tables = soup.findAll('table')
#print (all_tables)
print (len(all_tables))
#print (all_tables[0])
print("***")
a = list()
b = list()
c = list()
#print(all_tables[0].find_all('tr')[0].text)
for numTables in range(len(all_tables)-1):
for rows in all_tables[numTables].find_all('tr'):
a.append(rows.find_all('td')[0].text)
b.append(rows.find_all('td')[1].text)

for j in range(len(a)-1):
print(a[j],"-",b[j])
Using Beautiful Soup to Extract Table Data

As you can see this is very simple code.  First I set the variable url to the website where the holidays are located.  I Googled on how to do this – another cool thing about Python – tons of users.  I pulled the data from the website and stuffed it into the page object.  The page object has several attributes (properties) and one of them  is a text representation of the entire page.  I pass this text to the BeautifulSoup library and inform it to parse it with the html.parser.  In other words, prepare to extract certain values based on html tags.  All_tables contains all of the tables that were parsed from the text file using Soup.  Don’t worry how this works, as its not important, just use it as a tool.  In my younger days as a programmer I would have delved into how this works, but it wouldn’t be worth the time because I just need the data to carry out my objective; this is one of the reasons classically trained programmers never pick up the object concept.  Now that I have all the tables in a list I can loop through each row in each table.  It looked liker there were 9 rows and 2 columns in the different sections of the website, but I didn’t know for sure so I just let the library figure this out for me.  So I played around with the code and found out that the first two columns of the table contained the name of the holiday and the date of the holiday.  So, I simply stuffed the text values of these columns in two lists:  a and b.  Finally I print out the contents of the two lists, separated by a hyphen, into the Interpreter window.  At this point I could simply carry on with Python and create the EasyLanguage statements and fill in the data I need.  But I wanted to play around with Excel in case readers didn’t want to go the Python route.  I could have used a powerful editor such as NotePad++ to extract the data from the website in place of Python.  GREP could have done this.  GREP is an editor tool to find and replace expressions in a text file.

Use Excel to Create Actual EasyLanguage – Really!

I created a new spreadsheet.  I used Excel, but you could use any spreadsheet software.   I first created a prototype of the code I would need to encapsulate the data into array structures.  Here is what I want the code to look like:

Arrays: holidayName[300](""),holidayDate[300](0);

holidayName[1]="New Year's Day "; holidayDate[1]=19900101;
Code Prototype

This is just the first few lines of the function prototype.  But you can notice a repetitive pattern.  The array names stay the same – the only values that change are the array elements and the array indices.  Computers love repetitiveness.  I can use this information a build a spreadsheet – take a look.

Type EasyLanguage Into the Columns and Fill Down!

I haven’t copied the data that I got out of Python just yet.  That will be step 2.  Column A has the first array name holidayName (notice I put the left square [ bracket in the column as well).  Column B will contain the array index and this is a formula.  Column C contains ]=”.  Column D will contain the actual holiday name and Column E contains theThese columns will build the holidayName array.  Columns G throuh K will build the holidayDates array.    Notice column  H  equals column B.  So whatever we do to column B (Index) will be reflected in Column H (Index).  So we have basically put all the parts of the EasyLanguage into  Columns A thru K. 

Excel provides tools for manipulating strings and text.  I will use the Concat function to build my EasyLanguageBut before I can use Concat all the stuff I want to string together must be in a string or text format.  The only column in the first five that is not a string is Column B.  So the first thing I have to do is convert it to text.  First copy the column and paste special as values.  Then go to your Data Tab and select Text To Columns. 

Text To Columns

It will ask if fixed width or delimited – I don’t think it matters which you pick.  On step 3 select text.

Text To Columns – A Powerful Tool

The Text To Columns button will solve 90% of your formatting issues in Excel.    Once you do this you will notice the numbers will be left justified – this signifies a text format.  Now lets select another sheet in the workbook and past the holiday data.

Copy Holiday Data Into Another Spreadsheet

New Year's Day - January 1, 2021
Martin Luther King, Jr. Day - January 18, 2021
Washington's Birthday (Presidents' Day) - February 15, 2021
Good Friday - April 2, 2021
Memorial Day - May 31, 2021
Independence Day - July 5, 2021
Labor Day - September 6, 2021
Thanksgiving - November 25, 2021
Christmas - December 24, 2021
New Year's Day - January 1, 2020
Martin Luther King, Jr. Day - January 20, 2020
Washington's Birthday (Presidents' Day) - February 17, 2020
Good Friday - April 10, 2020
Memorial Day - May 25, 2020
Holiday Output

 

Data Is In Column A

Text To Columns to the rescue.  Here I will separate the data with the “-” as delimiter and tell Excel to import the second column in Date format as MDY.  

Text To Columns with “-” as the delimiter and MDY as Column B Format

Now once the data is split accordingly into two columns with the correct format – we need to convert the date column into a string.

Convert Date to a String

Now the last couple of steps are really easy.  Once you have converted the date to a string, copy Column A and past into Column D from the first spreadsheet.  Since this is text, you can simply copy and then paste.  Now go back to Sheet 2 and copy Column C and paste special [values] in Column J on Sheet 1.  All we need to do now is concatenate the strings in Columns A thru E for the EasyLanguage for the holidayName array.  Columns G thru K will be concatenated for the holidayDate array.  Take a look.

Concatenate all the strings to create the EasyLanguage

Now create a function in the EasyLanguage editor and name it IsHoliday and have it return a boolean value.  Then all you need to do is copy/paste Columns F and L and the data from the website will now be available for you use.   Here is a portion of the function code.  Notice I declare the holidayNameStr as a stringRef?  I did this so I could change the variable in the function and pass it back to the calling routine.

Inputs : testDate(numericSeries),holidayNameStr(stringRef);

Arrays: holidayName[300](""),holidayDate[300](0);

holidayNameStr = "";

holidayName[1]="New Year's Day "; holidayDate[1]=19900101;
holidayName[2]="Martin Luther King, Jr. Day "; holidayDate[2]=19900115;
holidayName[3]="Washington's Birthday (Presidents' Day) "; holidayDate[3]=19900219;
holidayName[4]="Good Friday "; holidayDate[4]=19900413;
holidayName[5]="Memorial Day "; holidayDate[5]=19900528;
holidayName[6]="Independence Day "; holidayDate[6]=19900704;
holidayName[7]="Labor Day "; holidayDate[7]=19900903;
holidayName[8]="Thanksgiving "; holidayDate[8]=19901122;
holidayName[9]="New Year's Day "; holidayDate[9]=19910101;
holidayName[10]="Martin Luther King, Jr. Day "; holidayDate[10]=19910121;
holidayName[11]="Washington's Birthday (Presidents' Day) "; holidayDate[11]=19910218;

// There are 287 holiays in the database.
// Here is the looping mechanism to compare the data that is passed
// to the database

vars: j(0);
IsHoliday = False;
For j=1 to 287
Begin
If testDate = holidayDate[j] - 19000000 then
Begin
holidayNameStr = holidayName[j] + " " + numToStr(holidayDate[j],0);
IsHoliday = True;
end;
end;
A Snippet Of The Function - Including Header and Looping Mechanism

This was a pretty long tutorial and might be difficult to follow along.  If you want to watch my video, then go to this link.

I created this post to demonstrate the need to have several tools at your disposal if you really want to become a Quant programmer.  How you use those tools is up to you.  Also you will be able to take bits and pieces out of this post and use in other ways to get the data you really need.  I could have skipped the entire Excel portion of the post and just did everything in Python.  But I know a lot of Quants that just love spreadsheets.  You have to continually hone your craft in this business.   And you can’t let one software application limit your creativity.  If you have a problem always be on the lookout for alternative platforms and/or languages to help you solve it.

 

 

Free Trend Following System with Indicator Tracker

Free Trend Following System

Here is a free Trend Following System that I read about on Andreas Clenow’s www.followthetrend.com website and from his book.  This is my interpretation of the rules as they were explained.  However the main impetus behind this post wasn’t to provide a free trading system, but to show how you can program a simple system with a complete input interface and program a tracking indicator.   You might be asking what is a “tracking indicator?”  We use a tracking indicator to help provide insight to what the strategy is doing and what it might do in the near future.  The indicator can let you know that a new signal is imminent and also what the risk is in a graphical form.  The indicator can also plot the indicators that are used in the strategy itself.

Step 1:  Program the Strategy

This system is very simple.  Trade on a 50 day Donchian in the direction of the trend and use a 3 X ATR trailing stop.  So the trend is defined as bullish when the 50-day exponential moving average is greater than the 100-day exponential moving average.  A bearish trend is defined when the 50-day is below the 100-day.  Long positions are initiated on the following day when a new 50 day high has been established and the trend is bullish.  Selling short occurs when the trend is bearish and a new 50 day low is establish.  The initial stop  is set to 3 X ATR below the high of the day of entry.  I tested using a 3 X ATR stop initially from the entryPrice for protection on the day of entry, but it made very little difference.  As the trade moves more into your favor, the trailing stop ratchets up and tracks the higher intra-trade extremes.  Eventually once the market reverses you get stopped out of a long position 3 X ATR from the highest high since you entered the long trade.  Hopefully, with a big winner.   The Clenow model also uses a position sizing equation that uses ATR to determine market risk and $2000 for the allocated amount to risk.  Size= 2000 / ATR – this equation will normalize size across a portfolio of markets.

Here is the code.

//Based on Andreas Clenow's description from www.followingthetrend.com
//This is my interpretation and may or may not be what Andreas intended
//Check his books out at amazon.com
//
inputs: xAvgShortLen(50),xAvgLongLen(100),hhllLen(50),buyTrigPrice(h),shortTrigPrice(l),risk$Alloc(2000);
inputs: atrLen(30),trailATRMult(3);
vars: avg1(0),avg2(0),lXit(0),sXit(0),posSize(0),atr(0);

avg1 = xaverage(c,xAvgShortLen);
avg2 = xaverage(c,xAvgLongLen);

atr = avgTrueRange(atrLen);
posSize = maxList(1,intPortion(risk$Alloc/(atr*bigPointValue)));

If marketPosition <> 1 and avg1 > avg2 and buyTrigPrice = highest(buyTrigPrice,hhllLen) then buy posSize contracts next bar at open;
If marketPosition <> -1 and avg1 < avg2 and shortTrigPrice = lowest(shortTrigPrice,hhllLen) then sellshort posSize contracts next bar at open;

If marketPosition = 0 then
Begin
lXit = o - trailATRMult * atr ;
sXit = o + trailATRMult * atr;
// if c < lXit then Sell currentcontracts contracts next bar at open;
// If c > sXit then buyToCover currentcontracts contracts next bar at open;
end;

If marketPosition = 1 then
begin
lXit = maxList(lXit,h - trailATRMult * atr);
If c < lXit then sell currentContracts contracts next bar at open;
end;

If marketPosition = -1 then
begin
sXit = minList(sXit,l + trailATRMult * atr);
If c > sXit then buyToCover currentContracts contracts next bar at open;
end;
Cleanow Simple Trend Following System

What I like about this code is how you can use it as a template for any trend following approach.  All the variables that could be optimized are included as inputs.  Many may not know that you can actually change the data series that you want to use as your signal generator right in the input.  Here I have provided two inputs : buyTrigPrice(H), shortTrigPrice(L).  If you want to use the closing price, then all you need to do is change the H and L to C.  The next lines of code performs the calculations needed to calculate the trend.  PosSize is then calculated next.  Here I am dividing the variable risk$Alloc by atr*bigPointValue.  Basically I am taking $2000 and dividing the average true range over the past 30 days multiplied by the point value of the market being tested.  Always remember when doing calculations with $s you have to convert whatever else you are using into dollars as well.  The ATR is expressed in the form of a price difference.  You can’t divide dollars by a price component, hence the multiplication by bigPointValue.  So now we have the trend calcuation and the position sizing taken care of and all we need now is the trend direction and the entry levels.  If avg1 > avg2 then the market is in a bullish posture, and if today’s High = highest(High,50) days back then initiate a long position with posSize contracts at the next bar’s openNotice how I used the keyword contracts after posSize.  This let’s TS know that I want to trade more than one contract.  If the current position is flat I set the lXit and sXit price levels to the open -/+ 3 X ATR.  Once a position (long or short) is initiated then I start ratcheting the trailing stop up or down.  Assuming a long position, I compare the current lXit and the current bar’s HIGH- 3 X ATR and take the larger of the two valuesSo lXit always moves up and never down.  Notice if the close is less than lXit I used the keyword currentContracts and contracts in the directive to exit a long trade.  CurrentContracts contains the current number of contracts currently long and contracts informs TS that more than one contract is being liquidated.  Getting out of a short position is exactly the same but in a different direction.

Step 2: Program the System Tracking Indicator

Now you can take the exact code and eliminate all the order directives and use it to create a tracking indicator.  Take a look at this code:

//Based on Andreas Clenow's description from www.followingthetrend.com
//This is my interpretation and may or may not be what Andreas intended
//Check his books out at amazon.com
//
inputs: xAvgShortLen(50),xAvgLongLen(100),hhllLen(50),buyTrigPrice(h),shortTrigPrice(l);
inputs: atrLen(30),trailATRMult(3);
vars: avg1(0),avg2(0),lXit(0),sXit(0),posSize(0),atr(0),mp(0);

avg1 = xaverage(c,xAvgShortLen);
avg2 = xaverage(c,xAvgLongLen);

atr = avgTrueRange(atrLen);

plot1(avg1,"stXavg");
plot2(avg2,"ltXavg");

If avg1[1] > avg2[1] and buyTrigPrice[1] = highest(buyTrigPrice[1],hhllLen) then mp = 1;
If avg1[1] < avg2[1] and shortTrigPrice[1] = lowest(shortTrigPrice[1],hhllLen) then mp = -1;

If mp = 0 then
Begin
lXit = o - trailATRMult * atr ;
sXit = o + trailATRMult * atr;
end;

If mp = 1 then
begin
lXit = maxList(lXit,h - trailATRMult * atr);
plot3(lXit,"LongTrail");
If c < lXit then mp = 0;
end;

If mp = -1 then
begin
sXit = minList(sXit,l + trailATRMult * atr);
plot4(sXit,"ShortTrail");
If c > sXit then mp = 0;
end;

However, you do need to keep track if the underlying strategy is long or short and you can do this by pretending you are the computer and using the mp variable.  You know if yesterdays avg1 > avg2 and HIGH[1] = highestHigh(HIGH[1],50), then a long position should have been initiated.  If this happens just set mp to 1You set mp to -1 by checking the trend and lowestLow(LOW[1],50).  Once you know the mp or implied market position then you can calculate the lXit and sXit.  You will always plot the moving averages to help determine trend direction, but you only plot the lXit and sXit when a position is on.  So plot3 and plot4 should only be plotted when a position is long or short.

Here is a screenshot of the strategy and tracking indicator.

Notice how the Yellow and Cyan plots follow the correct market position.  You will need to tell TS not to connect these plot lines when they are not designed to be plotted.

Turn-Off Auto Plot Line Connection

Do this for Plot3 and Plot4 and you will be good to go.

I hope you found this post useful.  Also don’t forget to check out my new book at Amazon.com.  If you really want to learn programming that will help across different platforms I think it would be a great learning experience.

 

A Christmas Project for TradeStation Day-Traders

Here is a neat little day trader system that takes advantage of what some technicians call a “CLEAR OUT” trade.  Basically traders push the market through yesterday’s high and then when everybody jumps on board they pull the rug out from beneath you.  This strategy tries to take advantage of this.  As is its OK, but it could be made into a complete system with some filtering.  Its a neat base to start your day-trading schemes from.

But first have you ever encountered this one when you only want to go long once during the day.

I have logic that examines marketPosition, and if it changes from a non 1 value to 1 then I increment buysToday.  Since there isn’t an intervening bar to establish a change in marketPosition, then buysToday does not get incremented and another buy order is issued.  I don’t want this.  Remember to plot on the @ES.D.

Here’s how I fixed it and also the source of the CLEAR-OUT day-trade in its entirety.  I have a $500 stop and a $350 take profit, but it simply trades way too often.  Have fun with this one – let me now if you come up with something.

inputs: clearOutAmtPer(0.1),prot$Stop(325),prof$Obj(500),lastTradeTime(1530);

vars: coBuy(false),coSell(false),buysToday(0),sellsToday(0),mp(0),totNumTrades(0);

If d <> d[1] then
Begin
coBuy = false;
coSell = false;
buysToday = 0;
sellsToday = 0;
totNumTrades = totalTrades;
end;


mp = marketPosition;
If mp[1] <> mp and mp = 1 then buysToday = buysToday + 1;
If mp[1] <> mp and mp = -1 then sellsToday = sellsToday + 1;

If h > highD(1) + clearOutAmtPer * (highD(1) - lowD(1)) then coSell = true;
If l < lowD(1) - clearOutAmtPer * (highD(1) - lowD(1)) then coBuy = true;

If totNumTrades <> totalTrades and mp = 0 and mp[1] = 0 and positionProfit(1) < 0 and entryPrice(1) > exitPrice(1) then buysToday = buysToday + 1;
If totNumTrades <> totalTrades and mp = 0 and mp[1] = 0 and positionProfit(1) < 0 and entryPrice(1) < exitPrice(1) then sellsToday =sellsToday + 1;

totNumTrades = totalTrades;

If buysToday = 0 and t < lastTradeTime and coBuy = true then buy ("COBuy") next bar at lowD(1) + minMove/priceScale stop;
If sellsToday = 0 and t < lastTradeTime and coSell = true then sellShort ("COSell") next bar at highD(1) - minMove/priceScale stop;

setStopLoss(prot$stop);
Setprofittarget(prof$Obj);
setExitOnClose;
Look at lines 22 and 23 - the entry/exit same bar fix

Testing Keith Fitschen’s Bar Scoring with Pattern Smasher

Keith’s Book

Thanks to MJ for planting the seed for this post.  If you were one of the lucky ones to get Keith’s “Building Reliable Trading SystemsTradable Strategies that Perform as They Backtest and Meet Your Risk-Reward Goals”  book by John Wiley 2013 at the list price of $75 count yourself lucky.  The book sells for a multiple of that on Amazon.com.  Is there anything earth shattering in the book you might ask?  I wouldn’t necessarily say that, but there are some very well thought out and researched topics that most traders would find of interest.

Bar Scoring

In his book Keith discusses the concept of bar-scoring.  In Keith’s words, “Bar-scoring is an objective way to classify an instrument’s movement potential every bar.  The two parts of the bar-scoring are the criterion and the resultant profit X days hence.”  Keith provides several bar scoring techniques, but I highlight just one.

Keith broke these patterns down into the relationship of the close to the open, and close in the upper half of the range; close greater than the open and close in the lower half of the range.  He extended the total number of types to 8 by adding the relationship of the close of the bar to yesterdays bar.

The PatternSmasher code can run through a binary representation

for each pattern and test holding the position for an optimizable number of days.  It can also check for long and short positions.  The original Pattern Smasher code used a for-loop to create patterns that were then compared to the real life facsimile.  In this code it was easier to just manually define the patterns and assign them the binary string.

if c[0]> c[1] and c[0] > o[0] and c[0] > (h[0] + l[0])/2  then patternString = "----";
if c[0]> c[1] and c[0] > o[0] and c[0] < (h[0] + l[0])/2 then patternString = "---+";
if c[0]> c[1] and c[0] < o[0] and c[0] > (h[0] + l[0])/2 then patternString = "--+-";
if c[0]> c[1] and c[0] < o[0] and c[0] < (h[0] + l[0])/2 then patternString = "--++";
if c[0]< c[1] and c[0] > o[0] and c[0] > (h[0] + l[0])/2 then patternString = "-+--";
if c[0]< c[1] and c[0] > o[0] and c[0] < (h[0] + l[0])/2 then patternString = "-+-+";
if c[0]< c[1] and c[0] < o[0] and c[0] > (h[0] + l[0])/2 then patternString = "-++-";
if c[0]< c[1] and c[0] < o[0] and c[0] < (h[0] + l[0])/2 then patternString = "-+++";
Manual Pattern Designations

Please check my code for any errors.  Here I go through the 8 different relationships and assign them to a Patter String.  “-+++”  represents pattern number (7 ) or type (7 + 1 = 8 – my strings start out at 0).  You can then optimize the test pattern and if the test pattern matches the actual pattern, then the Pattern Smasher takes the trade  on the opening of the next bar and holds it for the number of days you specify.  You an also designate long and short positions in the code.  Here I optimized the 8 patterns going long and short and holding from 1-4 days.

Here is the equity curve!  Remember these are Hypothetical Results with $0 commission/slippage and historic performance is not necessarily indicative of future results.  Educational purposes only!  This is tested on ES.D

Play around with the code and let me know if you find any errors or any improvements.

input: patternTests(8),orbAmount(0.20),LorS(1),holdDays(0),atrAvgLen(10),enterNextBarAtOpen(true);

var: patternTest(""),patternString(""),tempString("");
var: iCnt(0),jCnt(0);
array: patternBitChanger[4](0);

{written by George Pruitt -- copyright 2019 by George Pruitt
This will test a 4 day pattern based on the open to close
relationship. A plus represents a close greater than its
open, whereas a minus represents a close less than its open.
The default pattern is set to pattern 14 +++- (1110 binary).
You can optimize the different patterns by optimizing the
patternTests input from 1 to 16 and the orbAmount from .01 to
whatever you like. Same goes for the hold days, but in this
case you optimize start at zero. The LorS input can be
optimized from 1 to 2 with 1 being buy and 2 being sellshort.}

patternString = "";
patternTest = "";

patternBitChanger[0] = 0;
patternBitChanger[1] = 0;
patternBitChanger[2] = 0;
patternBitChanger[3] = 0;

value1 = patternTests - 1;


//example patternTests = 0 -- > 0000
//example patternTests = 1 -- > 0001
//example patternTests = 2 -- > 0010
//example patternTests = 3 -- > 0011
//example patternTests = 4 -- > 0100
//example patternTests = 5 -- > 0101
//example patternTests = 6 -- > 0110
//example patternTests = 7 -- > 0111

if(value1 >= 0) then
begin

if(mod(value1,2) = 1) or value1 = 1 then patternBitChanger[0] = 1;
value2 = value1 - patternBitChanger[0] * 1;

if(value2 >= 7) then begin
patternBitChanger[3] = 1;
value2 = value2 - 8;
end;

if(value2 >= 4) then begin
patternBitChanger[2] = 1;
value2 = value2 - 4;
end;
if(value2 = 2) then patternBitChanger[1] = 1;
end;

for iCnt = 3 downto 0 begin
if(patternBitChanger[iCnt] = 1) then
begin
patternTest = patternTest + "+";
end
else
begin
patternTest = patternTest + "-";
end;
end;

patternString = "";

if c[0]> c[1] and c[0] > o[0] and c[0] > (h[0] + l[0])/2 then patternString = "----";
if c[0]> c[1] and c[0] > o[0] and c[0] < (h[0] + l[0])/2 then patternString = "---+";
if c[0]> c[1] and c[0] < o[0] and c[0] > (h[0] + l[0])/2 then patternString = "--+-";
if c[0]> c[1] and c[0] < o[0] and c[0] < (h[0] + l[0])/2 then patternString = "--++";
if c[0]< c[1] and c[0] > o[0] and c[0] > (h[0] + l[0])/2 then patternString = "-+--";
if c[0]< c[1] and c[0] > o[0] and c[0] < (h[0] + l[0])/2 then patternString = "-+-+";
if c[0]< c[1] and c[0] < o[0] and c[0] > (h[0] + l[0])/2 then patternString = "-++-";
if c[0]< c[1] and c[0] < o[0] and c[0] < (h[0] + l[0])/2 then patternString = "-+++";


if(barNumber = 1) then print(elDateToString(date)," pattern ",patternTest," ",patternTests-1);
if(patternString = patternTest) then
begin

// print(date," ",patternString," ",patternTest); //uncomment this and you can print out the pattern
if (enterNextBarAtOpen) then
begin
if(LorS = 2) then SellShort("PatternSell") next bar on open;
if(LorS = 1) then buy("PatternBuy") next bar at open;
end
else
begin
if(LorS = 2) then SellShort("PatternSellBO") next bar at open of tomorrow - avgTrueRange(atrAvgLen) * orbAmount stop;
if(LorS = 1) then buy("PatternBuyBO") next bar at open of tomorrow + avgTrueRange(atrAvgLen) * orbAmount stop;
end;


end;

if(holdDays = 0 ) then setExitonClose;
if(holdDays > 0) then
begin
if(barsSinceEntry = holdDays and LorS = 2) then BuyToCover("xbarLExit") next bar at open;
if(barsSinceEntry = holdDays and LorS = 1) then Sell("xbarSExit") next bar at open;
end;
Bar Scoring Testing Template

How To Program A Ratcheting Stop in EasyLanguage

30 Minute Break Out utilizing a Ratchet Stop [7 point profit with 6 point retention]
I have always been a big fan of trailing stops.  They serve two purposes – lock in some profit and give the market room to vacillate.  A pure trailing stop will move up as the market makes new highs, but a ratcheting stop (my version) only moves up when a certain increment or multiple of profit has been achieved.  Here is a chart of a simple 30 minute break out on the ES day session.  I plot the buy and short levels and the stop level based on whichever level is hit first.

When you program something like this you never know what is the best profit trigger or the best profit retention value.  So, you should program this as a function of these two values.  Here is the code.

inputs: ratchetAmt(6),trailAmt(6);
vars:longMult(0),shortMult(0),myBarCount(0);
vars:stb(0),sts(0),buysToday(0),shortsToday(0),mp(0);
vars:lep(0),sep(0);

If d <> d[1] then
Begin
longMult = 0;
shortMult = 0;
myBarCount = 0;
mp = 0;
lep = 0;
sep = 0;
buysToday = 0;
shortsToday = 0;
end;

myBarCount = myBarCount + 1;

If myBarCount = 6 then // six 5 min bars = 30 minutes
Begin
stb = highD(0); //get the high of the day
sts = lowD(0); //get low of the day
end;

If myBarCount >= 6 and buysToday + shortsToday = 0 and high >= stb then
begin
mp = 1; //got long - illustrative purposes only
lep = stb;

end;
If myBarCount >=6 and buysToday + shortsToday = 0 and low <= sts then begin
mp = -1; //got short
sep = sts;
end;

If myBarCount >=6 then
Begin
plot3(stb,"buyLevel");
plot4(sts,"shortLevel");
end;
If mp = 1 then buysToday = 1;
If mp =-1 then shortsToday = 1;


// Okay initially you want a X point stop and then pull the stop up
// or down once price exceeds a multiple of Y points
// longMult keeps track of the number of Y point multipes of profit
// always key off of lep(LONG ENTRY POINT)
// notice how I used + 1 to determine profit
// and - 1 to determine stop level
If mp = 1 then
Begin
If h >= lep + (longMult + 1) * ratchetAmt then longMult = longMult + 1;
plot1(lep + (longMult - 1) * trailAmt,"LE-Ratchet");
end;

If mp = -1 then
Begin
If l <= sep - (shortMult + 1) * ratchetAmt then shortMult = shortMult + 1;
plot2(sep - (shortMult - 1) * trailAmt,"SE-Ratchet");
end;
Ratcheting Stop Code

So, basically I set my multiples to zero on the first bar of the trading session.  If the multiple = 0 and you get into a long position, then your initial stop will be entryPrice + (0 – 1) * trailAmt.  In other words your stop will be trailAmt (6 in this case) below entryPrce.  Once price exceeds or meets 7 points above entry price, you increment the multiple (now 1.)  So, you stop becomes entryPrice + (1-1) * trailAmt – which equals a break even stop.  This logic will always move the first stop to break even.  Assume the market moves 2 multiples into profit (14 points), what would your stop be then?

stop = entryPrice + (2 – 1) * 6 or entryPrice + 6 points.

See how it ratchets.  Now you can optimized the profit trigger and profit retention values.  Since I am keying of entryPrice your first trailing stop move will be a break-even stop.

This isn’t a strategy but it could very easily be turned into one.

Question on Multiple Time Indicator [Discrete Bars]

A reader of this blog proffered an excellent question on this indicator.  I hope this post answers his question and I am always open to any input that might improve my coding!

Because I use BarNumber in my MODULUS calculation the different time frames that I keep track of may not align with the time frames on the chart; your 10-minute bar O, H, L, and C values may not align with the values I am storing in my 10-minute bar container.    Take a look at this snapshot of a spreadsheet.

Here I  print out a 5-minute bar of the ES.D.  Because I use BarNumber in my Modulus calculation, I don’t get to a zero remainder until  9:50 in the 10, 15, and 20 minute time frames.  At 9:50 I start building fresh 10, 15, 20 minute bars by resetting the O, H, L and C to those of the 5-minute bars.  From there I keep track of the highest highs and lowest lows by extracting the data from the 5-minute bar.  I always set the close of the different time frames to the current 5-minute bar’s close.   Once the modulus for the different time frames reaches zero I close out the bar and start fresh again.  The 25-minute bar didn’t reach zero until the 10:05 bar.

I will see if I can come up with some code that will sync with the data on the chart.

Passing a Two Dimensional Array to a Function- EasyLanguage

In this post, I want to share some code that I was surprised wasn’t really all that accessible.  I was in need of passing a 2-D array to a function and couldn’t remember the exact syntax.  The semantics of the problem is pretty straightforward.

  • Build Array
  • Pass Array as Reference
  • Unpack Array
  • Do Calculation

A 2D Array Is Just Like a Table

Any readers please correct me if I am wrong here, but you can’t use dynamic arrays on any dimension greater than 1.  A dynamic array is one where you don’t initially know the size of the array so you leave it blank and TradeStation allocates memory dynamically.  Also, there are a plethora of built-in functions that only work with dynamic arrays.  Once we step up in dimension then that all goes out the window.  I know what you are thinking, just use multiple dynamic arrays.  Sometimes you want to keep the accounting down to a minimum and a matrix or table fits this bill.  So if you do use multi-dimension arrays just remember you will need to know the total number of rows and columns in your table.  Table?  What do you mean table?  I thought we were talking about arrays.  Well, we are and a two-dimensional array can look like a table with rows as your first index and columns as your second.  Just like an Excel spreadsheet.  First, let’s create a very small and simple table in EasyLangauge:

array: testArray[2,2](0);

Once
begin
testArray[0,0] = 100;
testArray[0,1] = 5;

testArray[1,0] = 200;
testArray[1,1] = 10;

testArray[2,0] = 300;
testArray[2,1] = 7.5;

Value2 = getArrayHH(testArray,2,2);
Print (value2);

end;
Create a Very Small Table in Our Sandbox

 

My EasyLanguage Sandbox

You will notice I used the keyword Once.  I use this whenever I want to play around with some code in my EasyLanguage Sandbox.  Huh?  In programmer-ese a Sandbox is a quick and dirty environment that runs very quickly and requires nearly zero overhead.  So here I apply the code to print out just one line of output when applied to any chart.   Notice how I declare the 2-D array – use the keyword Array: and the name of the array or table and allocate the total number of rows as the first argument and the total number of columns as the second argument.  Also notice the arguments are separated by a comma and enclosed in square brackets.  The following value enclosed in parentheses is the default value of every element in the array.    Remember arrays are zero-based in EasyLanguage.  So if you dimension an array with the number 2 you access the rows with 0 and 1 and 2.  Same goes for columns as well.  Did you catch that.  If you dimension an array with the number 2 shouldn’t there be just 2 rows?  Well in EasyLanguage when you dimension an array you get a free element at row 0 and column 0.  In EasyLanguage you can just ignore row 0 and column 0 if you like.  Here is the code if you ignore row 0 and column 0.

Should I Use Row 0 and Column Zero – It’s A Preference

array: testArray[2,2](0);

Once
begin
testArray[1,1] = 100;
testArray[1,2] = 5;

testArray[2,1] = 200;
testArray[2,2] = 10;

Value2 = getArrayHH(testArray,2,2);
Print (value2);

end;
Ignore the Elements at Row 0 and Column 0

Out Of Bounds

Even though you get one free row you still cannot go beyond the boundaries of the array size.  If I were to say something like:

testArray[3,1] = 300;

I would get an error message.  If you want to work with a zero element then all of your code must coincide with that.  If not, then your code shouldn’t try to access row 0 or column 0.    Okay here is the function that I programmed for this little test:

inputs: tempArray[x,y](numericArray),numOfRows(numericSimple),whichColumn(numericSimple);

vars: j(0),tempHi(0),cnt(0);

For j= 1 to numOfRows
Begin
print(j," ",tempArray[j,whichColumn]);
If tempArray[j,whichColumn] > tempHi then tempHi = tempArray[j,whichColumn];
end;

GetArrayHH = tempHi;
Function That Utilizes a 2D Array

Notice in the inputs how I declare the tempArray with the values x and y.  You could have used a and b if you like or any other letters.  This informs the compiler to expect a 2D array.  It doesn’t know the size and that’s not important as long as you control the boundaries from the calling routine.  The second parameter is the number of rows in the table and the third parameter is the column I am interested in.  In this example, I am interested in column 2.

The Caller Function is the QuarterBack – Make Sure You Don’t Throw it Out of Bounds

Again this function assumes the caller will prevent stepping out of bounds.  I loop the number of rows in the table and examine the second column and keep track of the highest value.  I then return the highest column value.

This was a simple post, but remembering the syntax can be tough and know that EasyLangauge is zero-based when it comes to arrays is nice to know.   You can also use this format for your own Sandbox.

 

 

MULTI-TIME FRAME – KEEPING TRACK OF DISCRETE TIME FRAMES

Just a quick post here.  I was asked how to keep track of the opening price for each time frame from our original Multi-Time Frame indicator and I was answering the question when I thought about modifying the indicator.  This version keeps track of each discrete time frame.  The original simply looked back a multiple of the base chart to gather the highest highs and lowest lows and then would do a simple calculation to determine the trend.  So let’s say its 1430 on a five-minute bar and you are looking back at time frame 2.  All I did was get the highest high and lowest low two bars back and stored that information as the high and low of time frame 2.  Time frame 3 simply looked back three bars to gather that information.  However if you tried to compare these values to a 10-minute or 15-minute chart they would not match.

In this version, I use the modulus function to determine the demarcation of each time frame.  If I hit the border of the time frame I reset the open, high, low and carry that value over until I hit the next demarcation.  All the while collecting the highest highs and lowest lows.  In this model, I am working my way from left to right instead of right to left.  And in doing so each time frame is discrete.

Let me know which version you like best.

 

Inputs:tf1Mult(2),tf2Mult(3),tf3Mult(4),tf4Mult(5);



vars: mtf1h(0),mtf1l(0),mtf1o(0),mtf1c(0),mtf1pvt(0),diff1(0),
mtf2h(0),mtf2l(0),mtf2o(0),mtf2c(0),mtf2pvt(0),diff2(0),
mtf3h(0),mtf3l(0),mtf3o(0),mtf3c(0),mtf3pvt(0),diff3(0),
mtf4h(0),mtf4l(0),mtf4o(0),mtf4c(0),mtf4pvt(0),diff4(0),
mtf0pvt(0),diff0(0);

If barNumber = 1 then
Begin
mtf1o = o;
mtf2o = o;
mtf3o = o;
mtf4o = o;
end;


If barNumber > 1 then
Begin

Condition1 = mod((barNumber+1),tf1Mult) = 0;
Condition2 = mod((barNumber+1),tf2Mult) = 0;
Condition3 = mod((barNumber+1),tf3Mult) = 0;
Condition4 = mod((barNumber+1),tf4Mult) = 0;

mtf1h = iff(not(condition1[1]),maxList(high,mtf1h[1]),high);
mtf1l = iff(not(condition1[1]),minList(low,mtf1l[1]),low);
mtf1o = iff(condition1[1],open,mtf1o[1]);
mtf1c = close;


mtf0pvt = (close + high + low) / 3;
diff0 = close - mtf0pvt;

mtf2h = iff(not(condition2[1]),maxList(high,mtf2h[1]),high);
mtf2l = iff(not(condition2[1]),minList(low,mtf2l[1]),low);
mtf2o = iff(condition2[1],open,mtf2o[1]);
mtf2c = close;


mtf1pvt = (mtf1h+mtf1l+mtf1c) / 3;
diff1 = mtf1c - mtf1pvt;

mtf2pvt = (mtf2h+mtf2l+mtf2c) / 3;
diff2 = mtf2c - mtf2pvt;

mtf3h = iff(not(condition3[1]),maxList(high,mtf3h[1]),high);
mtf3l = iff(not(condition3[1]),minList(low,mtf3l[1]),low);
mtf3o = iff(condition3[1],open,mtf3o[1]);
mtf3c = close;

mtf3pvt = (mtf3h+mtf3l+mtf3c) / 3;
diff3 = mtf3c - mtf3pvt;

mtf4h = iff(not(condition4[1]),maxList(high,mtf4h[1]),high);
mtf4l = iff(not(condition4[1]),minList(low,mtf4l[1]),low);
mtf4o = iff(condition4[1],open,mtf4o[1]);
mtf4c = close;

mtf4pvt = (mtf4h+mtf4l+mtf4c) / 3;
diff4 = mtf4c - mtf4pvt;


Condition10 = diff0 > 0;
Condition11 = diff1 > 0;
Condition12 = diff2 > 0;
Condition13 = diff3 > 0;
Condition14 = diff4 > 0;

If condition10 then setPlotColor(1,Green) else SetPlotColor(1,Red);
If condition11 then setPlotColor(2,Green) else SetPlotColor(2,Red);
If condition12 then setPlotColor(3,Green) else SetPlotColor(3,Red);
If condition13 then setPlotColor(4,Green) else SetPlotColor(4,Red);
If condition14 then setPlotColor(5,Green) else SetPlotColor(5,Red);

condition6 = condition10 and condition11 and condition12 and condition13 and condition14;
Condition7 = not(condition10) and not(condition11) and not(condition12) and not(condition13) and not(condition14);

If condition6 then setPlotColor(7,Green);
If condition7 then setPlotColor(7,Red);

If condition6 or condition7 then plot7(7,"trend");

Plot6(5,"line");
Plot1(4,"t1");
Plot2(3,"t2");
Plot3(2,"t3");
Plot4(1,"t4");
Plot5(0,"t5");

end;
Multi-Time Frame with Discrete Time Frames

Using a Dictionary to Create a Trading System

Dictionary Recap

Last month’s post on using the elcollections dictionary was a little thin so I wanted to elaborate on it and also develop a trading system around the best patterns that are stored in the dictionary.  The concept of the dictionary exists in most programming languages and almost all the time uses the (key)–>value model.  Just like a regular dictionary a word or a key has a unique definition or value.  In the last post, we stored the cumulative 3-day rate of return in keys that looked like “+ + – –” or “+ – – +“.  We will build off this and create a trading system that finds the best pattern historically based on average return.  Since its rather difficult to store serial data in a Dictionary I chose to use Wilder’s smoothing average function.

Ideally, I Would Have Liked to Use a Nested Dictionary

Initially, I played around with the idea of the pattern key pointing to another dictionary that contained not only the cumulative return but also the frequency that each pattern hit up.  A dictionary is designed to have  unique key–> to one value paradigm.  Remember the keys are strings.  I wanted to have unique key–> to multiple values. And you can do this but it’s rather complicated.  If someone wants to do this and share, that would be great.  AndroidMarvin has written an excellent manual on OOEL and it can be found on the TradeStation forums.  

Ended Up Using A Dictionary With 2*Keys Plus an Array

So I didn’t want to take the time to figure out the nested dictionary approach or a vector of dictionaries – it gets deep quick.  So following the dictionary paradigm I came up with the idea that words have synonyms and those definitions are related to the original word.  So in addition to having keys like “+ + – -” or “- – + -” I added keys like “0”, “1” or “15”.  For every  + or – key string there exists a parallel key like “0” or “15”.  Here is what it looks like:

–  –  –  –  = “0”
– – – + = “1”
– – + – = “2”

You can probably see the pattern here.  Every “+” represents a 1 and every “0” represent 0 in a binary-based numbering system.  In the + or – key I store the last value of Wilders average and in the numeric string equivalent, I store the frequency of the pattern.

Converting String Keys to Numbers [Back and Forth]

To use this pattern mapping I had to be able to convert the “++–” to a number and then to a string.  I used the numeric string representation as a dictionary key and the number as an index into an array that store the pattern frequency.  Here is the method I used for this conversion.  Remember a method is just a function local to the analysis technique it is written.

//Lets convert the string to unique number
method int convertPatternString2Num(string pattString)
Vars: int pattLen, int idx, int pattNumber;
begin
pattLen = strLen(pattString);
pattNumber = 0;
For idx = pattLen-1 downto 0
Begin
If MidStr(pattString,pattLen-idx,1) = "+" then pattNumber = pattNumber + power(2,idx);
end;
Return (pattNumber);
end;
String Pattern to Number

This is a simple method that parses the string from left to right and if there is a “+” it is raised to the power(2,idx) where idx is the location of “+” in the string.  So “+  +  –  –  ” turns out to be 8 + 4 + 0 + 0 or 12.

Once I retrieve the number I used it to index into my array and increment the frequency count by one.  And then store the frequency count in the correct slot in the dictionary.

patternNumber = convertPatternString2Num(patternString); 
//Keep track of pattern hits
patternCountArray[patternNumber] = patternCountArray[patternNumber] + 1;
//Convert pattern number to a string do use as a Dictionary Key
patternStringNum = numToStr(patternNumber,2);
//Populate the pattern number string key with the number of hits
patternDict[patternStringNum] = patternCountArray[patternNumber] astype double;
Store Value In Array and Dictionary

Calculating Wilder’s Average Return and Storing in Dictionary

Once I have stored an instance of each pattern [16] and the frequency of each pattern[16] I calculate the average return of each pattern and store that in the dictionary as well.

//Calculate the percentage change after the displaced pattern hits
Value1 = (c - c[2])/c[2]*100;
//Populate the dictionary with 4 ("++--") day pattern and the percent change
if patternDict.Contains(patternString) then
Begin
patternDict[patternString] = (patternDict[patternString] astype double *
(patternDict[patternStringNum] astype double - 1.00) + Value1) / patternDict[patternStringNum] astype double;
end
Else
begin
patternDict[patternString] = value1;
// print("Initiating: ",patternDict[patternString] astype double);
end;
(pAvg * (N-1) + return) / N

When you extract a value from a collection you must us an identifier to expresses its data type or you will get an error message : patternDict[patternString] holds a double value {a real number}  as well as patternDict[patternStringNum] – so I have to use the keyword asType.  Once I do my calculation I ram the new value right back into the dictionary in the exact same slot.  If the pattern string is not in the dictionary (first time), then the Else statement inserts the initial three-day rate of return.

Sort Through All of The Patterns and Find the Best!

The values in a dictionary are stored in alphabetic order and the string patterns are arranged in the first 16 keys.  So I loop through those first sixteen keys and extract the highest return value as the “best pattern.”

//  get the best pattern that produces the best average 3 bar return
vars: hiPattRet(0),bestPattString("");
If patternDict.Count > 29 then
Begin
index = patternDict.Keys;
values = patternDict.Values;
hiPattRet = 0;
For iCnt = 0 to 15
Begin
If values[iCnt] astype double > hiPattRet then
Begin
hiPattRet = values[iCnt] astype double ;
bestPattString = index[iCnt] astype string;
end;
end;
// print(Date," BestPattString ",bestPattString," ",hiPattRet:8:4," CurrPattString ",currPattString);
end;
Extract Best Pattern From All History

If Today’s Pattern Matches the Best Then Take the Trade

// if the current pattern matches the best pattern then bar next bar at open
If currPattString = BestPattString then buy next bar at open;
// cover in three days
If barsSinceEntry > 2 then sell next bar at open;
Does Today Match the Best Pattern?

If today matches the best pattern then buy and cover after the second day.

Conclusion

I didn’t know if this code was worth proffering up but I decided to posit it because it contained a plethora of programming concepts: dictionary, method, string manipulation, and array.  I am sure there is a much better way to write this code but at least this gets the point across.

Contents of Dictionary at End of Run

++++    0.06
+++- -0.08
++-+ 0.12
++-- -0.18
+-++ 0.08
+-+- 0.40
+--+ -0.46
+--- 0.34
-+++ 0.20
-++- 0.10
-+-+ 0.23
-+-- 0.31
--++ 0.02
--+- 0.07
---+ 0.22
---- 0.46
0.00 103.00
1.00 128.00
10.00 167.00
11.00 182.00
12.00 146.00
13.00 168.00
14.00 163.00
15.00 212.00
2.00 157.00
3.00 133.00
4.00 143.00
5.00 181.00
6.00 151.00
7.00 163.00
8.00 128.00
9.00 161.00
Contents of Dictionary

Example of Trades

Pattern Dictionary System

 

Code in Universum

//Dictionary based trading sytem
//Store pattern return
//Store pattern frequency
// by George Pruitt
Using elsystem.collections;

vars: string keystring("");
vars: dictionary patternDict(NULL),vector index(null), vector values(null);
array: patternCountArray[100](0);

input: patternTests(8);

var: patternTest(""),tempString(""),patternString(""),patternStringNum("");
var: patternNumber(0);
var: iCnt(0),jCnt(0);
//Lets convert the string to unique number
method int convertPatternString2Num(string pattString)
Vars: int pattLen, int idx, int pattNumber;
begin
pattLen = strLen(pattString);
pattNumber = 0;
For idx = pattLen-1 downto 0
Begin
If MidStr(pattString,pattLen-idx,1) = "+" then pattNumber = pattNumber + power(2,idx);
end;
Return (pattNumber);
end;


once begin
clearprintlog;
patternDict = new dictionary;
index = new vector;
values = new vector;
end;

//Convert 4 day pattern displaced by 2 days
patternString = "";
for iCnt = 5 downto 2
begin
if(close[iCnt]> close[iCnt+1]) then
begin
patternString = patternString + "+";
end
else
begin
patternString = patternString + "-";
end;
end;

//What is the current 4 day pattern
vars: currPattString("");
currPattString = "";

for iCnt = 3 downto 0
begin
if(close[iCnt]> close[iCnt+1]) then
begin
currPattString = currPattString + "+";
end
else
begin
currPattString = currPattString + "-";
end;
end;

//Get displaced pattern number
patternNumber = convertPatternString2Num(patternString);
//Keep track of pattern hits
patternCountArray[patternNumber] = patternCountArray[patternNumber] + 1;
//Convert pattern number to a string do use as a Dictionary Key
patternStringNum = numToStr(patternNumber,2);
//Populate the pattern number string key with the number of hits
patternDict[patternStringNum] = patternCountArray[patternNumber] astype double;
//Calculate the percentage change after the displaced pattern hits
Value1 = (c - c[2])/c[2]*100;
//Populate the dictionary with 4 ("++--") day pattern and the percent change
if patternDict.Contains(patternString) then
Begin
patternDict[patternString] = (patternDict[patternString] astype double *
(patternDict[patternStringNum] astype double - 1.00) + Value1) / patternDict[patternStringNum] astype double;
end
Else
begin
patternDict[patternString] = value1;
// print("Initiating: ",patternDict[patternString] astype double);
end;
// get the best pattern that produces the best average 3 bar return
vars: hiPattRet(0),bestPattString("");
If patternDict.Count > 29 then
Begin
index = patternDict.Keys;
values = patternDict.Values;
hiPattRet = 0;
For iCnt = 0 to 15
Begin
If values[iCnt] astype double > hiPattRet then
Begin
hiPattRet = values[iCnt] astype double ;
bestPattString = index[iCnt] astype string;
end;
end;
// print(Date," BestPattString ",bestPattString," ",hiPattRet:8:4," CurrPattString ",currPattString);
end;
// if the current pattern matches the best pattern then bar next bar at open
If currPattString = BestPattString then buy next bar at open;
// cover in three days
If barsSinceEntry > 2 then sell next bar at open;
Pattern Dictionary Part II