Category Archives: Free EasyLanguage

Updated Pattern Smasher in EasyLanguage

Update To Original Pattern Smasher

What will you learn : string manipulation, for-loops, optimization

Before proceeding I would suggest reading my original post on this subject.    If you believe the relationship of the last few bars of data can help determine future market direction, then this post will be in you wheel house.  Another added benefit is that you will also learn some cool EasyLanguage.

Original post was limited to four day patterns!

This version is limitless (well not really, but pretty close).  Let’s stick with the original string pattern nomenclature (+ + – – : two up closes followed by two down closes.)  Let’s also stick with our binary pattern representation:

Pattern # 2^3 2^2 2^1 1
3 0 0 1 1
4 0 1 0 0
5 0 1 0 1
6 0 1 1 1

Remember a 0 represents a down close and a 1 represents an up close.  We will deviate from the original post by doing away with the array and stick with only strings (which are really just arrays of characters.)  This way we won’t have to worry about array manipulation.

How to create a dynamic length string pattern

This was the difficult part of the programming.  I wanted to be able to optimize 3, 4 and 5 day patterns and I wanted to control this with using just inputs.  I discovered that pattern three is different in a three day pattern than it is in a four day pattern: in a three day pattern it is 011 or – + + and in a four day pattern it is 0011 or – – + +.  Since I am counting 0’s as down closes, pattern #3 depends on the ultimate size of the pattern string.  No worries I will have eventually have another version where I utilize a different value for down closes and we can then have holes in our string patterns.  But I digress – so to differentiate the patterns based on the pattern length I included a maxPatternLen input.  So if maxPatternLen is three and we are trying to match pattern #3 then we will be looking for 011 and not 0011.  That was an easy fix.  But then I wanted to build a string pattern based on this input and the pattern number dynamically.  Here is some psuedo code on how I figured it out.


{Psuedo code to translate pattern number into binary number}
patternNumber = 3
maxPatternLen = 3

numBits = 0 // stick with binary representation
testValue = 0 // temporary test value
numBits = maxPatternLen-1 // how many bits will it take to get to the
// center of - or numBits to represent max
// number of patterns or 2^numBits
currentBit =numBits // start wit current bit as total numBits

value1 = patternOptTest // value1 represents current pattern number
testString = "" // build test string from ground up


for icnt = numBits downto 0 //building string from left to right
begin // notice keyword downto
if power(2,currentBit) > value1 then // must use power function in EL
begin // if the very far left bit value >
testString = testString + "-" // patten number then plug in a "-"
end
else
begin // else plug in a "+" and deccrement by
testString = testString + "+" // that bits value - if its the 3rd bit
value1 = value1 - power(2,currentBit)// then decrement by 8
end;
currentBit = currentBit - 1 // move onto the next bit to the right
end;
Pseudocode for Binary Representation of Pattern #

Now if you want to optimize then you must make sure your pattern number search space or range can be contained within maxPatternLen.  For example, if you want to test all the different combinations of a four day pattern, then your maxPatternLen would naturally be four and you would optimize the pattern number from 0 to 15.  Don’t use 1-16 as I use zero as the base.  A five day pattern would include the search space from 0 – 31.  The rest of the code was basically hacked from my original post.   Here is the rest of the code to do optimizations on different length pattern strings.  Notice how I use strings, for-loops and comparisons.

input: buyPattern("+++-"),sellPattern("---+"),patternOptimize(True),patternOptTest(7),maxPatternLen(3),patternOptBuySell(1),
stopLoss$(2000),profitTarg$(2000),holdDays(5);
vars: buyPatternString(""),sellPatternString(""),buyPatternMatch(""),sellPatternMatch(""),numBits(0),testValue(0),currentBit(0),
remainder(0),value(0),icnt(0),testString(""),numCharsInBuyPattern(0),numCharsInSellPattern(0);
vars:okToBuy(false),okToSell(false);

buyPatternMatch = buyPattern;
sellPatternMatch = sellPattern;
numCharsInBuyPattern = strLen(buyPatternMatch);
numCharsInSellPattern = strLen(sellPatternMatch);

If patternOptimize then
begin
numBits = 0;
testValue = 0;
value = maxPatternLen;
numBits = maxPatternLen-1;
currentBit =numBits;
remainder = patternOptTest;
testString = "";
for icnt = numBits downto 0
begin
if power(2,currentBit) > remainder then {note this originally had value1 instead of remainder}
begin
testString = testString + "-";
end
else
begin
testString = testString + "+";
remainder = remainder - power(2,currentBit);
end;
currentBit = currentBit - 1;
end;
numCharsInBuyPattern = maxPatternLen;
numCharsInSellPattern = maxPatternLen;
if patternOptBuySell = 1 then
Begin
buyPatternMatch = testString;
sellPatternMatch = "0";
end;
If patternOptBuySell = 2 then
Begin
buyPatternMatch = "0";
sellPatternMatch = testString;
end;
end;


buyPatternString = "";
sellPatternString = "";

For icnt = numCharsInBuyPattern-1 downto 0
Begin
If close[icnt] >= close[icnt+1] then buyPatternString = buyPatternString + "+";
If close[icnt] < close[icnt+1] then buyPatternString = buyPatternString + "-";
end;
For icnt = numCharsInSellPattern-1 downto 0
Begin
If close[icnt] >= close[icnt+1] then sellPatternString = sellPatternString + "+";
If close[icnt] < close[icnt+1] then sellPatternString = sellPatternString + "-";
end;


okToBuy = false;
okToSell = false;

if buyPatternMatch <> "" then
If buyPatternString = buyPatternMatch then okToBuy = true;
If buyPatternMatch = "" then
okToBuy = true;
If sellPattern <> "" then
If sellPatternString = sellPatternMatch then okToSell = true;
If sellPatternMatch = "" then
okToSell = true;

If okToBuy then buy next bar at open;
If okToSell then sellshort next bar at open;

If marketPosition = 1 and barsSinceEntry > holdDays then sell next bar at open;
If marketPosition = -1 and barsSinceEntry > holdDays then buytocover next bar at open;

setStopLoss(stopLoss$);
setProfitTarget(profitTarg$);

If lastBarOnChart then print(d," ",buyPatternMatch);
Final Version of New Pattern Smasher

Also see how I incorporate a profit target and protective stop.  I use the built in BarsSinceEntry function to count the number of days I am in a trade so I can utilize a time based exit.  Here is an interesting equity curve I developed using a two day pattern ( – –) to go long.

Register on the website and I will email you an ELD of the improved Pattern Smasher.  Or just shoot me an email.

 

 

Making Trading Decisions on Current Month’s Profit/Loss

Keeping track of intra-month profit or loss

In real time trading I have noticed that once you reach a certain loss for the month its best, sometimes, to circle the wagons and quit trading until the beginning of the next month.  This concept works best for very short term or day trade algorithms, as its very easy to get started back up.  You can do this with Trend Following, but you must build a logical and replicable process for re-entering existing positions.  Let’s assume a trading algorithm whose averaging losing month is $1500 and you are currently down $2000 – what are the chances that you will revert to the mean or draw down further?  Probably 50/50.  Who knows you might turn around and actually make money by month’s end.  If you review a track record of a hedge fund manager, trader, or algorithm and they show a bar chart of monthly returns and there sticking out like a sore thumb is a big down bar, that kind of makes you think that could happen again.  If you can control the monthly downside without sacrificing the existing Profit:DrawDown ratio, then why not do it.

Sample Code To Monitor IntraMonth $P/L

if month(date) <> month(date[1]) then
Begin
begMonthProf = netProfit;
print(d," ",t," ",begMonthProf);
canTrade = true;
end;
Capture Beginning Of Month Net Profit

Here I am comparing the month of the current bar against the month of the prior bar.  If they are not equal, then we have a new month.  Store the netProfit in the variable begMonthProf.  All you have to do is compare the current bar’s netProfit to begMonthProf and make a decision.  Here is some code:

Making a Trading Decision Based on Monthly $P/L

		If dayOfMonth(date) > 15 and begMonthProf - netProfit >= intraMonthMaxLoss then canTrade = false;
If Down MaxLoss for Month and Past Mid-Month - Quit Trading

If the day of the month is greater than 15 (month half over) and the difference between the current netProfit and begMonthProfit is greater than a negative intraMonthMaxLoss then quit trading for the month.  Only turn it back on the first bar of the next month.  See how this works for your algos.

How to Create a Dominant Cycle Class in Python

John Ehlers used the following EasyLanguage code to calculate the Dominant Cycle in a small sample of data.  If you are interested in cycles and noise reduction, definitely check out the books by John Ehlers – “Rocket Science for Traders” or “Cybernetic Analysis for Stocks and Futures.”  I am doing some research in this area and wanted to share how I programmed the indicator/function in Python.  I refer you to his books or online resources for an explanation of the code.  I can tell you it involves an elegantly simplified approach using the Hilbert Transform.

 

Inputs:	Price((H+L)/2);

Vars: Imult(.635),
Qmult (.338),
InPhase(0),
Quadrature(0),
count(0),
Re(0),
Im(0),
DeltaPhase(0),
InstPeriod(0),
Period(0);

If CurrentBar > 8 then begin
Value1 = Price - Price[7];
Inphase = 1.25*(Value1[4] - Imult*Value1[2]) + Imult*InPhase[3];

// print(price," ",price[7]," ",value1," ",inPhase," ",Quadrature," ",self.im[-1]," ",self.re[-1])
// print(d," ",h," ",l," ",c," ",Value1[4]," ",Imult*Value1[2]," ", Imult*InPhase[3]," ",Inphase);
Quadrature = Value1[2] - Qmult*Value1 + Qmult*Quadrature[2];
Re = .2*(InPhase*InPhase[1] + Quadrature*Quadrature[1]) + .8*Re[1];
Im = .2*(InPhase*Quadrature[1] - InPhase[1]*Quadrature) + .8*Im[1];
print(d," ",o," ",h," ",l," ",c," ",value1," ",inPhase," ",Quadrature," ",Re," ",Im);
If Re <> 0 then DeltaPhase = ArcTangent(Im/Re);

{Sum DeltaPhases to reach 360 degrees. The sum is the instantaneous period.}
InstPeriod = 0;
Value4 = 0;
For count = 0 to 50 begin
Value4 = Value4 + DeltaPhase[count];
If Value4 > 360 and InstPeriod = 0 then begin
InstPeriod = count;
end;
end;

{Resolve Instantaneous Period errors and smooth}
If InstPeriod = 0 then InstPeriod = InstPeriod[1];
Period = .25*InstPeriod + .75*Period[1];

Plot1(Period, "DC");
EasyLanguage Code For Calculating Dominant Cycle

In my Python based back tester an indicator of this type is best programmed by using a class.  A class is really a simple construct, especially in Python, once you familiarize yourself with the syntax.   This indicator requires you to refer to historical values to calculate the next value in the equation:  Value1[4], inPhase[1], re[2], etc.,.  In EasyLanguage these values are readily accessible as every variable is defined as a BarArray – the complete history of a variable is accessible by using indexing.  In my PSB I used lists to store values for those variables most often used such as Open, High, Low, Close.  When you need to store the values of let’s say the last five bars its best to just create a list on the fly or build them into a class structure.  A Class stores data and data structures and includes the methods (functions) that the data will be pumped into.  The follow code describes the class in two sections:  1) data declaration and instantiation and 2) the function to calculate the Dominant Cycle.  First off I create the variables that will hold the constant values: imult and qmult.  By using the word self I make these variables class members and can access them using “.” notation.  I will show you later what this means.  I also make the rest of the variables class members, but this time I make them lists and instantiate the first five values to zero.  I use list comprehension to create the lists and zero out the first five elements – all in one line of code.  This is really just a neat short cut, but can be used for much more powerful applications.  Once you create a dominantCycleClass object the object is constructed and all of the data is connected to this particular object.  You can create many dominantCycleClass objects and each one would maintain its own data.  Remember a class is just a template that is used to create an object.

class dominantCycleClass(object):
def __init__(self):
self.imult = 0.635
self.qmult = 0.338
self.value1 = [0 for i in range(5)]
self.inPhase = [0 for i in range(5)]
self.quadrature = [0 for i in range(5)]
self.re = [0 for i in range(5)]
self.im = [0 for i in range(5)]
self.deltaPhase = [0 for i in range(5)]
self.instPeriod = [0 for i in range(5)]
self.period = [0 for i in range(5)]
Data Portion of Class

 

The second part of the class template contains the method or function for calculating the Dominant Cycle.  Notice how I index into the lists to extract prior values.  You will also see the word self. preceding the variable names used in the calculations Initially I felt like this redundancy hurt the readability of the code and in this case it might.  But by using self. I know I am dealing with a class member.  This is an example of the ” . ” notation I referred to earlier.  Basically this ties the variable to the class.

def calcDomCycle(self,dates,hPrices,lPrices,cPrices,curBar,offset):
tempVal1 = (hPrices[curBar - offset] + lPrices[curBar-offset])/2
tempVal2 = (hPrices[curBar - offset - 7] + lPrices[curBar-offset - 7])/2
self.value1.append(tempVal1 - tempVal2)
self.inPhase.append(1.25*(self.value1[-5] - self.imult*self.value1[-3]) + self.imult*self.inPhase[-3])
self.quadrature.append(self.value1[-3] - self.qmult*self.value1[-1] + self.qmult*self.quadrature[-2])
self.re.append(.2*(self.inPhase[-1]*self.inPhase[-2]+self.quadrature[-1]*self.quadrature[-2])+ 0.8*self.re[-1])
self.im.append(.2*(self.inPhase[-1]*self.quadrature[-2] - self.inPhase[-2]*self.quadrature[-1]) +.8*self.im[-1])
if self.re[-1] != 0.0: self.deltaPhase.append(degrees(atan(self.im[-1]/self.re[-1])))
if len(self.deltaPhase) > 51:
self.instPeriod.append(0)
value4 = 0
for count in range(1,51):
value4 += self.deltaPhase[-count]
if value4 > 360 and self.instPeriod[-1] == 0:
self.instPeriod.append(count)
if self.instPeriod[-1] == 0: self.instPeriod.append(self.instPeriod[-1])
self.period.append(.25*self.instPeriod[-1]+.75*self.period[-1])
return(self.period[-1])
Dominant Cycle Method

Okay we now have the class template to calculate the Dominant Cycle but how do we us it?

#---------------------------------------------------------------------------------
#Instantiate Indicator Classes if you need them
#---------------------------------------------------------------------------------
# rsiStudy = rsiClass()
# stochStudy = stochClass()
domCycle = dominantCycleClass()
#---------------------------------------------------------------------------------
#Call the dominantCycleClass method using " . " notation.
tempVal1 = domCycle.calcDomCycle(myDate,myHigh,myLow,myClose,i,0)
#Notice how I can access class members by using " . " notation as well!
tempVal2 = domCycle.imult
Dominant Cycle Object Creation

Here I assign domCycle the object created by calling the dominantCycleClass constructor.  TempVal1 is assigned the Dominant Cycle when the function or method is called using the objects name (domCycle) and the now familiar ” . ” notation.  See how you can also access the imult variable using the same notation.

Here is the code in its entirety.  I put this in the indicator module of the PSB.

class dominantCycleClass(object):
def __init__(self):
self.imult = 0.635
self.qmult = 0.338
self.value1 = [0 for i in range(5)]
self.inPhase = [0 for i in range(5)]
self.quadrature = [0 for i in range(5)]
self.re = [0 for i in range(5)]
self.im = [0 for i in range(5)]
self.deltaPhase = [0 for i in range(5)]
self.instPeriod = [0 for i in range(5)]
self.period = [0 for i in range(5)]

def calcDomCycle(self,dates,hPrices,lPrices,cPrices,curBar,offset):
tempVal1 = (hPrices[curBar - offset] + lPrices[curBar-offset])/2
tempVal2 = (hPrices[curBar - offset - 7] + lPrices[curBar-offset - 7])/2
self.value1.append(tempVal1 - tempVal2)
self.inPhase.append(1.25*(self.value1[-5] - self.imult*self.value1[-3]) + self.imult*self.inPhase[-3])
self.quadrature.append(self.value1[-3] - self.qmult*self.value1[-1] + self.qmult*self.quadrature[-2])
self.re.append(.2*(self.inPhase[-1]*self.inPhase[-2]+self.quadrature[-1]*self.quadrature[-2])+ 0.8*self.re[-1])
self.im.append(.2*(self.inPhase[-1]*self.quadrature[-2] - self.inPhase[-2]*self.quadrature[-1]) +.8*self.im[-1])
if self.re[-1] != 0.0: self.deltaPhase.append(degrees(atan(self.im[-1]/self.re[-1])))
if len(self.deltaPhase) > 51:
self.instPeriod.append(0)
value4 = 0
for count in range(1,51):
value4 += self.deltaPhase[-count]
if value4 > 360 and self.instPeriod[-1] == 0:
self.instPeriod.append(count)
if self.instPeriod[-1] == 0: self.instPeriod.append(self.instPeriod[-1])
self.period.append(.25*self.instPeriod[-1]+.75*self.period[-1])
return(self.period[-1])
Dominant Cycle Class - Python

 

How to Keep Track of BuysToday and SellsToday

The Useful MP

We all know how to use the reserved word/function MarketPosition – right?  Brief summary if not – use MarketPosition to see what your current position is: -1 for short, +1 for long and 0 for flat.  MarketPosition acts like a function because you can index it to see what you position was prior to the current position – all you need to do is pass a parameter for the number of positions ago.  If you pass it a one (MarketPosition(1)) then it will return the your prior position.  If you define a variable such as MP you can store each bars MarketPosition and this can come in handy.

mp = marketPosition;

If mp[1] <> 1 and mp = 1 then buysToday = buysToday + 1;
If mp[1] <> -1 and mp = -1 then sellsToday = sellsToday + 1;
Keeping Track of Buy and Sell Entries on Daily Basis

The code compares prior bar’s MP value with the current bar’s.   If there is a change in the value, then the current market position has changed.   Going from not 1 to 1 indicates a new long position.  Going from not -1 to -1 implies a new short.  If the criteria is met, then the buysToday or sellsToday counters are incremented.  If you want to keep the number of buys or sells to a certain level, let’s say once or twice,  you can incorporate this into your code.

If  time >= startTradeTime and t < endTradeTime and 
buysToday < 1 and
rsi(c,rsiLen) crosses above rsiBuyVal then buy this bar on close;
If time >= startTradeTime and t < endTradeTime and
sellsToday < 1 and
rsi(c,rsiLen) crosses below rsiShortVal then sellShort this bar on close;
Using MP to Keep Track of BuysToday and SellsToday

This logic will work most of the time, but it depends on the robustness of the builtin MarketPosition function Look how this logic fails in the following chart:

I didn't want entries in the same direction per day!
I only wanted 1 short entry per day!

MarketPosition Failure

Failure in the sense that the algorithm shorted twice in the same day.  Notice on the first trade how the profit objective was hit on the very next bar.  The problem with MarketPosition is that it only updates at the end of the bar one bar after the entry.  So MarketPosition stays 0 during the duration of this trade.  If MarketPosition doesn’t change then my counter won’t work.  TradeStation should update MarketPosition at the end of the entry bar.  Alas it doesn’t work this way.  I figured a way around it though.  I will push the code out and explain it later in more detail.

Input: rsiLen(14),rsiBuyVal(30),rsiShortVal(70),profitObj$(250),protStop$(300),startTradeTime(940),endTradeTime(1430);

Vars: mp(0),buysToday(0),sellsToday(0),startOfDayNetProfit(0);

If d <> d[1] then
Begin
buysToday = 0;
sellsToday = 0;
startOfDayNetProfit = netProfit;
end;

{mp = marketPosition;

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

If entriesToday(date) > buysToday + sellsToday then
Begin
If marketPosition = 1 then buysToday = buysToday + 1;
If marketPosition =-1 then sellsToday = sellsToday + 1;
If marketPosition = 0 then
Begin
if netProfit > startOfDayNetProfit then
begin
if exitPrice(1) > entryPrice(1) then buysToday = buysToday + 1;
If exitPrice(1) < entryPrice(1) then sellsToday = sellsToday + 1;
end;;
if netProfit < startOfDayNetProfit then
Begin
if exitPrice(1) < entryPrice(1) then buysToday = buysToday + 1;
If exitPrice(1) > entryPrice(1) then sellsToday = sellsToday + 1;
end;
end;
print(d," ",t," ",buysToday," ",sellsToday);
end;

If time >= startTradeTime and t < endTradeTime and
buysToday < 1 and
rsi(c,rsiLen) crosses above rsiBuyVal then buy this bar on close;
If time >= startTradeTime and t < endTradeTime and
sellsToday < 1 and
rsi(c,rsiLen) crosses below rsiShortVal then sellShort this bar on close;

SetProfittarget(profitObj$);
SetStopLoss(protStop$);

SetExitOnClose;
A Better Buy and Short Entries Counter

TradeStation does update EntriesToday at the end of the bar so you can use this keyword/function to help keep count of the different type of entries.  If MP is 0 and EntriesToday increments then you know an entry and an exit has occurred (takes care of the MarketPosition snafu) – all you need to do is determine if the entry was a buy or a sell.  NetProfit is also updated when a trade is closed.   I establish the StartOfDayNetProfit on the first bar of the day (line 9 in the code) and then examine EntriesToday and if NetProfit increased or decreased.  EntryPrice and ExitPrice are also updated at the end of the bar so I can also use them to extract the information I need.   Since MarketPosition is 0  I have to pass 1 to the EntryPrice and ExitPrice functions – prior position’s prices.  From there I can determine if a Long/Short entry occurred.  This seems like a lot of work for what you get out of it, but if you are controlling risk by limiting the number of trades (exposure) then an accurate count is so very important.

An alternative is to test on a higher resolution of data – say 1 minute bars.  In doing this you give a buffer to the MarketPosition function – more bars to catch up.

 

Pyramiding and then Scaling Out at Different Price Levels – EasyLanguage

TOTAL, TOTAL, TOTAL – an important keyword

I just learned something new!  I guess I never programmed a strategy that pyramided at different price levels and scaled out at different price levels.

Initially I thought no problem.  But I couldn’t get it to work – I tried everything and then I came across the keyword Total and then I remembered.  If you don’t specify Total in you exit directives then the entire position is liquidated.  Unless you are putting all your positions on at one time – like I did in my last post.   So remember if you are scaling out of a pyramid position use Total in your logic.

vars: maxPosSize(2);

If currentContracts < maxPosSize - 1 and c > average(c,50) and c = lowest(c,3) then buy("L3Close") 1 contract this bar on close;
If currentContracts < maxPosSize and c > average(c,50) and c = lowest(c,4) then buy("L4Close") 1 contract this bar on close;


If currentContracts = 2 and c = highest(c,5) then sell 1 contract total this bar on close;
If currentContracts = 1 and c = highest(c,10) then sell 1 contract total this bar on close;
Scaling Out Of Pyramid

Why you have to use the Total I don’t know.  You specify the number of contracts in the directive and that is sufficient if you aren’t pyramiding.  The pyramiding throws a “monkey wrench” in to the works.

Scaling Out of Position with EasyLanguage

First Put Multiple Contracts On:

If c > average(c,200) and c = lowest(c,3) then buy("5Large") 5 contracts this bar on close;
Using keyword contracts to put on multiple positions

Here you specify the number of contracts prior to the keyword contracts.

Easylanguage requires you to create a separate order for each exit.  Let’s say you want to get out of the 5 positions at different times and possibly prices.  Here’s how you do it:

If currentContracts = 5 and c > c[1] then sell 1 contracts this bar on close;
If currentContracts = 4 and c > c[1] then sell 1 contracts this bar on close;
If currentContracts = 3 and c > c[1] then sell 1 contracts this bar on close;
If currentContracts = 2 and c > c[1] then sell 1 contracts this bar on close;
If currentContracts = 1 and c > c[1] then sell 1 contracts this bar on close;
One order for each independent exit

The reserved word currentContracts hold the current position size.  Intuitively this should work but it doesn’t.

{If currentContracts > 0 then sell 1 contract this bar on close;}

You also can’t put order directives in loops.  You can scale out using percentages if you like.

Value1 = 5;

If currentContracts = 5 and c > c[1] then sell 0.2 * Value1 contracts this bar on close;
If currentContracts = 4 and c > c[1] then sell 1 contracts this bar on close;
If currentContracts = 3 and c > c[1] then sell 1 contracts this bar on close;
If currentContracts = 2 and c > c[1] then sell 1 contracts this bar on close;
If currentContracts = 1 and c > c[1] then sell 1 contracts this bar on close;
Using a percentage of original order size

 

That’s all there is to scaling out.  Just remember to have an independent exit order for each position you are liquidating.  You could have just two orders:  scale out of 3 and then just 2.

 

Setting Stop Loss and Profit Target Utilizing EntryPrice with EasyLanguage

One Problem with the “Next Bar” Paradigm – market position nor entryPrice are adjusted by the end of the bar

Whenever I develop a strategy I like to program all of my entries and exits without utilizing TradeStations built-in execution functions.  I just got use to doing this when I started programming in Fortran many years ago.  However, there a few scenarios where this isn’t possible.  If you enter a trade and use the following logic to get you out with a loss or a profit when referencing your entryPrice, you will be surprised with your results.  This is because you are telling the computer to use entryPrice before you know what it is.

This logic is absolutely correct in its intention.  However, TradeStation doesn’t realize you are in a position at the end of the bar and can’t properly reference entryPrice.  Okay so we force TradeStation to only issue orders once it has a valid entryPrice.TradeStation only realizes the correct marketPosition the following day and then issues an order for the next bar.  So we get the one bar delay.  It would be helpful if TradeStation would set the marketPosition at the close of the bar on the bar of entry.   However, you can overcome this with TradeStation’s built-in execution functions.  For some reason these functions know exactly when you get in – you can also get the same results by inserting the respective strategies on the chart.

An Easy Fix Though

But this little bug can creep into other areas of your programming.  Keep an eye on this.

Multiple Ouput function in EasyLanguage

In the Pascal programming language you have Procedures and Functions.  Procedures are used when you want to modify multiple variables within a sub-program.  A function is a sub-program that returns a single value after it has been modified by say a formula.  EasyLanguage combines procedures and functions into one sub-program called a function.  Functions and procedures both have a formal parameter definition –  a list that describes the type of parameters that are being received by the calling program.  In Pascal procedures, you pass the address of the value that you want changed.  By modifying the contents of the address you can pass the value back and forth or in and out of the procedure.  In functions you pass by value.   Remember the parameter in a normal function call is used to instruct something within the body of the function and is not altered (e.g. the number 19 in value1 = average(c,19)).  This value doesn’t need to be modified it’s just used.  Look at the following code:

Here I am modifying mav1, mav2 and mav3 within the function and then passing the values back to the calling strategy/indicator/paintbar.  All functions must return a value so I simply assign the value 1 to the function name.  The key here is the keyword numericRef, once I change the values located in the addresses of mav1, mav2 and mav3 (address are provided by the keyword numericRef), they will be made available to the calling program.  This code allows the function to return more than just one value.

Using TradeStation’s Development Environment Projects

I have started using the TDE’s projects more and more.  Before, when I was working on multiple related files I would lose track of them in the editor tabs, or discover, when working over time on different projects, I would have twenty or thirty files open – this of course would slow the editor down.  Using projects can clean up your workspace and speed up productivity.  Projects have been around forever and most professional IDEs  incorporate them to aid in the organization and productivity of the programmer.

Here is simple Project with three components:  indicator, function, and strategy.

 

 

Notice how you can focus just on the components of the project.

I also like to split the editor window and populate the bottom pane with code I might need to refer.

Check out the multiple output function – geoTriMavIndic.

 

Pyramiding with Python

A reader of the “UATSTB” asked for an example of how to pyramid in the Python System BackTester (PSB).  I had original bug where you couldn’t peel off all of the positions at once.  If you tried then the PSB would crash.  I have now fixed that problem and here are the necessary lines to add on another position after the initial positions is put on.   I am using a simple moving average crossover to initiate the first position and then if the longer term moving average is positive for 4 days in a row I add on another position.  That’s it.  A max of two position only.  The system either gets reversed to the other side, stopped out or takes profits.  Attached in this post is the module that fixes the pyramiding problem and the code for this system in its entirety.   I will also put the fix in the version 2.0 download.

        upCnt = 0
dnCnt = 0
for j in range(4):
if sAverage(myClose,39,i,j) > sAverage(myClose,39,i,j+1):
upCnt += 1
if sAverage(myClose,39,i,j) < sAverage(myClose,39,i,j+1):
dnCnt += 1


#Long Entry Logic
if (mp != 1) and avg1 > avg2 and prevAvg1 < prevAvg2:
profit = 0
price = myClose[i]
tradeName = "DMA Buy"

#Long Pyramid Logic
if (mp == 1) and upCnt == 4:
profit = 0
price = myClose[i]
tradeName = "LongPyra"
Pyramiding the Long Side of a Dual Moving Average

I only put in the summary of code that will create the initial position and then add 1 more.  Notice the highlighted code from line 3 to 7.  Here I am using a simple loop to determine if the the 39-day moving average is increasing/decreasing consecutively over the past four days.  If the upCnt == 4 then I add a long position.  Notice how I test in the Long Pyramid Logic the values of mp and upCnt.  I only go long another position if I am already long 1 and upCnt == 4.  

Here is a print out of some of the trades:

20040923      DMA Buy  1 127.79000       0.00       0.00
20040923 LongPyra 1 127.79000 0.00 0.00
20041006 L-Prof 2 130.79000 5800.00 14560.00
20041116 DMA Short 1 126.14000 0.00 0.00
20041119 ShortPyra 1 128.64000 0.00 0.00
20041201 S-Prof 2 125.64000 3300.00 17860.00
20050121 DMA Buy 1 127.85000 0.00 0.00
20050202 LongPyra 1 126.01000 0.00 0.00
20050222 L-Prof 2 129.01000 3960.00 21820.00
20050418 DMA Short 1 128.18000 0.00 0.00
20050419 S-MMLoss 1 130.28000 -2200.00 19620.00
20050616 DMA Buy 1 131.41000 0.00 0.00
20050621 LongPyra 1 133.02000 0.00 0.00
20050630 L-MMLoss 2 130.48000 -3670.00 15950.00
20050809 DMA Short 1 135.95000 0.00 0.00
20050810 RevShrtLiq 1 137.78000 -1930.00 14020.00
20050810 DMA Buy 1 137.78000 0.00 0.00
20050810 LongPyra 1 137.78000 0.00 0.00
20050829 L-Prof 2 140.98000 6200.00 20220.00
Trade Listing Of DMA with Pyramiding

While I was posting the trades I found something that struck my funny – look at line 5 (highlighted).  The short pyramid trade occurs at a higher price than the initial short – at first I thought I had made a programming error.  So I thought I would double check the code and then do some debugging.  Instead of invoking the debugger which is really cool and easy to use I decided to just print out the results to the console.

        for j in range(4):
if sAverage(myClose,39,i,j) > sAverage(myClose,39,i,j+1):
upCnt += 1
if sAverage(myClose,39,i,j) < sAverage(myClose,39,i,j+1):
dnCnt += 1
if tempDate == 20041119:
print(myDate[i]," ",j," ",sAverage(myClose,39,i,j))

'''Output of debugging using a print statement
20041119 0 130.68692307692308
20041119 1 130.69538461538463
20041119 2 130.74871794871794
20041119 3 130.7723076923077'''
Debugging using Print Statements

As you can see the longer term moving average is moving down event though price has increased.  Take a look at this chart and you can see multiple occurrences of this.

Examples of Divergence of Moving Average and Price

Remember to copy and replace the tradeClass.py in you PSB2.0 directory – this fixes the pyramid bug.  Also copy the DMAPyra.py to the same directory.  If you haven’t as of yet download the PSB from this website and buy the book for a very good description.

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