The concept of Scope when it comes to a programming language can get very confusing very quickly. If you are new to programming and you think Scope is a mouthwash, no worries here. I will give a full explanation of Scope in terms of programming with the help of ChatGPT. Its response is italicized.
In Python, the scope of a variable refers to the region of the program where that variable can be accessed or referenced. There are two types of scopes in Python: global scope and local scope.
Here’s an example that demonstrates the concept of scope in Python:
# global variable x = 10
def my_func(): # local variable y = 5 print("x inside my_func:", x) # x is accessed from the global scope print("y inside my_func:", y) # y is accessed from the local scope
print("x outside my_func:", x) # x is accessed from the global scope print("y outside my_func:") # y is not defined in the global scope, so this will raise a NameError
Example of Scope as demonstrated by Chat-GPT
In this example, we define a global variable x with a value of 10.
We then define a function my_func that has a local variable y with a value of 5. Inside the function, we print the values of x and y. The variable x is accessed from the global scope, which means it can be referenced from anywhere in the program.
The variable y, on the other hand, is only accessible within the function, which is the local scope. Outside the function, we print the value of x again, which is still accessible from the global scope. However, when we try to print the value of y, we get a NameError because y is not defined in the global scope.
Okay that was pretty formal. In simpler terms, a variable declared inside a function can only be seen inside that function, unless it is declared globally. Another thing about Scope, is that the variables have amnesia. Once you step out of the function the variable forgets what it was, and you can’t refer to its prior value upon return to the function.
Unless you are an EasyLanguage function. Scope is still constrained by an EasyLanguage function, because it is a separate piece of code held within the library of Analysis Techniques. Most of the time you can’t see what’s in the function unless you open it with the ELEditor. However, the variables that are defined inside the function do not suffer from amnesia. If you need to refer to a prior value of a locally declared variable, you can. This type of function is what EasyLanguage calls a Serial function. The only downside to this function is it slows processing down quite a bit.
Okay. To make a long story short I wanted to show the magic of EasyLanguage function that I have been working with on a project. This project includes some of Ehlers’ cycle analysis functions. The one I am going to discuss today is the HighRoof function – don’t worry I am not going to go into detail of what this function does. If you want to know just GOOGLE it or ask ChatGPT. I developed a strategy that used the function on the last 25 days of closing price data. I then turned around and fed the output of the first pass of the HighRoof function right back into the HighRoof function. Something similar to embedding functions.
doubleSmooth = average(average(c,20),20);
Sort of like a double smoothed moving average. After I did this, I started thinking does the function remember the data from its respective call? The first pass used closing price data, so its variables and their history should be in terms of price data. The second pass used the cyclical movements data that was output by the initial call to the HighRoof function. Everything turned out fine, the function remembered the correct data. Or seemed like it did. This is how you learn about any programming language – pull out your SandBox and do some testing. First off, here is my conversion of Ehlers’ HighRoof function in EasyLanguage.
This function requires just two inputs – the data (with a history) and a simple length or cut period. The first input is of type numericSeries and the second input is of type numericSimple. You will see the following line of code
Starting at the top of the output you will see that on 1230206 the function was called twice with two different sets of data. As you can see the output of the first two lines is of a different magnitude. The first line is approximately an order or magnitude of 10 of the second line. If you go to lines 3 and 4 you will see the highPass of lines 1 and 2 moves to highPass and then onto highPass. I think what happens internally is for every call on per bar basis, the variables for each function call are pushed into a queue in memory. The queue continues to grow for whatever length is necessary and then either maintained or truncated at some later time.
Why Is This So Cool?
In many languages the encapsulation of data with the function requires additional programming. The EasyLanguage function could be seen as an “object” like in object-oriented programming. You just don’t know you are doing it. EasyLanguage takes care of a lot of the behind-the-scenes data management. To do the same thing in Python you would need to create a class of Ehlers Roof that maintain historic data in class members and the calculations would be accomplished by a class method. In the case of calling the function twice, you would instantiate two classes from the template and each class would act independent of each other.
One last nugget of information. If you are going to be working with trigonometric functions such as Cosine, Sine or Tangent, make sure your arguments are in degrees not radians. In Python, you must use radians.
I had to wrap up Part -1 rather quickly and probably didn’t get my ideas across, completely. Here is what we did in Part – 1.
used my function to locate the First Notice Date in crude
used the same function to print out exact EasyLanguage syntax
chose to roll eight days before FND and had the function print out pure EasyLanguage
the output created array assignments and loaded the calculated roll points in YYYMMDD format into the array
visually inspected non-adjusted continuous contracts that were spliced eight days before FND
appended dates in the array to match roll points, as illustrated by the dip in open interest
Step 6 from above is very important, because you want to make sure you are out of a position on the correct rollover date. If you are not, then you will absorb the discount between the contracts into your profit/loss when you exit the trade.
Step 2 – Create the code that executes the rollover trades
Here is the code that handles the rollover trades.
// If in a position and date + 1900000 (convert TS date format to YYYYMMDD), // then exit long or short on the current bar's close and then re-enter // on the next bar's open
if d+19000000 = rollArr[arrCnt] then begin condition1 = true; arrCnt = arrCnt + 1; if marketPosition = 1 then begin sell("LongRollExit") this bar on close; buy("LongRollEntry") next bar at open; end; if marketPosition = -1 then begin buyToCover("ShrtRollExit") this bar on close; sellShort("ShrtRollEntry") next bar at open; end;
Code to rollover open position
This code gets us out of an open position during the transition from the old contract to the new contract. Remember our function created and loaded the rollArr for us with the appropriate dates. This simulation is the best we can do – in reality we would exit/enter at the same time in the two different contracts. Waiting until the open of the next bar introduces slippage. However, in the long run this slippage cost may wash out.
Step 3 – Create a trading system with entries and exits
The system will be a simple Donchian where you enter on the close when the bar’s high/low penetrates the highest/lowest low of the past 40 bars. If you are long, then you will exit on the close of the bar whose low is less than the lowest low of the past 20 bars. If short, get out on the close of the bar that is greater than the highest high of the past twenty bars. The first test will show the result of using an adjusted continuous contract rolling 8 days prior to FND
This test will use the exact same data to generate the signals, but execution will take place on a non-adjusted continuous contract with rollovers. Here data2 is the adjusted continuous contract and data1 is the non-adjusted.
Still a very nice trade, but in reality you would have to endure six rollover trades and the associated execution costs.
Here is the mechanism of the rollover trade.
And now the performance results using $30 for round turn execution costs.
Now with rollovers
The results are very close, if you take into consideration the additional execution costs. Since TradeStation is not built around the concept of rollovers, many of the trade metrics are not accurate. Metrics such as average trade, percent wins, average win/loss and max Trade Drawdown will not reflect the pure algorithm based entries and exits. These metrics take into consideration the entries and exits promulgated by the rollovers. The first trade graphic where the short was held for several months should be considered 1 entry and 1 exit. The rollovers should be executed in real time, but the performance metrics should ignore these intermediary trades.
I will test these rollovers with different algorithms, and see if we still get similar results, and will post them later. As you can see, testing on non-adjusted data with rollovers is no simple task. Email me if you would like to see some of the code I used in this post.
When I worked at Futures Truth, we tested everything with our Excalibur software. This software used individual contract data and loaded the entire history (well, the part we maintained) of each contract into memory and executed rollovers at a certain time of the month. Excalibur had its limitations as certain futures contracts had very short histories and rollover dates had to be predetermined – in other words, they were undynamic. Over the years, we fixed the short history problem by creating a dynamic continuous contract going back in time for the number of days required for a calculation. We also fixed the database with more appropriate rollover frequency and dates. So in the end, the software simulated what I had expected from trading real futures contracts. This software was originally written in Fortran and for the Macintosh. It also had limitations on portfolio analysis as it worked its way across the portfolio, one complete market at a time. Even with all these limitations, I truly thought that the returns more closely mirrored what a trader might see in real time. Today, there aren’t many, if any, simulation platforms that test on individual contracts. The main reasons for this are the complexity of the software, and the database management. However, if you are willing to do the work, you can get close to testing on individual contract data with EasyLanguage.
Step 1 – Get the rollover dates
This is critical as the dates will be used to roll out of one contract and into another. In this post, I will test a simple strategy on the crude futures. I picked crude because it rolls every month. Some data vendors use a specific date to roll contracts, such as Pinnacle data. In real time trading, I did this as well. We had a calendar for each month, and we would mark the rollover dates for all markets traded at the beginning of each month. Crude was rolled on the 11th or 12th of the prior month to expiration. So, if we were trading the September 2022 contract, we would roll on August 11th. A single order (rollover spread) was placed to sell (if long) the September contract and buy the October contract at the market simultaneously. Sometimes we would leg into the rollover by executing two separate orders – in hopes of getting better execution. I have never been able to find a historic database of when TradeStation performs its rollovers. When you use the default @CL symbol, you allow TradeStation to use a formula to determine the best time to perform a rollover. This was probably based on volume and open interest. TradeStation does allow you to pick several different rollover triggers when using their continuous data.
I am getting ahead of myself, because we can simply use the default @CL data to derive the rollover dates (almost.) Crude oil is one of those weird markets where LTD (last trade days) occurs before FND (first notice day.) Most markets will give you a notice before they back up a huge truck and dump a 1000 barrels of oil at your front door. With crude you have to be Johnny on the spot! Rollover is just a headache when trading futures, but it can be very expensive headache if you don’t get out in time. Some markets are cash settled so rollover isn’t that important, but others result in delivery of the commodity. Most clearing firms will help you unwind an expired contract for a small fee (well relatively small.) In the good old days your full service broker would give you heads up. They would call you and say, “George you have to get out of that Sept. crude pronto!” Some firms would automatically liquidate the offending contract on your behalf – which sounds nice but it could cost you. Over my 30 year history of trading futures I was caught a few times in the delivery process. You can determine these FND and LTD from the CME website. Here is the expiration description for crude futures.
Trading terminates 3 business day before the 25th calendar day of the month prior to the contract month. If the 25th calendar day is not a business day, trading terminates 4 business days before the 25th calendar day of the month prior to the contract month.
You can look this up on your favorite broker’s website or the handy calendars they send out at Christmas. Based on this description, the Sept. 2022 Crude contract would expire on August 20th and here’s why
August 25 is Tuesday
August 24 is Monday- DAY1
August 21 is Friday – DAY2
August 20 is Thursday – DAY3
This is the beauty of a well oiled machine or exchange. The FND will occur exactly as described. All you need to do is get all the calendars for the past ten years and find the 25th of the month and count back three business days. Or if the 25 falls on a weekend count back four business days. Boy that would be chore, would it not? Luckily, we can have the data and an EasyLanguage script do this for us. Take a look at this code and see if it makes any sense to you.
Case "@CL": If dayOfMonth(date) = 25 and firstMonthPrint = false then begin print(date+19000000:8:0); firstMonthPrint = true; end; If(dayOfMonth(date) < 25 and dayOfMonth(date) > 25 ) and firstMonthPrint = false then begin print(date+19000000:8:0); firstMonthPrint = true; end;
Code to printout all the FND of crude oil.
I have created a tool to print out the FND or LTD of any commodity futures by examining the date. In this example, I am using a Switch-Case to determine what logic is applied to the chart symbol. If the chart symbol is @CL, I look to see if the 25th of the month exists and if it does, I print the date 3 days prior out. If today’s day of month is greater than 25 and the prior day’s day of month is less than 25, I know the 25th occurred on a weekend and I must print out the date four bars prior. These dates are FN dates and cannot be used as is to simulate a rollover. You had best be out before the FND to prevent the delivery process. Pinnacle Date rolls the crude on the 11th day of the prior month for its crude continuous contracts. I aimed for this day of the month with my logic. If the FND normally fell on the 22nd of the month, then I should back up either 9 or 10 business days to get near the 11th of the month. Also I wanted to use the output directly in an EasyLanguage strategy so I modified my output to be exact EasyLanguage.
Case "@CL": If dayOfMonth(date) = 25 and firstMonthPrint = false then begin value1 = value1 + 1; print("rollArr[",value1:1:0,"]=",date+19000000:8:0,";"); firstMonthPrint = true; end; If(dayOfMonth(date) < 25 and dayOfMonth(date) > 25 ) and firstMonthPrint = false then begin value1 = value1 + 1; print("rollArr[",value1:1:0,"]=",date+19000000:8:0,";"); // print(date+19000000:8:0); firstMonthPrint = true; end;
Code to print our 9 or 10 bars prior to FND in actual EasyLanguage
Now. that I had the theoretical rollover dates for my analysis I had to make sure the data that I was going to use matched up exactly. As you saw before, you can pick the rollover date for your chart data. And you can also determine the discount to add or subtract to all prior data points based on the difference between the closing prices at the rollover point. I played around with the number of days prior to FND and selected non adjusted for the smoothing of prior data.
How did I determine 8 days Prior to First Notice Date? I plotted different data using a different number of days prior and determined 8 provided a sweet spot between the old and new contract data’s open interest. Can you see the rollover points in the following chart? Ignore the trades – these were a beta test.
The dates where the open interest creates a valley aligned very closely with the dates I printed out using my FND date finder function. To be safe, I compared the dates and fixed my array data to match the chart exactly. Here are two rollover trades – now these are correct.
This post turned out to be a little longer than I thought, so I will post the results of using an adjusted continuous contract with no rollovers, and the results using non-adjusted concatenated contracts with rollovers. The strategy will be a simple 40/20 bar Donchian entry/exit. You maybe surprised by the results – stay tuned.
The last book in the Easing Into EasyLanguage Serieshas finally been put to bed. Unlike the first two books in the series, where the major focus and objective was to introduce basic programming ideas to help get new EasyLanguages users up to speed, this edition introduces more Advanced topics and the code to develop and program them.
Buy this book to learn how to overcome the obstacles that may be holding you back from developing your ideal Analysis Technique. This book could be thousands of pages long because the number of topics could be infinite. The subjects covered in this edition provide a great cross-section of knowledge that can be used further down the road. The tutorials will cover subjects such as:
Arrays – single and multiple dimensions
Functions – creation and communicating via Passed by Value and Passed by Reference
Finite State Machine – implemented via the Switch-Case programming construct
String Manipulation – construction and deconstruction of strings using EasyLanguage functions
Hash Table and Hash Index – a data structure(s) that contains unique addresses of bins that can contain N records
Using Hash Tables – accessing and storing data related to unique Tokens
Token Generation – an individual instance of a type of symbol
Seasonality – in depth analysis of the Ruggiero/Barna and Sheldon Knight Universal Seasonal data
File Manipulation – creating, deleting and writing to external files
Using Projects – organizing Analysis Techniques by grouping support functions and code into a single entity
Text Graphic Objects – extracting text from a chart and storing the object information in arrays for later development into a strategy
Commitment of Traders Report – TradeStation only (not MultiChart compatible) code. Converting the COT indicator and using the FundValue functionality to develop a trading strategy
Multiple Time Frame based indicator – use five discrete time frames and pump the data into a single indicator – “traffic stop light” feel
Once you become a programmer, of any language, you must continually work on honing your craft. This book shows you how to use your knowledge as building blocks to complete some really cool and advanced topics.
Illustrating Difference Between Data Aliasing and Not Data Aliasing
If you have a higher resolution as Data 1 (5 minute in this case) than Data 2 (15 minute), then you must use Data Aliasing if you are going to use a variable to represent a price or a function output. With out Data Aliasing all data references are in terms of Data 1. When the 15 minute bar closes then the current  and one bar back[ 1] will be correct – going back further in time will reflect correct data. During the 15 minute bar only the last value  will show the correct reading of the last completed 15 minute bar. Once you tie the variable to its correct time frame variableName(0, Data2), you can then reference historic bars in the same fashion as if it were Data1. This includes price references and function output values.
Check this chart out and see if it makes sense to you. I dedicate a portion of a Tutorial on Data Aliasing in my latest book due out next week – Easing Into EasyLanguage – Advanced Topics.
Quickly Analyze Market Metrics with Gradient Based Shading
This is a simple indicator but it does involve some semi-advanced topics. Just to let you know I am working on the third book in the Easing Into EasyLanguage series. If you haven’t check out the first two, you might just want to head over to amazon and check those out. This topic falls in the spectrum of the ideas that I will be covering in the Advanced Topics edition. Also to let you know I just published the 2nd Edition of Trend Following Systems: A DIY Project – Batteries Included. Check this out if you want to learn some Python and also see some pretty cool Trend Following algorithms – I include EasyLanguage too!
The code that follows demonstrates how to shade between plots and adjust gradient in terms of the RSI reading. I compiled this with MultiCharts, so I assume it will work there too – just let me know if it doesnt. I found this code somewhere on the web when researching shading. If I knew the original author I would definitely give full credit. The code is rather simple, setting up the chart is just slightly more difficult. The Keltner Channel was used to define the shading boundaries. You could have just as easily used Bollinger Bands or anything that provided a range around the market. Here’s the code.
Basically all this math is doing is keeping the RSI reading within the bounds of the Keltner Upper and Lower Channels. You want a high RSI reading to be near the Upper Channel and a low RSI reading to be near the Lower Channel. You can change up the formula to make more sense.
Here you take the LowerBand and add the percentage of the MyRSI/100 times the range. This works too. But the original formula scales or intensifies the RSI reading so you get much wider gradient spectrum. The AVG is used as the center of gravity and the RSI is converted in terms of the middle 50 line. A positive number, anything > 50, is then scaled higher in the range and a negative number, anything < 50 is scaled lower in the range. In other words it makes a prettier and more informative picture.
Sometimes you just want to create a combined equity curve of several markets and for one reason or another you don’t want to use Maestro. This post will show you an indicator that you can insert into your TradeStation chart/strategies that will output monthly cumulative equity readings. After that I refresh my VBA skills a little bit by creating a VBA Macro/Script that will take the output and parse it into a table where the different months are the rows and the different market EOM equities, for those months, will be the columns. Then all the rows will be summed and then finally a chart will be produced. I will zip the Exel .xlsm and include it at the end of this post.
Part 1: Output Monthly Data to Print Log
You can determine the end of the month by comparing the current month of the date and the month of the prior date. If they are different, then you know you are sitting on the first trading day of the new month. You can then reach back and access the total equity as of yesterday. If you want you can also track the change in month equity. Here is the indicator code in EasyLanguage.
// Non plotting indicator that needs to be applied to // a chart that also has a strategy applied // one that produces a number of trades
if month(date) <> month(date) then begin monthlyEqu = totalEquity - priorMonthEqu; priorMonthEqu = totalEquity; print(getSymbolName,",",month(date):2:0,"-",year(date)+1900:4:0,",",monthlyEqu,",",totalEquity); end; totalEquity = i_ClosedEquity;
Indicator that exports the EOM equity values
The interesting part of this code is the print statement. You can use the month and year functions to extract the respective values from the date bar array. I use a formatted print to export the month and year without decimals. Remember 2021 in TradeStation is represented by 121 and all you have to do is add 1900 to get a more comfortable value. The month output is formatted with :2:0 and the year with :4:0. The first value in the format notation informs the computer to allow at least 2 or 4 values for the month and the year respectively. The second value following the second colon informs the computer that you do not want any decimals values (:0). Next insert the indicator into all the charts in your workspace. Here’s a snippet of the output on one market. I tested this on six markets and this data was the output generated. Some of the markets were interspersed and that is okay. You may have a few months of @EC and then a few months of @JY and then @EC again.
If you use this post’s EXCEL workbook with the macro you may need to tell EXCEL to forget any formatting that might already be inside the workbook. Open my workbook and beware that it will inform/warn you that a macro is located inside and that it could be dangerous. If you want to go ahead and enable the macro go ahead. On Sheet1 click in A1 and place the letter “G”. Then goto the Data Menu and then the Data Tools section of the ribbon and click Text to Columns. A dialog will open and ask you they type of file that best describes your data. Click the Delimited radio button and then next. You should see a dialog like this one.
Now copy all of the data from the Print-Log and paste it into Column A. If all goes right everything will be dumped in the appropriate rows and in a single column.
First select column A and go back to the Data Menu and the Data Tools on the Ribbon. Select Delimited and hit next, Choose comma because we used commas to separate our values. Click Next again. Eventually you will get to this dialog.
If you chose Date format for column 2 with MDY, then it will be imported into the appropriate column in a date format. This makes charting easier. If all goes well then you will have four columns of data – a column for Symbol, Date, Delta-EOM and EOM. Select column B and right click and select Format Cells.
Once you format the B column in the form of MM-YYYY you will have a date like 9-2007, 10-2007, 11-2007…
Running the VBA Macro/Script
On the Ribbon in EXCEL goto the Developer Tab. If you don’t see it then you will need to install it. Just GOOGLE it and follow their instructions. Once on the Develop Tab goto the Code category and click the Visual Basic Icon. Your VBA IDE will open and should like very similar to this.
If all goes according to plan after you hit the green Arrow for the Run command your spreadsheet should like similar to this.
The Date column will be needed to be reformatted again as Date with Custom MM-YYYY format. Now copy the table by highlighting the columns and rows including the headings and then goto to Insert Menu and select the Charts category.
This is what you should get.
This is the output of the SuperTurtle Trading system tested on the currency sector from 2007 to the present.
I have become very spoiled using Python as it does many things for you by simply calling a function. This code took my longer to develop than I thought it would, because I had to back to the really old school of programming (really wanted to see if I could do this from scratch) to get this done. You could of course eliminate some of my code by calling spread sheet functions from within EXCEL. I went ahead and did it the brute force way just to see if I could do it.
'read data from columns 'symbol, date, monthlyEquity, cumulativeEquity - format 'create arrays to hold each column of data 'use nested loops to do all the work 'brute force coding, no objects - just like we did in the 80s
Dim symbol(1250) As String Dim symbolHeadings(20) As String Dim myDate(1250) As Long Dim monthlyEquity(1250) As Double Dim cumulativeEquity(1250) As Double
'read the data from the cells dataCnt = 1 Do While Cells(dataCnt, 1) <> "" symbol(dataCnt) = Cells(dataCnt, 1) myDate(dataCnt) = Cells(dataCnt, 2) monthlyEquity(dataCnt) = Cells(dataCnt, 3) cumulativeEquity(dataCnt) = Cells(dataCnt, 4) dataCnt = dataCnt + 1 Loop dataCnt = dataCnt - 1
'get distinct symbolNames and use as headers symbolHeadings(1) = symbol(1) numSymbolheadings = 1 For i = 2 To dataCnt - 1 If symbol(i) <> symbol(i + 1) Then newSymbol = True For j = 1 To numSymbolheadings If symbol(i + 1) = symbolHeadings(j) Then newSymbol = False End If Next j If newSymbol = True Then numSymbolheadings = numSymbolheadings + 1 symbolHeadings(numSymbolheadings) = symbol(i + 1) End If End If Next i
'Remove duplicate months in date array 'have just one column of month end dates
Cells(2, 7) = myDate(1) dispRow = 2 numMonths = 1 i = 1 Do While i <= dataCnt foundDate = False For j = 1 To numMonths If myDate(i) = Cells(j + 1, 7) Then foundDate = True End If Next j If foundDate = False Then numMonths = numMonths + 1 Cells(numMonths + 1, 7) = myDate(i) End If i = i + 1 Loop 'put symbols across top of table 'put "date" and "cumulative" column headings in proper 'locations too
Cells(1, 7) = "Date" For i = 1 To numSymbolheadings Cells(1, 7 + i) = symbolHeadings(i) Next i
numSymbols = numSymbolheadings Cells(1, 7 + numSymbols + 1) = "Cumulative" 'now distribute the monthly returns in their proper 'slots in the table dispRow = 2 dispCol = 7 For i = 1 To numSymbols For j = 2 To numMonths + 1 For k = 1 To dataCnt foundDate = False If symbol(k) = symbolHeadings(i) And myDate(k) = Cells(j, 7) Then Cells(dispRow, dispCol + i) = cumulativeEquity(k) dispRow = dispRow + 1 Exit For End If 'for later use 'If j > 1 Then ' If symbol(k) = symbolHeadings(i) And myDate(k) < Cells(j, 7) And myDate(k) > Cells(j - 1, 7) Then ' dispRow = dispRow + 1 ' End If 'End If Next k Next j dispRow = 2 Next i 'now accumulate across table and then down For i = 1 To numMonths cumulative = 0 For j = 1 To numSymbols cumulative = cumulative + Cells(i + 1, j + 7) Next j Cells(i + 1, 7 + numSymbols + 1) = cumulative Next i End Sub
This a throwback to the 80s BASIC on many of the family computers of that era. If you are new to VBA you can access cell values by using the keyword Cells and the row and column that points to the data. The first thing you do is create a Module named combineEquityFromTS and in doing so it will create a Sub combineEquityFromTS() header and a End Sub footer. All of your code will be squeezed between these two statements. This code is ad hoc because I just sat down and started coding without much forethought.
Use DIM to Dimension an Arrays
I like to read the date from the cells into arrays so I can manipulate the data internally. Here I create five arrays and then loop through column one until there is no longer any data. The appropriate arrays are filled with their respective data from each row.
Once the data is in arrays we can start do parse it. The first thing I want is to get the symbolHeadings or markets. I know the first row has a symbol name so I go ahead and put that into the symbolHeadings array. I kept track of the number of rows in the data with the variable dataCnt. Here I use nested loops to work my way down the data and keep track of new symbols as I encounter them. If the symbol changes values, I then check my list of stored symbolHeadings and if the new symbol is not in the list I add it.
Since all the currencies will have the same month values I wanted to compress all the months into a single discrete month list. This isn’t really all that necessary since we could have just prefilled the worksheet with monthly date values going back to 2007. This algorithm is similar to the one that is used to extract the different symbols. Except this time, just for giggles, I used a Do While Loop.
As well as getting values from cells you can also put values into them. Here I run through the list of markets and put them into Cells(1, 7+i). When working with cells you need to make sure you get the offset correct. Here I wanted to put the market names in Row A and Columns: H, I, J, K, L, M.
Column H = 8
Column I = 9
Column J = 10
Column K =11
Column L = 12
Column M = 13
Cells are two dimensional arrays. However if you are going to use what is on the worksheet make sure you are referencing the correct data. Here I introduce dispRow and dispCol as the anchor points where the data I need to reference starts out.
Here I first parse through each symbol and extract the EOM value that matches the symbol name and month-year value. So if I am working on @EC and I need the EOM for 07-2010, I fist loop through the month date values and compare the symbol AND myDate (looped through with another for-loop) with the month date values. If they are the same then I dump the value in the array on to the spreadsheet. And yes I should have used this:
For j = dispRow to numMonths-1
Instead of –
For j = 2 to numMonths-1
Keeping arrays in alignment with Cells can be difficult. I have a hybrid approach here. I will clean this up later and stick just with arrays and only use Cells to extract and place data. The last thing you need to do is sum each row up and store that value in the Cumulative column.
This was another post where we relied on another application to help us achieve our objective. If you are new to EXCEL VBA (working with algorithms that generate trades) you can find out more in my Ultimate Algorithmic Trading System Toolbox book. Even if you don’t get the book this post should get you started on the right track.
SuperTrend is a trading strategy and indicator all built into one entity. There are a couple of versions floating around out there. MultiCharts and Sierra Chart both have slightly different flavors of this combo approach.
Ratcheting Trailing Stop Paradigm
This indic/strat falls into this category of algorithm. The indicator never moves away from your current position like a parabolic stop or chandelier exit. I used the code that was disclosed on Futures.io or formerly known as BigMikesTrading blog. This version differs from the original SuperTrend which used average true range. I like Big Mike’s version so it will discussed here.
Big Mike’s Math
The math for this indicator utilizes volatility in the terms of the distance the market has travelled over the past N days. This is determined by calculating the highest high of the last N days/bars and then subtracting the lowest low of last Ndays/bars. Let’s call this the highLowRange. The next calculation is an exponential moving average of the highLowRange. This value will define the market volatility. Exponential moving averages of the last strength days/bars highs and lows are then calculated and divided by two – giving a midpoint. The volatility measure (multiplied my mult) is then added to this midpoint to calculate an upper band. A lower band is formed by subtracting the volatility measure X mult from the midpoint.
Upper or Lower Channel?
If the closing price penetrates the upper channel and the close is also above the highest high of strength days/bars back (offset by one of course) then the trend will flip to UP. When the trend is UP, then the Lower Channel is plotted. Once the trend flips to DN, the upper channel will be plotted. If the trend is UP the lower channel will either rise with the market or stay put. The same goes for a DN trend – hence the ratcheting. Here is a graphic of the indicator on CL.
If you plan on using an customized indicator in a strategy it is always best to build the calculations inside a function. The function then can be used in either an indicator or a strategy.
Function Name: SuperTrend_BM
Function Type: Series – we will need to access prior variable values
if trend < 0 and trend > 0 then trendDN = True; if trend > 0 and trend < 0 then trendUP = True;
//ratcheting mechanism if trend > 0 then dn = maxList(dn,dn); if trend < 0 then up = minList(up,up);
// if trend dir. changes then assign // up and down appropriately if trendUP then up = xAvg + mult * xAvgRng; if trendDN then dn = xAvg - mult * xAvgRng;
if trend = 1 then ST = dn else ST = up;
STrend = trend;
SuperTrend_BM = ST;
SuperTrend ala Big Mike
The Inputs to the Function
The original SuperTrend did include the Strength input. This input is a Donchian like signal. Not only does the price need to close above/below the upper/lower channel but also the close must be above/below the appropriate Donchian Channels to flip the trend, Also notice we are using a numericRef as the type for STrend. This is done because we need the function to return two values: trend direction and the upper or lower channel value. The appropriate channel value is assigned to the function name and STrend contains the Trend Direction.
A Function Driver in the Form of an Indicator
A function is a sub-program and must be called to be utilized. Here is the indicator code that will plot the values of the function using: length(9), mult(1), strength(9).
// SuperTrend indicator // March 25 2010 // Big Mike https://www.bigmiketrading.com inputs: length(9), mult(1), strength(9);
vars: strend(0), st(0);
st = SuperTrend_BM(length, mult,strength,strend);
if strend = 1 then Plot1(st,"SuperTrendUP"); if strend = -1 then Plot2(st,"SuperTrendDN");
Function Drive in the form of an Indicator
This should be a fun indicator to play with in the development of a trend following approach. My version of Big Mike’s code is a little different as I wanted the variable names to be a little more descriptive.
Update Feb 28 2022
I forgot to mention that you will need to make sure your plot lines don’t automatically connect.
Can You Do This with Just One Plot1?
An astute reader brought it to my attention that we could get away with a single plot and he was right. The reason I initially used two plot was to enable the user to chose his/her own plot colors by using the Format dialog.
//if strend = 1 then Plot1(st,"SuperTrendUP"); //if strend = -1 then Plot2(st,"SuperTrendDN");
if strend = 1 then SetPlotColor(1,red); if strend = -1 then SetPlotColor(1,green);
This is my second book in the Easing Into EasyLanguage [EZNGN2EZLANG] series of books. Here are the table of contents.
About Website Computer Code and Fonts In Print Version
Using EasyLanguage to Program on Minute Intervals?
Tutorial 14 – Why Do I Need to Use Intraday Data
Tutorial 15 – An Algorithm Template that Uses Minute Bars to Trade a Daily Bar Scheme
Tutorial 16 – Using Data2 as a Daily Bar
Tutorial 17 – Let’s Day Trade!
Tutorial 18 – Moving From Discrete Day-Trade Strategy to a Framework
Tutorial 19 – Day-Trading Continued: Volatility Based Open Range Break Out with Pattern Recognition
Tutorial 20 – Pyramiding with Camarilla
Tutorial 21 – Programming a Scale Out Scheme
Tutorial 22- Crawling Like A Bug on a Five Minute Chart
Tutorial 23 – Templates For Further Research
Appendix A-Source Code
Appendix B-Links to Video Instruction
I have included five hours of video instruction which is included via links in the book and in the supplemental resource download.
What’s In This Book
If you are not a Trend Follower, then in most cases, you will not be able to properly or accurately code and backtest your trading algorithm without the use of higher resolution data (minute bars). A very large portion of the consulting I have done over the years has dealt with converting a daily bar system to one that uses intraday data such as a 5-minute bar. Coding a daily bar system is much more simple than taking the same concept and adding it to a higher resolution (Hi-Res) chart. If you use a 100 day moving average and you apply it to a 5-minute chart you get a 100 five minute bar moving average – a big difference.
Why Do I Need To Use Hi-Res Data?
If all you need to do is calculate a single entry or exit on a daily basis and can manually execute the trades, then you can stick with daily bars. Many of the famous Trend-Following systems such as Turtle, Aberration, Aberration Plus, Andromeda, and many others fall into this category. Most CTAs use these types of systems and spend most of their efforts on accurate execution and portfolio management. These systems, until the genesis of the COVID pandemic, have struggled for many years. Some of the biggest and brightest futures fund managers had to shut their doors due to their lagging performance and elevated levels of risk in comparison to the stock market. However, if you need to know the ebb and flow of the intraday market movement to determine accurate trade entry, then intraday data is an absolute necessity. Also, if you want to automate, Hi-Res data will help too! Here is an example of a strategy that would need to know what occurs first in chronological order.
Example of a Simple Algorithm that Needs Intraday Data
If the market closes above the prior day’s close, then buy the open of the next day plus 20% of today’s range andsellShort the open of the next day minus 40% of today’s range. Use a protective stop of $500 and a profit objective of $750. If the market closes below the prior day’s close then sellShort the open of the next day minus 20% of today’s range andbuy the open of the next day plus 40% of todays range. The same trade management of profit and loss is applied as well. From the low resolution of a daily bar the computer cannot determine if the market moves up 20% or down 40% first. So the computer cannot accurately determine if a long or short is established first. And to add insult to injury, if the computer could determine the initial position accurately from a daily bar, it still couldn’t determine if the position is liquidated via a profit or a loss if both conditions could have occurred.
What About “Look Inside Bar”?
There is evidence that if the bar closes near the high and the open near the low of a daily bar, then there is a higher probability that the low was made first. And the opposite is true as well. If the market opens near the middle of the bar, then all bets are off. When real money is in play you can’t count on this type of probability or the lack thereof . TradeStation allows you to use your daily bar scheme and then Look Inside Bar to see the overall ebb and flow of the intraday movement. This function allows you to drill down to one minute bars, if you like. This helps a lot, but it still doesn’t allow you to make intraday decisions, because you are making trading decisions from the close of the prior day.
if c > c then begin buy next day at open of next day + 0.2 * range stop; sellShort next day at open of next day - 0.4 * range stop; end;
Next Day Order Placement
Using setProfitTarget and setStopLoss helps increase testing accuracy, but shouldn’t you really test on a 5-minute bar just to be on the safe side.
DayTrading in Most Cases Needs Hi-Res Data
If I say buy tomorrow at open of next day and use a setStopLoss(500), then I don’t need Hi-Res data. I execute the open which is the first time stamp in the chronological order of the day. Getting stopped out will happen later and any adverse move from the open that equates to $500 will liquidate the position or the position will be liquidated at the end of the day.
However, if I say buy the high of the first 30 minutes and use the low of the first 30 minutes as my stop loss and take profits if the position is profitable an hour later or at $750, then intraday data is absolute necessity. Most day trading systems need to react to what the market offers up and only slightly relies on longer term daily bar indicators.
If Intraday Data is So Important then Why ” The Foundation Edition?”
You must learn to crawl before you can walk. And many traders don’t care about the intraday action – all they care about is where the market closed and how much money should be allocated to a given trade or position. Or how an open position needs to be managed. The concepts and constructs of EasyLanguage must be learned first from a daily bar framework before a new EL programmer can understand how to use that knowledge on a five minute bar. You cannot just jump into a five minute bar framework and start programming accurately unless you are a programmer from the start or you have a sound Foundation in EasyLanguage.
Excerpt from Hi-Res Edition
Here is an example of a simple and very popular day trading scheme. Buy 2 units on a break out and take profits on 1 unit at X dollars. Pull stop on 2nd unit to breakeven to provide a free trade. Take profit on 2nd unit or get out at the end of the day.
Conceptually this is easy to see on the chart and to understand. But programming this is not so easy. The code and video for this algorithm is from Tutorial 21 in the Hi-Res edition.
Here are the results of the algorithm on a 5 minute ES.D chart going back five years. Remember these results are the result of data mining. Make sure you understand the limitations of back-testing. You can read those here.
There are a total of 10 Tutorials and over 5 hours of Video Instruction included. If you want to expand your programming capabilities to include intraday algorithm development, including day trading, then get your copy today.
Before the days of OOEL and more advanced data structures, such as vectors, you had to work with multidimensional arrays.
The problem with arrays is you have to do all the housekeeping whereas with vectors the housekeeping is handled internally. Yes, vectors in many cases would be the most efficient approach, but if you are already using Multi-D arrays, then mixing the two could become confusing. So stick with the arrays for now and progress into vectors at your leisure.
Recreate the CCI indicator with Multi-D Array
This exercise is for demonstration purposes only as the existing CCI function works just fine. However, when you are trying out something new or in this case an application of a different data structure (array) its always great to check your results against a known entity. If your program replicates the known entity, then you know that you are close to a solution. The CCI function accesses data via the globalHigh, Low and Close data streams and then applies a mathematical formula to derive a result. <
Derive Your Function First
Create the function first by prototyping what the function will need in the formal parameter list (funciton header). The first thing the function will need is the data – here is what it will look like.
OHLCArray[1,1] =1210903.00 // DATE
OHLCArray[1,2] = 4420.25 // OPEN
OHLCArray[1,3] = 4490.25 // HIGH
OHLCArray[1,4] = 4410.25 // LOW
OHLCArray[1,5] = 4480.75 // CLOSE
OHLCArray[2,1] =1210904.00 // DATE
OHLCArray[2,2] = 4470.25 // OPEN
OHLCArray[2,3] = 4490.25 // HIGH
OHLCArray[2,4] = 4420.25 // LOW
OHLCArray[2,5] = 4440.75 // CLOSE
Visualize 2-D Array as a Table
The CCI function is only concerned with H, L, C and that data is in columns 3, 4, 5. If you know the structure of the array before you program the function, then you now which columns or fields you will need to access. If you don’t know the structure beforehand , then that information would need to be passed into the function as well. Let us assume we know the structure. Part of the housekeeping that I mentioned earlier was keeping track of the current row where the latest data is being stored. This “index” plus the length of the CCI indicator is the last two things we will need to know to do a proper calculation.
CCI_2D Function Formal Parameter List
// This function needs data, current data row, and length // Notice how I declare the OHLCArray using the dummy X and Y // Variable - this just tells TradeStation to expect 2-D array // ------------------ // | | // * * inputs: OHLCArray[x,y](numericArray), currentRow(numericSimple), length(numericSimple); // *** // ||| //---------------------------- // Also notice I tell TradeStation that the array is of type numeric // We are not changing the array but if we were, then the type would be // numericArrayRef - the actual location in memory not just a copy
CCI_2D Formal Parameter List
2-D Array Must Run Parallels with Actual Data
The rest of the function expects the data to be just like the H, L, C built-in data – so there cannot be gaps. This is very important when you pack the data and you will see this in the function driver code a.k.a an indicator. The data needs to align with the bars. Now if you are using large arrays this can slow things down a bit. You can also shuffle the array and keep the array size to a minimum and I will post how to do this in a post later this week. The CCI doesn’t care about the order of the H,L,C as long as the last N element is the latest values.
if AvgDev = 0 then CCI_2D = 0 else CCI_2D = ( value1 + value2 + value3 - Mean ) / ( .015 * AvgDev ) ;
This function could be streamlined, but I wanted to show you how to access the different data values with the currentRow variable and columns 3, 4, and 5. I extract these data and store them in Values variables. Notice the highlighted line where I check to make sure there are enough rows to handle the calculation. If you try to access data before row #1, then you will get an out of bounds error and a halt to program execution.
Notice lines 16 and 17 where I am plotting both function results – my CCI_2D and CCI. Also notice how I increment numRows on each bar – this is the housekeeping that keeps that array synched with the chart. In the following graphic I use 14 for CCI_2D and 9 for the built-in CCI.
Now the following graphic uses the same length parameters for both functions. Why did just one line show up?
Make Your Unique Coding Replicate a Known Entity – If You Can
Here is where your programming is graded. The replication of the CCI using a 2-D Array instead of the built-in H, L, C data streams, if programmed correctly, should create the exact same results and it does, hence the one line. Big Deal right! Why did I go through all this to do something that was already done? Great programming is not supposed to re-invent the wheel. And we just did exactly that. But read between the lines here. We validated code that packed a 2-D array with data and then passed it to a function that then accessed the data correctly and applied a known formula and compared it to a known entity. So now you have re-usable code for passing a 2-D array to a function. All you have to do is use the template and modify the calculations. Re-inventing the wheel is A-Okay if you are using it as a tool for validation.
Backtesting with [Trade Station,Python,AmiBroker, Excel]. Intended for informational and educational purposes only!