Category Archives: Must Know

Why Do I Need to Test with Intraday Data

Why Can’t I Just Test with Daily Bars and Use Look-Inside Bar?

Good question.  You can’t because it doesn’t work accurately all of the time.   I just default to using 5 minute or less bars whenever I need to.  A large portion of short term, including day trade, systems need to know the intra day market movements to know which orders were filled accurately.  It would be great if you could just flip a switch and convert a daily bar system to an intraday system and Look Inside Bar(LIB) is theoretically that switch.  Here I will prove that switch doesn’t always work.

Daily Bar System

  • Buy next bar at open of the day plus 20% of the 5 day average range
  • SellShort next at open of the day minus 20% of the 5 day average range
  • If long take a profit at one 5 day average range above entryPrice
  • If short take a profit at one 5 day average range below entryPrice
  • If long get out at a loss at 1/2 a 5 day average range below entryPrice
  • If short get out at a loss at 1/2 a 5 day average range above entry price
  • Allow only 1 long and 1 short entry per day
  • Get out at the end of the day

Simple Code for the System

value1 = .2 * average(Range,5);
value2 = value1 * 5;

Buy next bar at open of next bar + value1 stop;
sellShort next bar at open of next bar - value1 stop;

setProfitTarget(value2*bigPointValue);
setStopLoss(value2/2*bigPointValue);
setExitOnClose;
Simplified Daily Bar DayTrade System using ES.D Daily
Daily Bar Using 5 min Look Inside Bar

Looks great with just the one hiccup:  Bot @ 3846.75 and the Shorted @ 3834.75 and then took nearly 30 handles of profit.

Now let’s see what really happened.

What Really Happened – Bot – Shorted – Stopped Out

Intraday Code to Control Entry Time and Number of Longs and Shorts

Not an accurate representation so let’s take this really simple system and apply it to intraday data.  Approaching this from a logical perspective with limited knowledge about TradeStation you might come up with this seemingly valid solution.  Working on the long side first.

//First Attempt


if d <> d[1] then value1 = .2 * average(Range of data2,5);
value2 = value1 * 5;
if t > sess1startTime then buy next bar at opend(0) + value1 stop;
setProfitTarget(value2*bigPointValue);
setStopLoss(value2/2*bigPointValue);
setExitOnClose;
First Simple Attempt

This looks very similar to the daily bar system.  I cheated a little by using

if d <> d[1] then value1 = .2 * average(Range of data2,5);

Here I am only calculating the average once a day instead of on each 5 minute bar.  Makes things quicker.  Also I used

if t > sess1StartTime then buy next bar at openD(0) + value1 stop;

I did that because if you did this:

buy next bar at open of next bar + value1 stop;

You would get this:

Cannot Sneak a Peek with Data2

That should do it for the long side, right?

Didn’t work quite right!

So now we have to monitor when we can place a trade and monitor the number of long and short entries.

How does this look!

Correct Execution!

So here is the code.  You will notice the added complexity.  The important things to know is how to control when an entry is allowed and how to count the number of long and short entries.  I use the built-in keyword/function totalTrades to keep track of entries/exits and marketPosition to keep track of the type of entry.

Take a look at the code and you can see how the daily bar system is somewhat embedded in the code.  But remember you have to take into account that you are stepping through every 5 minute bar and things change from one bar to the next.

vars: buysToday(0),shortsToday(0),curTotTrades(0),mp(0),tradeZoneTime(False);


if d <> d[1] then 
begin
	curTotTrades = totalTrades;
 	value1 = .2 * average(Range of data2,5);
	value2 = value1 * 5;	
	buysToday = 0;
	shortsToday = 0;
	tradeZoneTime = False;
end;

mp = marketPosition;

if totalTrades > curTotTrades then
begin
	if mp <> mp[1] then 
	begin
		if mp[1] = 1 then buysToday = buysToday + 1;
		if mp[1] = -1 then shortsToday = shortsToday + 1;
	end;
	if mp[1] = -1 then print(d," ",t," ",mp," ",mp[1]," ",shortsToday);
	curTotTrades = totalTrades;
end;
if t > sess1StartTime and t < sess1EndTime then tradeZoneTime = True;

if tradeZoneTime and buysToday = 0 and mp <> 1 then 
	buy next bar at opend(0) + value1 stop;
	
if tradeZoneTime and  shortsToday = 0 and mp <> -1 then 
	sellShort next bar at opend(0) - value1 stop;

setProfitTarget(value2*bigPointValue);
setStopLoss(value2/2*bigPointValue);
setExitOnClose;
Proper Code to Replicate the Daily Bar System with Accuracy

Here’s a few trade examples to prove our code works.

Looks Right!

Okay the code worked but did the system?

Uh? NO!

Conclusion

If you need to know what occurred first – a high or a low in a move then you must use intraday data.  If you want to have multiple entries then of course your only alternative is intraday data.   This little bit of code can get you started converting your daily bar systems to intraday data and can be a framework to develop your own day trading/or swing systems.

Can I Prototype A Short Term System with Daily Data?

You can of course use Daily Bars for fast system prototyping.  When the daily bar system was tested with LIB turned on, it came close to the same results as the more accurately programmed intraday system.  So you can prototype to determine if a system has a chance.  Our core concept buyt a break out, short a break out, take profits and losses and have no overnight exposure sounds good theoretically.  And if you only allow 2 entries in opposite directions on a daily bar you can determine if there is something there.

A Dr. Jekyll and Mr. Hyde Scenario

While playing around with this I did some prototyping of a daily bar system and created this equity curve.  I mistakenly did not allow any losses – only took profits and re-entered long.

Wow! Awesome! Holy Grail Uncovered. Venalicius Cave!

Venalicius Cave!  Don’t take a loser you and will reap the benefits.  The chart says so – so its got to be true – I know right?

The same chart from a different perspective.

You Start and End at the Same Place. But What A Ride. Yikes!

Moral of the Story – always look at your detailed Equity Curve.  This curve is very close to a simple buy and hold strategy.   Maybe a little better.

Daily Bar Ratcheting Stop and Conditional Optimization

Happy New Year!  My First Post of 2021!

In this post I simply wanted to convert the intraday ratcheting stop mechanism that I previously posted into a daily bar mechanism.  Well that got me thinking of how many different values could be used as the amount to ratchet.  I came up with three:

I have had requests for the EasyLanguage in an ELD – so here it is – just click on the link and unZip.

RATCHETINGSTOPWSWITCH

Ratcheting Schemes

  • ATR of N days
  • Fixed $ Amount
  • Percentage of Standard Deviation of 20 Days

So this was going to be a great start to a post, because I was going to incorporate one of my favorite programming constructs : Switch-Case.  After doing the program I thought wouldn’t it be really cool to be able to optimize over each scheme the ratchet and trail multiplier as well as the values that might go into each scheme.

In scheme one I wanted to optimize the N days for the ATR calculation.  In scheme two I wanted to optimize the $ amount and the scheme three the percentage of a 20 day standard deviation.  I could do a stepwise optimization and run three independent optimizations – one for each scheme.  Why not just do one global optimization you might ask?  You could but it would be a waste of computer time and then you would have to sift through the results.  Huh?  Why?  Here is a typical optimization loop:

Scheme Ratchet Mult Trigger Mult Parameter 1
1 : ATR 1 1 ATR (2)
2 : $ Amt 1 1 ATR (2)
3 : % of Dev. Amt 1 1 ATR (2)
1 : ATR 2 1 ATR (2)
2 : $ Amt 2 1 ATR (2)

Notice when we switch schemes the Parameter 1 doesn’t make sense.  When we switch to $ Amt we want to use a $ Value as Parameter 1 and not ATR.  So we could do a bunch of optimizations across non sensical values, but that wouldn’t really make a lot of sense.  Why not do a conditional optimization?  In other words, optimize only across a certain parameter range based on which scheme is currently being used.  I knew there wasn’t an overlay available to use using standard EasyLanguage but I thought maybe OOP,  and there is an optimization API that is quite powerful.  The only problem is that it was very complicated and I don’t know if I could get it to work exactly the way I wanted.

EasyLanguage is almost a full blown programming language.  So should I not be able to distill this conditional optimization down to something that I could do with such a powerful programming language?  And the answer is yes and its not that complicated.  Well at least for me it wasn’t but for beginners probably.  But to become a successful programmer you have to step outside your comfort zones, so I am going to not only explain the Switch/Case construct (I have done this in earlier posts)  but incorporate some array stuff.

When performing conditional optimization there are really just a few things you have to predefine:

  1. Scheme Based Optimization Parameters
  2. Exact Same Number of Iterations for each Scheme [starting point and increment value]
  3. Complete Search Space
  4. Total Number of Iterations
  5. Staying inside the bounds of your Search Space

Here are the optimization range per scheme:

  • Scheme #1 – optimize number of days in ATR calculation – starting at 10 days and incrementing by 2 days
  • Scheme #2 – optimize $ amounts – starting at $250 and incrementing by $100
  • Scheme #3 – optimize percent of 20 Bar standard deviation – starting at 0,25 and incrementing by 0.25

I also wanted to optimize the ratchet and target multiplier.  Here is the base code for the daily bar ratcheting system with three different schemes.  Entries are based on penetration of 20 bar highest/lowest close.

inputs: 
ratchetMult(2),trailMult(2),
volBase(True),volCalcLen(20),
dollarBase(False),dollarAmt(250),
devBase(False),devAmt(0.25);


vars:longMult(0),shortMult(0);
vars:ratchetAmt(0),trailAmt(0);
vars:stb(0),sts(0),mp(0);
vars:lep(0),sep(0);



if volBase then 
begin
	ratchetAmt = avgTrueRange(volCalcLen) * ratchetMult;
	trailAmt = avgTrueRange(volCalcLen) * trailMult;
end;
if dollarBase then 
begin
	ratchetAmt =dollarAmt/bigPointValue * ratchetMult;
	trailAmt = dollarAmt/bigPointValue * trailMult;
end;
if devBase then 
begin
	ratchetAmt = stddev(c,20) * devAmt * ratchetMult;
	trailAmt = stddev(c,20) * devAmt * trailMult;
end;


if c crosses over highest(c[1],20) then buy next bar at open;
if c crosses under lowest(c[1],20) then sellshort next bar at open;

mp = marketPosition;
if mp <> 0 and mp[1] <> mp then
begin
	longMult = 0;
	shortMult = 0;
end;


If mp = 1 then lep = entryPrice;
If mp =-1 then sep = entryPrice;


// 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 multiples 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;
	Sell("LongTrail") next bar at (lep + (longMult - 1) *  trailAmt) stop;
end;

If mp = -1 then 
Begin
	If l <= sep - (shortMult + 1) * ratchetAmt then	shortMult = shortMult + 1;
	buyToCover("ShortTrail") next bar (sep - (shortMult - 1) *  trailAmt) stop;
end;
Daily Bar Ratchet System

This code is fairly simple.  The intriguing inputs are:

  • volBase [True of False] and  volCalcLen [numeric Value]
  • dollarBase [True of False] and  dollarAmt [numeric Value]
  • devBase [True of False] and devAmt [numeric Value]

If volBase is true then you use the parameters that go along with that scheme.  The same goes for the other schemes.  So when you run this you would turn one scheme on at a time and set the parameters accordingly.  if I wanted to use dollarBase(True) then I would set the dollarAmt to a $ value.  The ratcheting mechanism is the same as it was in the prior post so I refer you back to that one for further explanation.

So this was a pretty straightforward strategy.  Let us plan out our optimization search space based on the different ranges for each scheme.  Since each scheme uses a different calculation we can’t simply optimize across all of the different ranges – one is days, and the other two are dollars and percentages.

Enumerate

We know how to make TradeStation loop based on the range of a value.  If you want to optimize from $250 to $1000 in steps of $250, you know this involves [$1000 – $250] / $250 + 1 or 3 + 1 or 4 interations.   Four loops will cover this entire search space.  Let’s examine the search space for each scheme:

  • ATR Scheme: start at 10 bars and end at 40 by steps of 2 or [40-10]/2 + 1 = 16
  • $ Amount Scheme: start at $250 and since we have to have 16 iterations [remember # of iterations have to be the same for each scheme] what can we do to use this information?  Well if we start $250 and step by $100 we cover the search space $250, $350, $450, $550…$1,750.  $250 + 15 x 250.  15 because $250 is iteration 1.
  • Percentage StdDev Scheme:  start at 0.25 and end at 0.25 + 15 x 0.25  = 4

So we enumerate 16 iterations to a different value.  The easiest way to do this is to create a map.  I know this seems to be getting hairy but it really isn’t.  The map will be defined as an array with 16 elements.  The array will be filled with the search space based on which scheme is currently being tested.  Take a look at this code where I show how to define an array of 16 elements and introduce my Switch/Case construct.

array: optVals[16](0);

switch(switchMode)
begin
	case 1:
		startPoint = 10; // vol based
		increment = 2;
	case 2:
		startPoint = 250/bigPointValue; // $ based
		increment = 100/bigPointValue;
	case 3:
		startPoint = 0.25; //standard dev
		increment = 0.25*minMove/priceScale;
	default:
		startPoint = 1;
		increment = 1;
end;

vars: cnt(0),loopCnt(0);
once 
begin
	for cnt = 1 to 16 
	begin
		optVals[cnt] = startPoint + (cnt-1) * increment;
	end;
end
Set Up Complete Search Space for all Three Schemes

This code creates a 16 element array, optVals, and assigns 0 to each element.  SwitchMode goes from 1 to 3.

  • if switchMode is 1: ATR scheme [case: 1] the startPoint is set to 10 and increment is set to 2
  • if switchMode is 2: $ Amt scheme [case: 2] the startPoint is set to $250 and increment is set to $100
  • if switchMode is 3: Percentage of StdDev [case: 3] the startPoint is set to 0.25 and the increment is set to 0.25

Once these two values are set the following 15 values can be spawned by the these two.  A for loop is great for populating our search space.  Notice I wrap this code with ONCE – remember ONCE  is only executed at the very beginning of each iteration or run.

once
begin
   for cnt = 1 to 16
   begin
     optVals[cnt] = startPoint + (cnt-1) * increment;
   end;
end

Based on startPoint and increment the entire search space is filled out.  Now all you have to do is extract this information stored in the array based on the iteration number.

Switch(switchMode) 
Begin
	Case 1:
		ratchetAmt = avgTrueRange(optVals[optLoops]) * ratchetMult;
		trailAmt = avgTrueRange(optVals[optLoops]) * trailMult;	
	Case 2:
		ratchetAmt =optVals[optLoops] * ratchetMult;
		trailAmt = optVals[optLoops] * trailMult;
	Case 3: 
		ratchetAmt =stddev(c,20) * optVals[optLoops] * ratchetMult;
		trailAmt = stddev(c,20) * optVals[optLoops] * trailMult;
	Default:
		ratchetAmt = avgTrueRange(optVals[optLoops]) * ratchetMult;
		trailAmt = avgTrueRange(optVals[optLoops]) * trailMult;
end;


if c crosses over highest(c[1],20) then buy next bar at open;
if c crosses under lowest(c[1],20) then sellshort next bar at open;

mp = marketPosition;
if mp <> 0 and mp[1] <> mp then
begin
	longMult = 0;
	shortMult = 0;
end;


If mp = 1 then lep = entryPrice;
If mp =-1 then sep = entryPrice;


// 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 multiples 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;
	Sell("LongTrail") next bar at (lep + (longMult - 1) *  trailAmt) stop;
end;

If mp = -1 then 
Begin
	If l <= sep - (shortMult + 1) * ratchetAmt then	shortMult = shortMult + 1;
	buyToCover("ShortTrail") next bar (sep - (shortMult - 1) *  trailAmt) stop;
end;
Extract Search Space Values and Rest of Code

Switch(switchMode)
Begin
Case 1:
  ratchetAmt = avgTrueRange(optVals[optLoops])ratchetMult;
  trailAmt = avgTrueRange(optVals[optLoops]) trailMult;
Case 2:
  ratchetAmt =optVals[optLoops] * ratchetMult;
  trailAmt = optVals[optLoops] * trailMult;
Case 3:
  ratchetAmt =stddev(c,20)optVals[optLoops]
ratchetMult;
  trailAmt = stddev(c,20) * optVals[optLoops] * trailMult;

Notice how the optVals are indexed by optLoops.  So the only variable that is optimized is the optLoops and it spans 1 through 16.  This is the power of enumerations – each number represents a different thing and this is how you can control which variables are optimized in terms of another optimized variable.   Here is my optimization specifications:

Opimization space

And here are the results:

Optimization Results

The best combination was scheme 1 [N-day ATR Calculation] using a 2 Mult Ratchet and 1 Mult Trail Trigger.  The best N-day was optVals[2] for this scheme.  What in the world is this value?  Well you will need to back engineer a little bit here.  The starting point for this scheme was 10 and the increment was 2 so if optVals[1] =10 then optVals[2] = 12 or ATR(12).    You can also print out a map of the search spaces.

vars: cnt(0),loopCnt(0);
once 
begin
	loopCnt = loopCnt + 1;
//	print(switchMode," : ",d," ",startPoint);
//	print("  ",loopCnt:2:0,"  --------------------");
	for cnt = 1 to 16 
	begin
		optVals[cnt] = startPoint + (cnt-1) * increment;
//		print(cnt," ",optVals[cnt]," ",cnt-1);
	end;
end;	
  Scheme 1
  --------------------
   1.00   10.00    0.00 10 days
   2.00   12.00    1.00
   3.00   14.00    2.00
   4.00   16.00    3.00
   5.00   18.00    4.00
   6.00   20.00    5.00
   7.00   22.00    6.00
   8.00   24.00    7.00
   9.00   26.00    8.00
  10.00   28.00    9.00
  11.00   30.00   10.00
  12.00   32.00   11.00
  13.00   34.00   12.00
  14.00   36.00   13.00
  15.00   38.00   14.00
  16.00   40.00   15.00
 
  Scheme2
  --------------------
   1.00    5.00    0.00 $ 250
   2.00    7.00    1.00 $ 350
   3.00    9.00    2.00 $ 400
   4.00   11.00    3.00 $ ---
   5.00   13.00    4.00
   6.00   15.00    5.00
   7.00   17.00    6.00
   8.00   19.00    7.00
   9.00   21.00    8.00
  10.00   23.00    9.00
  11.00   25.00   10.00
  12.00   27.00   11.00
  13.00   29.00   12.00
  14.00   31.00   13.00
  15.00   33.00   14.00
  16.00   35.00   15.00 $1750

  Scheme 3
  --------------------
   1.00    0.25    0.00 25 % stdDev
   2.00    0.50    1.00
   3.00    0.75    2.00
   4.00    1.00    3.00
   5.00    1.25    4.00
   6.00    1.50    5.00
   7.00    1.75    6.00
   8.00    2.00    7.00
   9.00    2.25    8.00
  10.00    2.50    9.00
  11.00    2.75   10.00
  12.00    3.00   11.00
  13.00    3.25   12.00
  14.00    3.50   13.00
  15.00    3.75   14.00
  16.00    4.00   15.00

This was a elaborate post so please email me with questions.  I wanted to demonstrate that we can accomplish very sophisticated things with just the pure and raw EasyLanguage which is a programming language itself.

ES.D Strategy with Ratcheting Trailing Stop [Intra-Day] – EasyLanguage

ES.D Strategy Utilizing Ratchet Trailing Stop

A reader of this blog wanted a conversion from my Ratchet Trailing Stop indicator into a Strategy.  You will notice a very close similarity with the indicator code as the code for this strategy.  This is a simple N-Bar [Hi/Lo] break out with inputs for the RatchetAmt and TrailAmt.  Remember RatchetAmt is how far the market must move in your favor before the stop is pulldown the TrailAmt.  So if the RatchetAmt is 12 and the TrailAmt is 6, the market would need to move 12 handles in your favor and the Trail Stop would move to break even.  If it moves another 12 handles then the stop would be moved up/down by 6 handles.  Let me know if you have any questions – this system is similar to the one I just posted.

Notice how the RED line Ratchets Up by the Fixed Amount [8/6]
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 t < calcTime(sess1Endtime,-3*barInterval) then
Begin
	if buysToday = 0  then buy("NBar-Range-B") next bar stb stop;
	if shortsToday = 0 then sellShort("NBar-Range-S") next bar sts stop;
end;

mp = marketPosition;
If mp = 1 then 
begin
	lep = entryPrice;
	buysToday = 1;
end;
If mp =-1 then 
begin
	sep = entryPrice;
	shortsToday = 1;
end;


// 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;
	Sell("LongTrail") next bar at (lep + (longMult - 1) *  trailAmt) stop;
end;

If mp = -1 then 
Begin
	If l <= sep - (shortMult + 1) * ratchetAmt then	shortMult = shortMult + 1;
	buyToCover("ShortTrail") next bar (sep - (shortMult - 1) *  trailAmt) stop;
end;

setExitOnClose;
I Used my Ratchet Indicator for the Basis of this Strategy

A Simple Break Out Algorithm Demonstrating Time Optimization

What is Better:  30, 60, or 120 Minute Break-Out on ES.D

Here is a simple tutorial you can use as a foundation to build a potentially profitable day trading system.  Here we wait N minutes after the open and then buy the high of the day or short the low of the day and apply a protective stop and profit objective.  The time increment can be optimized to see what time frame is best to use.  You can also optimize the stop loss and profit objective – this system gets out at the end of the day.  This system can be applied to any .D data stream in TradeStation or Multicharts.

Logic Description

  1. get open time
  2. get close time
  3. get N time increment
    1. 15 – first 15 minute of day
    2. 30 – first 30 minute of day
    3. 60 – first hour of day
  4. get High and Low of day
  5. place stop orders at high and low of day – no entries late in day
  6. calculate buy and short entries – only allow one each*
  7. apply stop loss
  8. apply profit objective
  9. get out at end of day if not exits have occurred

Optimization Results [From 15 to 120 by 5 minutes] on @ES.D 5 Minute Chart – Over Last Two Years

Optimization of Time: Look How the # Trades Decrease as the Time Increment Increases

Simple Orbo EasyLanguage

I threw this together rather quickly in a response to a reader’s question.  Let me know if you see a bug or two.  Remember once you gather your stops you must allow the order to be issued on every subsequent bar of the trading day.  The trading day is defined to be the time between timeIncrement and endTradeMinB4Close.  Notice how I used the EL function calcTime to calculate time using either a +positive or -negative input.  I want to sample the high/low of the day at timeIncrement and want to trade up until endTradeMinB4Close time.  I use the HighD and LowD functions to extract the high and low of the day up to that point.  Since I am using a tight stop relative to today’s volatility you will see more than 1 buy or 1 short occurring.  This happens when entry/exit occurs on the same bar and MP is not updated accordingly.  Somewhere  hidden in this tome of a blog you will see a solution for this.  If you don’t want to search I will repost it tomorrow.


//Optimizing Time to determine a simple break out
//Only works on .D data streams
Inputs: timeIncrement(15),endTradeMinB4Close(-15),stopLoss$(500),profTarg$(1000);

vars: firstBarTime(0),lastBarTime(0),buyStop(0),shortStop(0),
calcStopTime(0),quitTradeTime(0),buysToday(0),shortsToday(0),mp(0);

firstBarTime = sessionStartTime(0,1);
lastBarTime = sessionEndTime(0,1);

calcStopTime = calcTime(firstBarTime,timeIncrement);
quitTradeTime = calcTime(lastBarTime,endTradeMinB4Close);



If time = calcStopTime then 
begin
       buyStop = HighD(0);
       shortStop = LowD(0);
       buysToday = 0;
       shortsToday = 0;
End;

if time >= calcStopTime and time < quitTradeTime then 
begin
	if buysToday = 0 then Buy next bar at buyStop stop;
	if shortsToday = 0 then Sell short next bar at shortStop stop;
end;

mp = marketPosition;

If mp = 1 then buysToday = 1;
If mp = -1 then shortsToday = 1;

SetStopLoss(stopLoss$);
setProfitTarget(profTarg$);
setExitOnClose;
Orbo EasyLanguage Code

 

 

 

Converting A String Date To A Number – String Manipulation in EasyLanguage

EasyLanguage Includes a Powerful String Manipulation Library

I thought I would share this function.  I needed to convert a date string (not a number per se) like “20010115” or “2001/01/15” or “01/15/2001” or “2001-01-15” into a date that TradeStation would understand.  The function had to be flexible enough to accept the four different formats listed above.

String Functions

Most programming languages have functions that operate strictly on strings and so does EasyLanguage.  The most popular are:

  • Right String (rightStr) – returns N characters from the right side of the string.
  • Left String (leftStr) – returns N character starting from the left side of the string
  • Mid String (midStr) – returns the middle portion of a string starting at a specific place in the string and advance N characters
  • String Length (strLen) – returns the number of characters in the string
  • String To Number (strToNum) – converts the string to a numeric representation.  If the string has a character, this function will return 0
  • In String (inStr) – returns location of a sub string inside a larger string ( a substring can be just one character long)

Unpack the String

If the format is YYYYMMDD format then all you need to do is remove the dashes or slashes (if there are any) and then convert what is left over to a number.   But if the format is MM/DD/YYYY format then we are talking about a different animal.  So how can you determine if the date string is in this format?  First off you need to find out if the month/day/year separator is a slash or a dash.  This is how you do this:

whereIsAslash = inStr(dateString,”/”);
whereIsAdash = inStr(dateString,”-“);

If either is a non zero then you know there is a separator.  The next thing to do is locate the first “dash or slash” (the search character or string).  If it is located within the first four characters of the date string then you know its not a four digit year.  But, lets pretend the format is “12/14/2001” so if the first dash/slash is the 3rd character you can extract the month string by doing this:

firstSrchStrLoc = inStr(dateString,srchStr);
mnStr= leftStr(dateString,firstSrchStrLoc-1);

So if firstSrchStrLoc = 3 then we want to leftStr the date string and extract the first two characters and store them in mnStr.  We then store what’s left of the date string in tempStr by using rightStr:

strLength = strLen(dateString);

tempStr = rightStr(dateString,strLength-firstSrchStrLoc);

Here I pass dateString and the strLength-firstSrchStrLoc – so if the dateString is 10 characters long and the firstSrchStrLoc is 3, then we can create a tempstring by taking [10 -3  = 7 ] characters from right side of the string:

“12/14/2001” becomes “14/2001” – once that is done we can pull the first two characters from the tempStr and store those into the dyStr [day string.]  I do this by searching for the “/” and storing its location in srchStrLoc.  Once I have that location I can use that information and leftStr to get the value I need.   All that is left now is to use the srchStrLoc and the rightStr function.

srchStrLoc = inStr(tempStr,srchStr);
dyStr = leftStr(tempStr,srchStrLoc-1);
yrStr = rightStr(tempStr,strLen(tempStr)-srchStrLoc);

Now convert the strings to numbers and multiply their values accordingly.

DateSTrToYYYMMDD = strToNum(yrStr) X 10000-19000000 + strToNum(mnStr) X 100 + strToNum(dyStr)

To get the date into TS format I have to subtract 19000000 from the year.  Remember TS represents the date in YYYMMDD  format.

Now what do  you do if the date is in the right format but simply includes the dash or slash separators.  All you need to do here is loop through the string and copy all non dash or slash characters to a new string and then convert to a number.  Here is the loop:

        tempStr = "";
        iCnt = 1;
        While iCnt <= strLength
        Begin
            If midStr(dateString,iCnt,1) <> srchStr then
            	tempStr += midStr(dateString,iCnt,1);
            	iCnt+=1;
        end;
        tempDate = strToNum(tempStr);
        DateStrToYYYMMDD = tempDate-19000000;

Here I use midStr to step through each character in the string.  MidStr requires a string and the starting point and how many characters you want returned from the string.  Notice I step through the string with iCnt and only ask for 1 character at a time.  If the character is not a dash or slash I concatenate tempStr with the non dash/slash character.  At the end of the While loop I simply strToNum the string and subtract 19000000.  That’s it!  Remember EasyLanguage is basically a full blown programming language with a unique set of functions that relate directly to trading.

Here is the function and testFunc caller.

STRINGFUNCANDFUNCCALLER

 

The Complete Turtle EasyLanguage [Well About as Close as You Can Get]

The Complete Turtle EasyLanguage – Almost!

I have seen a plethora of posts on the Turtle trading strategies where the rules and code are provided.  The codes range from a mere Donchian breakout to a fairly close representation.  Without dynamic portfolio feedback its rather impossible to program the portfolio constraints as explained by Curtis Faith in his well received “Way Of The Turtle.”  But the other components can be programmed rather closely to Curtis’ descriptions.   I wanted to provide this code in a concise manner to illustrate some of EasyLanguage’s esoteric constructs and some neat shortcuts.  First of all let’s take a look at how the system has performed on Crude for the past 15 years.

Turtle Performance on Crude past 15 years

If a market trends, the Turtle will catch it.  Look how the market rallied in 2007 and immediately snapped back in 2008, and look at how the Turtle caught the moves – impressive.  But see how the system stops working in congestion.  It did take a small portion of the 2014 move down and has done a great job of catching the pandemic collapse and bounce.  In my last post, I programmed the LTL (Last Trader Loser) function to determine the success/failure of the Turtle System 1 entry.  I modified it slightly for this post and used it in concert with Turtle System 2 Entry and the 1/2N AddOn pyramid trade to get as close as possible to the core of the Turtle Entry/Exit logic.

Can Your Program This – sure you CAN!

Can You Program This?

I will provide the ELD so you can review at your leisure, but here are the important pieces of the code that you might not be able to derive without a lot of programming experience.

If mp[1] <> mp and mp <> 0 then 
begin
	if mp = 1 then
	begin	
		origEntry = entryPrice;
		origEntryName = "Sys1Long";
		If ltl = False and h >= lep1[1] then origEntryName = "Sys2Long";
	end;
	if mp =-1 then
	begin	
		origEntry = entryPrice;
		origEntryName = "Sys1Short";
		If ltl = False and l <= sep1[1] then origEntryName = "Sys2Short";
	end;
end;
Keeping Track Of Last Entry Signal Price and Name

This code determines if the current market position is not flat and is different than the prior bar’s market position.  If this is the case then a new trade has been executed.  This information is needed so that you know which exit to apply without having to forcibly tie them together using EasyLanguage’s from Entry keywords.  Here I just need to know the name of the entry.  The entryPrice is the entryPrice.  Here I know if the LTL is false, and the entryPrice is equal to or greater/less  than (based on current market position) than System 2 entry levels, then I know that System 2 got us into the trade.

If mp = 1 and origEntryName = "Sys1Long" then Sell currentShares shares next bar at lxp stop;
If mp =-1 and origEntryName = "Sys1Short" then buyToCover currentShares shares next bar at sxp stop;

//55 bar component - no contingency here
If mp = 0 and ltl = False then buy("55BBO") next bar at lep1 stop;
If mp = 1 and origEntryName = "Sys2Long" then sell("55BBO-Lx") currentShares shares next bar at lxp1 stop;

If mp = 0 and ltl = False then sellShort("55SBO") next bar at sep1 stop;
If mp =-1 and origEntryName = "Sys2Short" then buyToCover("55SBO-Sx") currentShares shares next bar at sxp1 stop;
Entries and Exits

The key to this logic is the keywords currentShares shares.  This code tells TradeStation to liquidate all the current shares or contracts at the stop levels.  You could use currentContracts contracts if you are more comfortable with futures vernacular.

AddOn Pyramiding Signal Logic

Before you can pyramid you must turn it on in the Strategy Properties.

Turn Pyramiding ON
If mp = 1 and currentShares < 4 then buy("AddonBuy") next bar at entryPrice + (currentShares * .5*NValue) stop;
If mp =-1 and currentShares < 4 then sellShort("AddonShort") next bar at entryPrice - (currentShares * .5*NValue) stop;

This logic adds positions on from the original entryPrice in increments of 1/2N.  The description for this logic is a little fuzzy.  Is the N value the ATR reading when the first contract was put on or is it dynamically recalculated?  I erred on the side of caution and used the N when the first contract was put on.  So to calculate the AddOn long entries you simply take the original entryPrice and add the currentShares * .5N.  So if currentShares is 1, then the next pyramid level would be entryPrice + 1* .5N.  If currentShares is 2 ,then entryPrice + 2* .5N and so on an so forth.  The 2N stop trails from the latest entryPrice.  So if you put on 4 contracts (specified in Curtis’ book), then the trailing exit would be 2N from where you added the 4th contract.  Here is the code for that.

Liquidate All Contracts at Last Entry –  2N

vars: lastEntryPrice(0);
If cs <= 1 then lastEntryPrice = entryPrice;
If cs > 1 and cs > cs[1] and mp = 1 then lastEntryPrice = entryPrice + ((currentShares-1) * .5*NValue);
If cs > 1 and cs > cs[1] and mp =-1 then lastEntryPrice = entryPrice - ((currentShares-1) * .5*NValue);

//If mp = -1 then print(d," ",lastEntryPrice," ",NValue);

If mp = 1 then sell("2NLongLoss") currentShares shares next bar at lastEntryPrice-2*NValue stop;
If mp =-1 then buyToCover("2NShrtLoss") currentShares shares next bar at lastEntryPrice+2*NValue Stop;
Calculate Last EntryPrice and Go From There

I introduce a new variable here: cs.  CS stands for currentShares and I keep track of it from bar to bar.  If currentShares or cs is less than or equal to1 I know that the last entryPrice was the original entryPrice.  Things get a little more complicated when you start adding positions – initially I couldn’t remember if EasyLanguage’s entryPrice contained the last entryPrice or the original – turns out it is the original – good to know.  So, if currentShares is greater than one and the current bar’s currentShares is greater than the prior bar’s currentShares, then I know I added on another contract and therefore must update lastEntryPrice.  LastEntryPrice is calculated by taking the original entryPrice and adding (currentShares-1) * .5N.  Now this is the theoretical entryPrice, because I don’t take into consideration slippage on entry.  You could make this adjustment.  So, once I know the lastEntryPrice I can determine 2N from that price.

Getting Out At 2N Trailing Stop

If mp = 1 then sell("2NLongLoss") currentShares shares next bar at lastEntryPrice-2*NValue stop;
If mp =-1 then buyToCover("2NShrtLoss") currentShares shares next bar at lastEntryPrice+2*NValue Stop;
Get Out At LastEntryPrice +/-2N

That’s all of the nifty code.  Below is the function and ELD for my implementation of the Turtle dual entry system.   You will see some rather sophisticated code when it comes to System 1 Entry and this is because of these scenarios:

  • What if you are theoretically short and are theoretically stopped out for a true loser and you can enter on the same bar into a long trade.
  • What if you are theoretically short and the reversal point would result in a losing trade.  You wouldn’t  record the loser in time to enter the long position at the reversal point.
  • What if you are really short and the reversal point would results in a true loser, then you would want to allow the reversal at that point

There are probably some other scenarios, but I think I covered all bases.  Just let me know if that’s not the case.  What I did to validate the entries was I programmed a 20/10 day breakout/failure with a 2N stop and then went through the list and deleted the trades that followed a non 2N loss (10 bar exit for a loss or a win.)  Then I made sure those trades were not in the output of the complete system.  There was quite a bit of trial and error.  If you see a mistake, like I said, just let me know.

Remember I published the results of different permutations of this strategy incorporating dynamic portfolio feedback at my other site www.trendfollowingsystems.com.  These results reflect the a fairly close portfolio that Curtis suggests in his book.

TURTLELTLFUNCTEST

 

Implementing Finite State Machine Functionality with EasyLanguage (Last Trade Was Loser Filter a la Turtle)

Last Trade Was a Loser Filter – To Use or Not To Use

Premise

A major component of the Turtle algorithm was to skip the subsequent 20-day break out if the prior was a winner.  I guess Dennis believed the success/failure of a trade had an impact on the outcome of the subsequent trade.  I have written on how you can implement this in EasyLanguage in prior posts, but I have been getting some questions on implementing FSM in trading and thought this post could kill two birds with one stone: 1) provide a template that can be adapted to any LTL mechanism and 2) provide the code/structure of setting up a FSM using EasyLanguage’s Switch/Case structure.

Turtle Specific LTL Logic

The Turtle LTL logic states that a trade is a loser if a 2N loss occurs after entry.  N is basically an exponential-like moving average of TrueRange.  So if the market moves 2N against a long or short position and stops you out, you have a losing trade.  What makes the Turtle algorithm a little more difficult is that you can also exit on a new 10-day low/high depending on your position.  The 10-day trailing exit does not signify a loss.  Well at least in this post it doesn’t.  I have code that says any loss is a loss, but for this explanation let’s just stick to a 2N loss to determine a trade’s failure.

How To Monitor Trades When Skipping Some Of Them

This is another added layer of complexity.  You have to do your own trade accounting behind the scenes to determine if a losing trade occurs.  Because if you have a winning trade you skip the next trade and if you skip it how do you know if it would have been a winner or a loser.  You have to run a theoretical system in parallel with the actual system code.

Okay let’s start out assuming the last trade was a winner.  So we turn real trading off.  As the bars go by we look for a 20-Day high or low penetration.  Assume a new 20-Day high is put in and a long position is established at the prior 20-Day high.  At this point you calculate a 2N amount and subtract if from the theoretical entry price to obtain the theoretical exit price.  So you have a theoMP (marketPosition) and a theoEX (exit price.)  This task seems pretty simple, so you mov on and start looking for a day that either puts in a new 10-Day low or crosses below your theoEX price.  If a new 10-Day low is put in then you continue on looking for a new entry and a subsequent 2N loss.  If a 2N loss occurs, then you turn trading back on and continue monitoring the trades – turning trading off and then back on when necessary.  In the following code I use these variables:

  • state – 0: looking for an entry or 1: looking for an exit
  • lep – long entry price
  • sep– short entry price
  • seekLong – I am seeking a long position
  • seekShort – I am seeking a short position
  • theoMP – theoretical market position
  • theoEX – theoretical exit price
  • lxp – long exit price
  • sxp – short exit price

Let’s jump into the Switch/Case structure when state = 0:

	Switch(state)
	Begin
		Case 0:
			lep = highest(h[1],20) + minMove/priceScale;
			sep = lowest(l[1],20) - minMove/priceScale;
			If seekLong and h >= lep then 
			begin
				theoMP = 1;
				theoEX = maxList(lep,o) - 2 * atr; 
//				print(d," entered long >> exit at ",theoEX," ",atr);
			end;
			If seekShort and l <= sep then 
			begin
				theoMP = -1;
				theoEX = minList(sep,o) + 2 * atr;
			end;
			If theoMP <> 0 then 
			begin
				state = 1;
				cantExitToday = True;
			end;
State 0 (Finite State Set Up)

The Switch/Case is a must have structure in any programming language.  What really blows my mind is that Python doesn’t have it.  They claim its redundant to an if-then structure and it is but its so much easier to read and implement.  Basically you use the Switch statement and a variable name and based on the value of the variable it will flow to whatever case the variable equates to.  Here we are looking at state 0.  In the CASE: 0  structure the computer calculates the lep and sep values – long and short entry levels.  If you are flat then you are seeking a long or a short position.  If the high or low of the bar penetrates it respective trigger levels then theoMP is set to 1 for long or -1 for short.  TheoEX is then calculated based on the atr value on the day of entry.  If theoMP is set to either a 1 or -1, then we know a trade has just been triggered.  The Finite State Machine then switches gears to State 1.  Since State = 1 the next Case statement is immediately evaluated.  I don’t want to exit on the same bar as I entered (wide bars can enter and exit during volatile times) I use a variable cantExitToday.  This variable delays the Case 1: evaluation by one bar.

State = 1 code:

		Case 1:
			If not(cantExitToday) then
			begin
				lxp = maxList(theoEX,lowest(l[1],10)-minMove/priceScale);
				sxp = minList(theoEX,highest(h[1],10)+minMove/priceScale);	
				If theoMP = 1 and l <= lxp then
				begin
					theoMP = 0;
					seekLong = False;
					if lxp <= theoEX then 
						ltl = True
					Else 
						ltl = False;
				end;
				If theoMP =-1 and h >= sxp then
				begin
					theoMP = 0;
					seekShort = False;
					if sxp >= theoEX then 
						ltl = True
					else 
						ltl = False;
				end;
				If theoMP = 0 then state = 0;
			end;
			cantExitToday = False;	
	end;
State = 1 (Switching Gears)

Once we have a theoretical position, then we only examine the code in the Case 1: module.  On the subsequent bar after entry, the lxp and sxp (long exit and short exit prices) are calculated.  Notice these values use maxList or minList to determine whichever is closer to the current market action – the 2N stop or the lowest/highest low/high for the past 10-daysLxp and sxp are assigned whichever is closer.  Each bar’s high or low is compared to these values.  If theoMP = 1 then the low is compared to lxp.  If the low crosses below lxp, then things are set into motion.  The theoMP is immediately set to  0 and seekLong is turned to False.  If lxp <= a 2N loss then ltl (last trade loser) is set to true.  If not, then ltl is set to False.   If theoMP = 0 then we assume a flat position and switch the FSM back to State 0 and start looking for a new trade.  The ltl variable is then used in the code to allow a real trade to occur.

Strategy Incorporates Our FSM Output

vars:N(0),mp(0),NLossAmt(0);
If barNumber = 1 then n = avgTrueRange(20);
if barNumber > 1 then n = (n*19 + trueRange)/20;

If useLTLFilter then
Begin
	if ltl then buy next bar at highest(h,20) + minMove/priceScale stop;
	if ltl then sellShort next bar at lowest(l,20) -minMove/priceScale stop;
end
Else
Begin
	buy next bar at highest(h,20) + minMove/priceScale stop;
	sellShort next bar at lowest(l,20) -minMove/priceScale stop;
end;

mp = marketPosition;

If mp <> 0 and mp[1] <> mp then NLossAmt = 2 * n;

If mp = 1 then
Begin
	Sell("LL10-LX") next bar at lowest(l,10) - minMove/priceScale stop;
	Sell("2NLS-LX") next bar at entryPrice - NLossAmt stop;
end;
If mp =-1 then
Begin
	buyToCover("HH10-SX") next bar at highest(h,10) + minMove/priceScale stop;
	buyToCover("2NLS-SX") next bar at entryPrice + NLossAmt stop;
end;
Strategy Code Using ltl filter

This code basically replicates what we did in the FSM, but places real orders based on the fact that the Last Trade Was A Loser (ltl.)

Does It Work – Only Trade After a 2N-Loss

Last Trade Loser In Action

Without Filter on the last 10-years in Crude Oil

With Filter on the last 10-years in Crude Oil

I have programmed this into my TradingSimula-18 software and will show a portfolio performance with this filter a little later at www.trendfollowingsystems.com.

I had to do some fancy footwork with some of the code due to the fact you can exit and then re-enter on the same bar.  In the next post on this blog I will so you those machinations .  With this template you should be able to recreate any last trade was a loser mechanism and see if it can help out with your own trading algorithms.  Shoot me an email with any questions.

 

 

 

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