[follow_me]I was speaking with Mike Chalek on the phone this weekend concerning Data Aliasing and he felt this post was a little confusing. After re-reading it I can see where he is coming from. Using the same example let me see if I can clarify: assume the trading day is Wednesday and you want to keep track of the slope of a 19-day weighted moving average of data2 (weekly bars) by using a variable. The following code will give an erroneous result:
wAvg = wAverage(c of data2,19);
mySlope = wAvg – wAvg[1];
If you interrogate mySlope intra-week then it will always be equal to zero. The wAvg is by default tied to data1 which in this case is daily bars. So the value of wAvg is carried over from one day to the next. It only changes when the average of the weekly bar changes and that only occurs on Friday.
There are two possible solutions:
Without the use of data aliasing – inLine function calls
mySlope = wAverage(c of data2,19) – wAverage(c[1] of data2,19) ;
With the use of data aliasing –
vars: wAvg(close of data2,0);
wAvg = wAverage(c of data2,19);
mySlop = wAvg – wAvg[1];
Either examples will work, but if you have several variables tied to a different data stream, then the code will be much cleaner looking using data aliasing – plus it cuts down on multiple function calls.
I have been working on a project where the strategy combined daily and weekly bars. Keeping track of the two time frames was, at one time, not that easy. However, with TradeStation’s Data Aliasing it is no problem at all. We all know that Data 1 is the highest resolution time frame and is the one used for trade execution. Data 2 can be a different market or a different time from of the same market. TradeStation allows for multiple data streams. Take a look at the following output in table 1. Wavg is a nine period moving average of weekly crude data. Wavg[1] is the prior value of the moving average. If you wanted to make a trading decision on a daily bar basis by looking at the slope of the Wavg you couldn’t. The Wavg and Wavg[1] only changes at the beginning of the next week. Most traders want to be able to make a trading decision intra-week by examining the current values of the Davg1, Davg2 and the slope of Wavg. During the week the slope of Wavg is ZERO.
Now look at table 2. The Wavg is not being updated on a daily basis but on a weekly basis. The current Wavg doesn’t become the prior Wavg on each daily bar. Wavg[1] stays the same until a new weekly bar occurs. You can now make a trading decision intra-week by examining the slope of the Wavg. Each time frame update should only occur when a new bar of that same time frame is generated. This feature is really cool and is easy to implement.
Here is the code that utilizes Data Aliasing. All I did was declare the weekly avg variable and tied it to data2.
vars: mavShortDaily(0),mavLongDaily(0);
vars: mavWeekly(0,data2);
mavShortDaily = average(c,19);
mavLongDaily = average(c,39);
mavWeekly = average(C of data2, 9);
If mavShortDaily > mavLongDaily and mavWeekly > mavWeekly[1] then buy this bar on close;
If mavShortDaily < mavLongDaily and mavWeekly < mavWeekly[1] then sellshort this bar on close;
print(date," ",mavShortDaily," ",mavLongDaily," ",mavWeekly," ",mavWeekly[1]);
Notice how the variable mavWeekly was tied to data2. When you delcare a variable that is tied to another data other than data1 you can put the data stream right in the variable delcaration : mavWeekly(0,data2).
In the next few weeks I will be providing EasyLanguage code utilizing FSMs to model trading systems. Cut your teeth on this model of a combination lock. The EasyLanguage will use the Switch and Case keywords to implement these models.
The easiest way to program a multi step criteria entry/exit signal is to use a Finite State Machine (FSM). This is much easier than setting flags and then having to turn them on and off. Here is a diagram of a FSM:
This is how you round to the nearest tick in EasyLanguage – helpful when plotting
price based indicators. Also the formula for calculating the min tick value is given.
vars: minTick(0),testPrice(0);
minTick = minMove/priceScale;
testPrice = close * .21 * range;
// round up
value1 = testPrice + (minTick-mod(testPrice,minTick));
// round dn
value2 = testPrice - (mod(testPrice,minTick));
{mod is a call to the modulus function
aka remainder function -- mod(12,5) = 2 -- 12/5 = 2 Remainder 2
say ES testPrice = 1123.57
minTick = .25
1123.57 + (0.25 - mod(1123.57,0.25)) = 1123.57 + 0.25 - 0.07 = 1123.75}
A very astute reader of the BWTSwTS2 has brought to my attention errors in my description of the Thermostat and Bollinger Bandit algorithms. In the Thermo description I incorrectly used the words yesterday and today. The code is correct in the book. Thanks to John for finding this!
Corrected description follows:
….If today’s closing price is greater than the average of today’s high,low and close, then we feel tomorrow’s action will probably be bearish. However, if today’s closing price is less than or equal to the average of today’s high, low, and close, then tomorrow’s market will behave in a bullish manner.
In addition John uncovered a typo as well for the Bollinger Bandit description – when I stated BELOW I meant ABOVE and vice versa.
Corrected description follows:
If liqPoint is BELOW the upband, we will liquidate a long position if today’s market action <= liqPoint.
If liqPoint is ABOVE the dnband, we will liquidate a long position if today’s market action >= liqPoint.
Several have brought it to my attention that the King Keltner code in the book is missing a couple of lines. Here’s the complete code in its entirety. Thanks for bringing this to my attention.
[LegacyColorValue = true];
{King Keltner Program
King Keltner by George Pruitt -- based on trading system presented by Chester Keltner
-- an example of a simple, robust and effective strategy}
Inputs: avgLength(40),atrLength(40);
Vars: upBand(0),dnBand(0),liquidPoint(0),movAvgVal(0);
movAvgVal = average((h+l+c)/3,avgLength);
upBand = movAvgVal + AvgTrueRange(atrLength);
dnBand = movAvgVal - AvgTrueRange(atrLength);
{Remember buy stops are above the market and sell stops are below the market
-- if the market gaps above the buy stop, then the order turns into a market order
vice versa for the sell stop}
if(movAvgVal > movAvgVal[1]) then Buy ("KKBuy") tomorrow at upBand stop;
if(movAvgVal < movAvgVal[1]) then SellShort("KKSell")tomorrow at dnBand stop;
liquidPoint = movAvgVal;
if(MarketPosition = 1) then Sell tomorrow at liquidPoint stop;
if(MarketPosition =-1) then BuyTocover tomorrow at liquidPoint stop;
I have requests from some users to program a little more sophisticated version of my trade input strategy. This is where you can simply list the trade, trade date, and trade price and TradeStation will plot the trades for you and calculate the performance. This is a an easier to use program then TS’s _HistoricalEntry strategy.
{If you are entering the next bar then use the prior bars date
Make sure your price is above or below open if stop or limit order
}
array: DateArray[1000](0),BorSArray[1000](""),PriceArray[1000](0);
vars: iCnt(1);
DateArray[1]=1141117; BorSArray[1]="S"; PriceArray[1]=75.00;
DateArray[2]=1141219; BorSArray[2]="F"; PriceArray[2]=59.01;
DateArray[3]=1150102; BorSArray[3]="B"; PriceArray[3]=53.10;
DateArray[4]=1150210; BorSArray[4]="S"; PriceArray[4]=50.00;
if date >= dateArray[1] then
begin
if date = dateArray[iCnt] then
begin
if BorSArray[iCnt] = "B" then buy next bar at PriceArray[iCnt] stop;
if BorSArray[iCnt] = "S" then sellShort next bar at PriceArray[iCnt] stop;
if BorSArray[iCnt] = "F" then
begin
if marketPosition = 1 then sell next bar at PriceArray[iCnt] stop;
if marketPosition =-1 then buytocover next bar at PriceArray[iCnt] stop;
end;
iCnt = iCnt + 1;
end;
end;
Like I stated in an earlier post the “Trend”, once a lost friend, is back. Check out the results from the King Keltner system as published in “Building Winning Trading Systems with TradeStation.” Looking at the results it looks like 2014 is as good as the “life saving” 2008. Is it time to re-think Trend Following – has the paradigm shifting pendulum swung back?
HYPOTHETICAL PERFORMANCE RESULTS HAVE MANY INHERENT LIMITATIONS, SOME OF WHICH ARE DESCRIBED BELOW. NO REPRESENTATION IS BEING MADE THAT ANY ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFITS OR LOSSES SIMILAR TO THOSE SHOWN. IN FACT, THERE ARE FREQUENTLY SHARP DIFFERENCES BETWEEN HYPOTHETICAL PERFORMANCE RESULTS AND THE ACTUAL RESULTS SUBSEQUENTLY ACHIEVED BY ANY PARTICULAR TRADING PROGRAM.
ONE OF THE LIMITATIONS OF HYPOTHETICAL PERFORMANCE RESULTS IS THAT THEY ARE GENERALLY PREPARED WITH THE BENEFIT OF HINDSIGHT. IN ADDITION, HYPOTHETICAL TRADING DOES NOT INVOLVE FINANCIAL RISK, AND NO HYPOTHETICAL TRADING RECORD CAN COMPLETELY ACCOUNT FOR THE IMPACT OF FINANCIAL RISK IN ACTUAL TRADING. FOR EXAMPLE, THE ABILITY TO WITHSTAND LOSSES OR TO ADHERE TO A PARTICULAR TRADING PROGRAM IN SPITE OF TRADING LOSSES ARE MATERIAL POINTS WHICH CAN ALSO ADVERSELY AFFECT ACTUAL TRADING RESULTS. THERE ARE NUMEROUS OTHER FACTORS RELATED TO THE MARKETS IN GENERAL OR TO THE IMPLEMENTATION OF ANY SPECIFIC TRADING PROGRAM WHICH CANNOT BE FULLY ACCOUNTED FOR IN THE PREPARATION OF HYPOTHETICAL PERFORMANCE RESULTS AND ALL OF WHICH CAN ADVERSELY AFFECT ACTUAL TRADING RESULTS.
I have often developed programs that use data that TradeStation may not have in their database, and later wanted to use the signals generated on that data and it apply it to another market. Here is a simple program that uses arrays to specify trade dates and signals. The code to interpret the arrays and then execute the orders follows:
array: DateArray[1000](0),BorSArray[1000]("");
vars: iCnt(1);
DateArray[1]=1081228; BorSArray[1]="S";
DateArray[2]=1081229; BorSArray[2]="B";
DateArray[3]=1090104; BorSArray[3]="S";
if date >= dateArray[1] then
begin
if date = dateArray[iCnt] then
begin
if BorSArray[iCnt] = "B" then buy this bar on close;
if BorSArray[iCnt] = "S" then sellShort this bar on close;
iCnt = iCnt + 1;
end;
end;
Notice how arrays are defined and declared. How do you think you would handle a system that goes flat?
Backtesting with [Trade Station,Python,AmiBroker, Excel]. Intended for informational and educational purposes only!
Get All Five Books in the Easing Into EasyLanguage Series - The Trend Following Edition is now Available!
Announcement – A Trend Following edition has been added to my Easing into EasyLanguage Series! This edition will be the fifth and final installment and will utilize concepts discussed in the Foundation editions. I will pay respect to the legends of Trend Following by replicating the essence of their algorithms. Learn about the most prominent form of algorithmic trading. But get geared up for it by reading the first four editions in the series now. Get your favorite QUANT the books they need!
This series includes five editions that covers the full spectrum of the EasyLanguage programming language. Fully compliant with TradeStation and mostly compliant with MultiCharts. Start out with the Foundation Edition. It is designed for the new user of EasyLanguage or for those you would like to have a refresher course. There are 13 tutorials ranging from creating Strategies to PaintBars. Learn how to create your own functions or apply stops and profit objectives. Ever wanted to know how to find an inside day that is also a Narrow Range 7 (NR7?) Now you can, and the best part is you get over 4 HOURS OF VIDEO INSTRUCTION – one for each tutorial.
This book is ideal for those who have completed the Foundation Edition or have some experience with EasyLanguage, especially if you’re ready to take your programming skills to the next level. The Hi-Res Edition is designed for programmers who want to build intraday trading systems, incorporating trade management techniques like profit targets and stop losses. This edition bridges the gap between daily and intraday bar programming, making it easier to handle challenges like tracking the sequence of high and low prices within the trading day. Plus, enjoy 5 hours of video instruction to guide you through each tutorial.
The Advanced Topics Edition delves into essential programming concepts within EasyLanguage, offering a focused approach to complex topics. This book covers arrays and fixed-length buffers, including methods for element management, extraction, and sorting. Explore finite state machines using the switch-case construct, text graphic manipulation to retrieve precise X and Y coordinates, and gain insights into seasonality with the Ruggiero/Barna Universal Seasonal and Sheldon Knight Seasonal methods. Additionally, learn to build EasyLanguage projects, integrate fundamental data like Commitment of Traders, and create multi-timeframe indicators for comprehensive analysis.
The Day Trading Edition complements the other books in the series, diving into the popular approach of day trading, where overnight risk is avoided (though daytime risk still applies!). Programming on high-resolution data, such as five- or one-minute bars, can be challenging, and this book provides guidance without claiming to be a “Holy Grail.” It’s not for ultra-high-frequency trading but rather for those interested in techniques like volatility-based breakouts, pyramiding, scaling out, and zone-based trading. Ideal for readers of the Foundation and Hi-Res editions or those with EasyLanguage experience, this book offers insights into algorithms that shaped the day trading industry.
For thirty-one years as the Director of Research at Futures Truth Magazine, I had the privilege of collaborating with renowned experts in technical analysis, including Fitschen, Stuckey, Ruggiero, Fox, and Waite. I gained invaluable insights as I watched their trend-following methods reach impressive peaks, face sharp declines, and ultimately rebound. From late 2014 to early 2020, I witnessed a dramatic downturn across the trend-following industry. Iconic systems like Aberration, CatScan, Andromeda, and Super Turtle—once thriving on robust trends of the 1990s through early 2010s—began to falter long before the pandemic. Since 2020 we have seen the familiar trends return. Get six hours of video instruction with this edition.
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