Last Trade Was a Loser Filter – To Use or Not To Use
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:
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:
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-days. Lxp 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
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
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.