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Adding to trades - best practice? Calculation attached
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Adding to trades - best practice? Calculation attached

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Adding to trades - best practice? Calculation attached

I've tried to model the ways you could manage the trade, to try and find what is best mathematically. The results are quite interesting.

4 scenarios's.
a) All in all out
b) Add contracts as the trade goes in your direction
c) Add contracts, and then start scaling out
d) Start scaling out as it moves in your favour.

They each have the same max loss / risk. As the trade moves in your favour you start adding size, so you aren't taking on more risk.

Each scenario has the exact same probabilities of reaching the various targets. I'm assuming you have a method / system - and so the outcome ultimately depends on how you manage the trade.

I have included 3 sheets.
a) 3 targets
b) 4 targets
c) 5 targets.

The reason being, at the start of the trade you are aiming for 5 targets (letting winners run), but perhaps you determine the market has changed after 3. So you exit. At that point you are only half way through your normal trade management - so I wanted to see how the results between management style would differ in that situation.

I've made the s/sheet so most things can be tinkered with (max risk, commission, equity etc etc). The most important one is the edge %. It gets interesting here. I was struggling in my head as to whether the edge % plays out over the entire trade. I came to the conclusion the probability of the market either going up or down (your edge %) stays the same regardless of how far price has moved. So if your edge is 56%, then after the 4th target there is still a 56% probability that price continues to move in your direction. I assume your edge includes being able to 'read' the market. So when have determined the market conditions have changed, and your edge no longer holds, you'll exit the trade - otherwise you are just gambling. For those who believe your probability decreases the further price moves in your favour, then there is an option on the 5 targets sheet to adjust the last 2 targets to random - i.e 50% of either going up or down.

Based on this s/sheet it is blatantly obvious the best method is to add to the trade, and then exit all out. And scaling out, without previously adding size just plain sucks. AIAO, even on small accounts sizes with a 10 points total target are a sub-optimal way to trade. And therein lies the reason why I'm posting this to the forum. It's quite possible there are errors or inconsistencies, or my logic is corrupt somewhere. So I'd appreciate it if people would look this over (or perhaps try and re-create your own and compare results) to see if you can find something I've done wrong.

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Register to download File Type: xlsx Scaling - theortical example.xlsx (60.7 KB, 32 views)
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  #3 (permalink)
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As tigertrader has said, there are three reasons to stay in a trade.

1. To make more money.
2. To make more money.
3. To make more money.


One thing I have to say though I guess I have understood AIAO as you enter with all the contracts you are going to trade, then exit all at once.

In your AIAO example you enter with 13, exit with 13. Whereas in your scaling strategies you are up to 67 contracts which doesnt seem to make sense to me.

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Quoting 
I came to the conclusion the probability of the market either going up or down (your edge %) stays the same regardless of how far price has moved. So if your edge is 56%, then after the 4th target there is still a 56% probability that price continues to move in your direction.

I am not sure exactly what you are meaning with this, but in my research, the probability of reaching a target declines the further away the target is from it's entry. This is consistent with any method of entry I have studied. It is this constant probability distribution that causes the 'random entry' study to come out break even when we modify the exit criteria (trade management). As the gross win per trade increases (ie. larger targets), the probability of a winning trade decreases, keeping the end result firmly fixed at break-even. In other words, there is no statistical advantage (edge) gained through trade management alone.

Be Patient and Trade Smart
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If you are trading your max size ofcourse AIAO is going to make theoretically the most money.

If you are scaling up like how your examples are essentially you are putting in a trailing stop.

For me the trick to adding to trades is to find 2nd entry points that allow my stop to remain way out of the trading range, and yet still be able to add to my trade.

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DeadCatBounced View Post
In your AIAO example you enter with 13, exit with 13. Whereas in your scaling strategies you are up to 67 contracts which doesnt seem to make sense to me.

That's the point of adding to the trade as it goes in your favour. AIAO assumes you are trading at your max size = max risk level. By getting up to 67 contracts as you build equity in the trade, you aren't taking on any more risk in terms of ultimate losses(unless of course you get unexpected adverse price move and incur massive slippage - and of course that would need to be considered when determining how many extra contracts to add).


DeadCatBounced View Post
If you are trading your max size ofcourse AIAO is going to make theoretically the most money.

For the reasons mentioned above, I can't see why AIAO is deemed better.


DeadCatBounced View Post
If you are scaling up like how your examples are essentially you are putting in a trailing stop.

Yes, that's the way I've put the spreadsheet together. It wasn't a question of finding out if trailing stops are/aren't effective - it was a matter of given the exact same price path and probabilities which way would you make more money.

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How did you come up with the %'s that each target was hit? Is this based off of your edge or is this just completely theoretical?

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trendwaves View Post
I am not sure exactly what you are meaning with this, but in my research, the probability of reaching a target declines the further away the target is from it's entry. This is consistent with any method of entry I have studied. It is this constant probability distribution that causes the 'random entry' study to come out break even when we modify the exit criteria (trade management). As the gross win per trade increases (ie. larger targets), the probability of a winning trade decreases, keeping the end result firmly fixed at break-even. In other words, there is no statistical advantage (edge) gained through trade management alone.

The 'random entry' study - by default will come out at breakeven - regardless of parameters. Try re-running your study with a statistical edge and adjusting trade management and see what happens. I'm quite sure it won't come out at BE.

With 50% edge (randomness) you have equal chance to get 5 points or lose 5 - and you also have a 50% chance to gain 50 or lose 50 (ignoring long term bullish drift etc). On that I'm sure we agree.

So with a 56% edge I have a slighter higher probability to get 5, than I do to lose 5. And I have that same slightly higher probability of 56% to gain 50, rather than lose 50. So on that logic, at each increment in price I have a 56% chance it will move in my favour by 2, rather than against me by 2. And so by extrapolating it out (assuming 5 targets of 2 points) you end up with a risk:reward of 2:10 with 44% chance of losing 2, and 5.5% chance of gaining the full 10. So on that I think we also agree - the larger the target (relative to risk), the smaller the win %.

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the main problem with all of this imo is that the market is not linear. Your edge occurs at certain moments, so by linearly scaling into a position, you are not scaling into your edge but scaling into randomness, regardless of the initial position's edge.

I am absolutely in favor of scaling into winning trades to size up the instances that work compared to those that don't - but the where, how and how much in my opinion can only be decided individually for each trade.

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DeadCatBounced View Post
How did you come up with the %'s that each target was hit? Is this based off of your edge or is this just completely theoretical?

Purely theoretical.

If your edge is 56% then you have a 56% chance it will go in your favour by x, and 44% it will go against you by x.

At x, (which happens 56% of the time) you then have a 56% chance it will go in your favour by x, and 44% chance it will go against you by x.

So you have:
44% = -x, [price went -x]
(56% x 44%) = 24.6% = Breakeven [price went +x, then -x]
(56% x 56%) = 31.4% = 2x [price went +x, then +x]
That adds up to 100%. You keep working this way breaking down the 31.4% into smaller % as the targets get further away.

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