#### EnlightenedJoe

##### Experienced member

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How do you make this out?

Same way he declares a net loss as a net win.

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How do you make this out?

Same way he declares a net loss as a net win.

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How do you make this out?

Staring capital 100,000

after 1 LOSS capital 97,500

after 2 LOSS capital 95,062

after 3 LOSS capital 92,685

after 4 LOSS capital 90,368

after 5 LOSS capital 88,109

after 6 LOSS capital 85,906

after 7 LOSS capital 83,759

after 8 LOSS capital 81,664

after 9 LOSS capital 79,622

after 10 LOSS capital 77,632

after 11 LOSS capital 75,691

When you add in revenge trades , mistakes , double ups on size and the beginner Joe "get my money back from Mr MARKET" , the additional losses will result , as a result of above trades.This is more practical and really more likely , than your theoretical figures.

This is more practical and really more likely , than your theoretical figures.

And this is the conundrum concerning trading - it isn't hard and it isn't risky, but still so few people can do it.

The majority of traders lose because they cannot let themselves run a boring strategy, whether they bought it or built it.

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People lose because they buy high sell low. Winners will always buy low sell high.

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3% is the most anyone should ever risk per trade.

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3% is the most anyone should ever risk per trade.

Do you know real profits in reality?

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I've done a lot of work on position sizing and would have to agree with Quantt here. There is no 'correct' position size. It depends on a lot of things, particularly your (or your investors') risk appetite and expectations.

I am learning Python and have built a basic simulation that can help you understand your trading edge and the impact of position sizing a bit more. unfortunately I haven't yet learnt how to get it online so you can play around with it yourselves but I hope to achieve that in the coming days. for now i'm happy to run anyone's numbers through it and feedback on here (or via PM) if it's of interest. I'd also appreciate feedback as to what other metrics people would think to be useful outputs.

Input variables (you should have a good grasp of these for your own trading):

- Account size

- % of capital at risk per trade

- Win rate(0-100%)

- Average win:loss ratio

- Number of trades (probably best to use trades per year to give idea of annual returns)

- The minimum returns you would be satisfied with (over that same time period)

- The maximum drawdown you would tolerate

For example: $100,000 account, 1% risk per trade, 35% win ratio, 4 win:loss ratio, 100 trades/year, min tolerated returns 10%, max tolerable drawdown 5%.

From these I can give the following outputs which I hope would help you understand your situation a little better:

Average Return:73.56%

Ave. Max. Drawdown:-7.68%

Ave Max Drawdown Duration:21.0

Average Max Cons Losses:9.0

Max Return: 130.0%

Min Return: 15.0%

Max Drawdown:-20.0%

Max Drawdown Duration:72

Max Cons Losses:19.0

Std Dev of Returns: 22.35%

Std Dev of Drawdowns: 3.16%

Probability of >10.0 pc return:100.0%

Probability of >5.0 pc drawdown:82.0%

So while it might look like a very attractive trading approach/system initially, if you're working at a prop shop with a 5% stop (you get fired when you lose 5% of capital) then all of a sudden it looks like 1% per trade is perhaps a bit much as there's a 82% chance you will exceed a 5% loss over the course of the year. If you already understand your trading approach/system it's unlikely you will see an improvement in your win rate or win ratio over the long run so optimising your position size according to your risk tolerance is your best bet of holding on to your capital/your job whilst maximising your returns. It all relies on a good initial understanding of your trading though which most retail guys lack unfortunately.

It always pays to remember also that every trade you will ever take will be either too big or too small...!

So if you are a high frequency scalper who regularly takes 7-8 losing trades in an hour , 1% is probably too aggressive . Conversely a position trader taking one trade a month and who maybe expects a maximum of 4-5 losses before a drawdown ends , 3-4% seems more appropriate . All depends on what you could tolerate as your max dd

There are probably some very good formulas out there to work out this kind of thing too

Unfortunately, all those numbers are arbitrary... you need to apply something like the Kelly criterion (not perfect, but a good start) on your past trades to determine the risk level for your trading system...

I agree, I work with 2% as in my plan. It has to be a truly exceptional circumstance to move from this. Last week when Provident took a dive was the only time in many months that I made a decision to increase risk threshold. And not by much to be honest. If news feed had not included top guy walking out I would of used 2%.

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It allows you to bear the brunt of a losing streak and comeback .

Live to trade another day so too speak .

2% is my max but fair play to others with bigger risk tolerance

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Simply with a dreadful run of variance I can go longer without winning without blowing the account.

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I start at 5% most trades and scale into my winning trades.

I don't think this is crazy.

I start at 5% most trades and scale into my winning trades.

Your risk tolerance in percent of account capital at risk per trade should be dependent on your strategy's long-term performance. If you don't know what this is, it is essential to run the absolute minimum risk per trade until you have more reliable data. But once you are certain of the strategy's probabilities, this amount should be ramped up.

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What if you have a 90% hit with 1R+?

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If you know the order of your losses, then just skip those losses so that you have a 100% win rate!

Then you have a tremendous strategy.What if you have a 90% hit with 1R+?

If your risk is 1% of your account capital and this is starting at only $1000 and you only make one trade per day, you will be the richest person you know.

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