How do you guys keep your 'Ego' in check?

[Gringotts Bank]

The calculation of a potential losing streak based solely on average winning % using maths that has an assumption (whether the person realised or not) of randomness is a long way from useful information for position sizing but hey its probably better than most use.

I feel it's an acceptable assumption if the win rate is 70% or higher and the number of trades in the backtest is high and frequent and the Monte Carlo runs are tightly packed.

If all of these 3 conditions are satisfied, then the likelihood of say 15 losers in a row is going to be extremely low. Then adjust position sizing to accomodate that safely. And if using a Martingale approach to size up after a loser, then this needs particular attention.

I'm sure it's possible to do this on a more sophisticated level, but this is enough for me, a part time trader.

 

[craft]

What is their to explain??? .

I'm not after a definition, explain to me how you position size to avoid your risk of ruin.

 

[craft]

I feel it's an acceptable assumption if the win rate is 70% or higher and the number of trades in the backtest is high and frequent and the Monte Carlo runs are tightly packed.

If all of these 3 conditions are satisfied, then the likelihood of say 15 losers in a row is going to be extremely low. Then adjust position sizing to accomodate that safely. And if using a Martingale approach to size up after a loser, then this needs particular attention.

I'm sure it's possible to do this on a more sophisticated level, but this is enough for me, a part time trader.

2 wins 1 loss 2 wins 1 loss 2 wins 1 loss is vastly different for position sizing purposes than 3 losses 7 wins series even though they re both 70% win rates. Now throw in a wide ranging distribution of win amounts as compared to a to a tight range that could both equal the same average R amount and you should start to see the issue. And forget about Monte Carlo as it to has an underlying assumption of no serial correlation. If you were using it on inflation data it would tell you that you can have 15% immediately followed by 1% because they are both in the population even though we know that doesn't happen in reality and it doesn't make any more sense to ignore the serial correlation of bull an bear market effects on your trading results.

 

[Gringotts Bank]

And forget about Monte Carlo as it to has an underlying assumption of no serial correlation.

As far as I know, a Monte Carlo is a test for serial correlation bias. Trade order gets re-arranged to find the best and worst outcomes, and everything in between. If the runs are tightly packed (as mentioned), this tells me serial correlation is absent or minimal. Therefore I don't need to worry about getting a run of losers out of the blue - they will be randomly distributed amongst the winners.

 

[Quant]

I'm not after a definition, explain to me how you position size to avoid your risk of ruin.

I certainly dont want to waste too much of my time banging my head against a wall explaining it . Basically put , the lower the win success rate the larger the number of consecutive losses you will have , the larger the sample the bigger the probability of larger runs of consec losses , you need to keep your position size at a level that WHEN one of these high number runs occurs your account is not Drawdown to a level where recovery is unlikely in a reasonable time frame or at all , as my visuals indicate a large enough drawdown will make what was a successful R become redundant . I really cant be bothered tbh

Low win rates have large runs of losers
large runs of losers create large equity drawdowns
large runs of losers will reduce position size making recovery slow and or totally unlikey
therefore low win rates require smaller position sizing

a low win rate start with same positive expectancy has a higher chance of ruin than a high win rate strategy assuming same position size

to explain this all properly some probability bell curves are needed , i really cant be bothered putting the time in 4 no reward tbh

this all im saying and its way more than i planned to ..... GOOGLE IT ... positive expectancy , probability curves


AND ego has nothing to do with it whatsoever , maths and probability are facts , definable and irrefutable although im sure you will find a way

 

[Quant]

As far as I know, a Monte Carlo is a test for serial correlation bias. Trade order gets re-arranged to find the best and worst outcomes, and everything in between. If the runs are tightly packed (as mentioned), this tells me serial correlation is absent or minimal. Therefore I don't need to worry about getting a run of losers out of the blue - they will be randomly distributed amongst the winners.

i was going to post a series of montecarlos with big numbers of low win rate and high win rate success rates with same expectancy but i cant be bothered , id rather work on something rewarding

I hate jumping through hoops , the train is of the rails

 

[craft]

i was going to post a series of montecarlos with big numbers of low win rate and high win rate success rates with same expectancy but i cant be bothered , id rather work on something rewarding

I hate jumping through hoops , the train is of the rails

I certainly dont want to waste too much of my time banging my head against a wall explaining it . Basically put , the lower the win success rate the larger the number of consecutive losses you will have , the larger the sample the bigger the probability of larger runs of consec losses , you need to keep your position size at a level that WHEN one of these high number runs occurs your account is not Drawdown to a level where recovery is unlikely in a reasonable time frame or at all , as my visuals indicate a large enough drawdown will make what was a successful R become redundant . I really cant be bothered tbh

Low win rates have large runs of losers
large runs of losers create large equity drawdowns
large runs of losers will reduce position size making recovery slow and or totally unlikey
therefore low win rates require smaller position sizing

a low win rate start with same positive expectancy has a higher chance of ruin than a high win rate strategy assuming same position size

to explain this all properly some probability bell curves are needed , i really cant be bothered putting the time in 4 no reward tbh

this all im saying and its way more than i planned to ..... GOOGLE IT ... positive expectancy , probability curves


AND ego has nothing to do with it whatsoever , maths and probability are facts , definable and irrefutable although im sure you will find a way

You keep restating the blindingly obvious that low win rates have more losers – Nobody’s arguing except it would seem you against your perceptions.....

Maybe you have missed what is being said here. Which is simply that there is much more to position sizing than Win%.

Or perhaps you think that only win rate matters – which you don’t because you acknowledge in your straw man arguments that the impact of R as part of the expectancy calc.

But beyond even expectancy based on average W and Average R the distribution and sequence is important to position sizing and the sequence is influenced by serial correlation which Monte Carlo doesn’t handle well.

You call yourself Quant surely you know this stuff.......

Peter2 who you laid into with your first post instinctively knows it through his experience and demonstrates it in his trade management displayed in his thread.

The OP asked how he can keep his Ego in check and not trade too big – He demonstrated one way – learn the hard way with the market handing you the lesson – the other way is to properly understand position sizing – but you try and have a discussion on this site and it always end with people behaving like you have that kills all possibilities of anything beneficial being discussed.

I'm not after a definition, explain to me how you position size to avoid your risk of ruin.

Forget I asked.

As far as I know, a Monte Carlo is a test for serial correlation bias. Trade order gets re-arranged to find the best and worst outcomes, and everything in between. If the runs are tightly packed (as mentioned), this tells me serial correlation is absent or minimal. Therefore I don't need to worry about getting a run of losers out of the blue - they will be randomly distributed amongst the winners.

Sorry GB, This discussion could have been good but I've lost enthusiasm. I think its worth challenging your beliefs in this area with a little deeper understanding of the tools you are relying upon. I know your smart so you could easily do this by yourself with out my distractions if you WANT.

 

[Quant]

You keep restating the blindingly obvious that low win rates have more losers – Nobody’s arguing except it would seem you against your perceptions.....



Or perhaps you think that only win rate matters – which you don’t because you acknowledge in your straw man arguments that the impact of R as part of the expectancy calc.

But beyond even expectancy based on average W and Average R the distribution and sequence is important to position sizing and the sequence is influenced by serial correlation which Monte Carlo doesn’t handle well.

You call yourself Quant surely you know this stuff.......

Peter2 who you laid into with your first post instinctively knows it through his experience and demonstrates it in his trade management displayed in his thread.

The OP asked how he can keep his Ego in check and not trade too big – He demonstrated one way – learn the hard way with the market handing you the lesson – the other way is to properly understand position sizing – but you try and have a discussion on this site and it always end with people behaving like you have that kills all possibilities of anything beneficial being discussed.

Forget I asked.




Sorry GB, This discussion could have been good but I've lost enthusiasm. I think its worth challenging your beliefs in this area with a little deeper understanding of the tools you are relying upon. I know your smart so you could easily do this by yourself with out my distractions if you WANT.

Its not that low win rates have more losers its the devastating runs of CONSECUTIVE Losses that increase the likelyhood of RUIN , you keep thinking your 30% or whatever trade success rate is elite . Low trade success rates by the very notion of large consecutive loss sequences severely limit practical position sizing A high win rate v low win rate strategy with the SAME positive expectancy has less chance of RUIN using same position size % , what is so hard to understand here . I refuse to debate something in which i am so obviously correct , its like debating a scientologist tbh I know i could give you irrefutable proof but i have no doubt it would not be enough for you ... good day , enjoy




PS EGO and position sizing have ZERO to do with each other , and if you are motivated to feed your EGO purely on large sizing you will be an ex trader (gambler) very quickly . You are not a trader unless you have an edge thats exploited systematically

 

[minwa]

I refuse to debate something in which i am so obviously correct , its like debating a scientologist tbh I know i could give you irrefutable proof but i have no doubt it would not be enough for you ... good day , enjoy


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Perhaps its time you go back to your self imposed ban of this forum from few months ago if you just come on here, calling other people morons because they don't agree you and you refuse to present anything ?

 

[Quant]

Perhaps its time you go back to your self imposed ban of this forum from few months ago if you just come on here, calling other people morons because they don't agree you and you refuse to present anything ?

there is nothing to debate here , I AM 100% RIGHT , i am not jumping through hoops for anyone . I am only giving back what i got first . Back to you feeding your EGO champ , good day and enjoy

 

[minwa]

there is nothing to debate here , I AM 100% RIGHT , i am not jumping through hoops for anyone . I am only giving back what i got first . Back to you feeding your EGO champ , good day and enjoy

Same crap as last time. Enjoy your stay

 

[cynic]

One of the things that seems to escape the attention of some, is that any strike rate below 100%, can theoretically result in large runs of consecutive losses!

There may exist a correlation between consecutive run lengths and single event's likelihood in theory! The world in which this theory is applied can ofttimes be quite different!

Probability theory is exactly that! A theory!

Results are these things that happen while traders are theorising other outcomes!

 

[Value Hunter]

I think sometimes the quant guys can get carried away with theories and numbers and forget that investing and trading is not a proper science. As Peter Lynch says its part science, part art and part leg work.

It is all well and good to use formulas to calculate risk, expectancy, to simulate things, etc but most of the time the inputs are garbage. For example how many investors or traders can even accurately estimate their future win rate? Or their average future win percentage? Or their future expectancy?or the number of bets/investments that will be made in the future? Garbage in = garbage out. They seem to be a bunch of tools which are merely used by some as a means of intellectual masturbation. In reality many of these quantitavie tools/analyses do have some use for professional quant funds but overall they have a very narrow and limited real world application, with many people gravely misusing the tools.

 

[Value Hunter]

Another issue I have is with people discussing geometric returns, etc. The old argument of if you lose 90% of your capital you have to get a 900% return (i.e. ten bagger) to break even again. While this is mathematically true it ignores a few important facts:
-Mean reversion. Studies have shown that stocks at 52 week lows, etc putperform the market.
-Intrinsic value is what will determine the future return over the long term. If a stock has an intrinsic value $10 per share and the share price is $10 per share when you buy and the stock then subsequently falls to $1 per share over the next twelve months due to sentiment, etc meanwhile the intrinsic value stays at $10 per share then assuming you hold for the long term and the value stays the same the stock will rise from $1 to $10 which is a ten bagger. It is not like a coin toss where if you got 5 heads in a row and you flip it again the odds of a heads is still 50% and thus unchanged from before. The probability of the stock being a ten bagger has increased after the share price fell because it is more undervalued. I am not omly talking about this only from a theoretical view point I have viewed it first hand that a stock that a stock I owned rose very strongly after falling sharply because it became more undervalued. Stock prices are obviously proven by both logic and empirical evidence to be at least partially path dependant at least in most circumstances.

 

[Value Hunter]

This whole quant obsession some people have reminds of the kelly formula. When people try to use the Kelly Formula (or half kelly) in the stock market (which it was not designed for). How can you accuretly estimate what probability of winning on any individual investment/stock is? Or for that matter the expected return if you do win? For the formula to work properly you have to be able to do this relatively accurately for each stock in your portfolio. If you stuff up the calculation on even one or two stocks you throw the whole portfolio out of wack. Also you cannot predict how many possible future bets/opportunities will come your way.

 

[minwa]

share price is $10 per share when you buy and the stock then subsequently falls to $1 per share over the next twelve months due to sentiment, etc meanwhile the intrinsic value stays at $10 per share then assuming you hold for the long term and the value stays the same the stock will rise from $1 to $10 which is a ten bagger.

Umm if you bought at $10, it went down to $1 and back $10, you've made nothing (maybe dividends which doesn't cover the opportunity cost), all you've done is went through a lot of headache, locking up your capital. OK so you were in a ten bagger..but you made nothing.

If your analysis says $10 is a good buy, and willing to hold it all the way down to $1 is insanity to me.

Ten bagger trades happen every single day in leveraged instruments.

 

[Value Hunter]

Minwa you missed the point. My point was that the past return does affect the future return.

 

[minwa]

Minwa you missed the point. My point was that the past return does affect the future return.

Ah OK fair enough, yes there are studies for buying 52w lows, but then there are also studies(experiment) like turtle traders, where they SHORT fresh lows and proved to be profitable. It's all contradictory so I don't think a conclusion like that can be made. If it's profitable for you great, but accept there are also people profitable with the opposing belief (shorting beaten down stocks).