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Risk of Ruin


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Risk of Ruin

  #121 (permalink)
Ian Lavoie
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Big Mike View Post

Kaufman gives us the following formula for calculating the risk of ruin:
risk_of_ruin = ((1 - Edge)/(1 + Edge)) ^ Capital_Units
Edge is the probability of a win.

There are a few different formulas floating around, and I've seen some requests to incorporate

I thought I would give a recap of online calculators that are out there since this post, as things have changed:

1) Chris Capre has updated his site to show an interactive calculator instead of just the published tables. The weakness of the calculator as well as the formula it is based on ignores the number of trades placed, and makes no provision for a profit target to be reached before being ruined.

2) The Au.Tra.Sy blog has an interactive calculator based on a monte carlo simulator. It does take inot account the number of trades (periods). It additionally allows you to set a drawdown level instead of ruin. However, it does not allow for a profit target.

3) Forex Scam Alerts has an online risk tool based on monte carlo simulations. It also considers the number of trades, and allows you to set a drawdown level as well. Further, it includes profit targets (retirement), which allows you to see what the probability is of hitting that target before reaching your drawdown limit. The downside of this tool is that it doesn't allow you to set an value you want, but only predetermined values that the tool looks up in a huge database on Monte Carlo simulations.

There are other similar calculators, but they are on blackjack sites, so are not built to be as applicable for traders.

Let me know if I have missed any good ones.

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  #122 (permalink)
 
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 DominionCuentas 
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Dear All,

I just want to say this:

"Risk of ruin has absolutely zero practical application in trading. Running through the calculations to determine the risk of ruin on any particular method is also completely useless."

'The Trading Game' by Ryan Jones.

Don't waste your time fellas.

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  #123 (permalink)
 
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 Fat Tails 
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virgo739 View Post
Dear All,

I just want to say this:

"Risk of ruin has absolutely zero practical application in trading. Running through the calculations to determine the risk of ruin on any particular method is also completely useless."

'The Trading Game' by Ryan Jones.

Don't waste your time fellas.


Risk of ruin is the key to position sizing. Position sizing is the key to growing a trading account, once you have found an edge and mastered trading psychology.

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  #124 (permalink)
 
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virgo739 View Post
Dear All,

I just want to say this:

"Risk of ruin has absolutely zero practical application in trading. Running through the calculations to determine the risk of ruin on any particular method is also completely useless."

'The Trading Game' by Ryan Jones.

Don't waste your time fellas.

I would like you explain in details what you find useless about it. Do you understand what it truly measures for each trader?

Matt Z
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  #125 (permalink)
 
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 JonnyBoy 
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virgo739 View Post
Dear All,

I just want to say this:

"Risk of ruin has absolutely zero practical application in trading. Running through the calculations to determine the risk of ruin on any particular method is also completely useless."

'The Trading Game' by Ryan Jones.

Don't waste your time fellas.

I 100% disagree with that statement. If you don't know your risk of ruin then you can't possibly size your positions.

The probability of ruin matrix is a calculation based on several pieces of data. First, it assumes 100 events; in this case that would be 100 trades. Next, it defines ruin as 50% drawdown from starting equity. Last, it assumes that the methodology used to initiate each event is always the same in every event; in other words each trade done during the 100 trades in the sample set is executed for exactly the same reason.

According to this matrix, if you do 100 trades, and have 42% winners and pull two dollars out for every dollar you give back, your probability of ruin is a little less than 14%. If you calculate the numbers yourself you will find that (42 x 2) - (58 x 1) actually yields a profit of $26, but the ruin matrix is using the full scope of probability theory. That includes the possibility that all the losing trades will come in the first 50% before the sample set of 100 trades is complete.

Notice that a high percentage of winning trades is not an indication that you will make money net in your account. Someone who has 55% winning trades to losing trades has a worse risk of ruin if he wins about the same amount as he loses every time. It actually has a better probability for your account if you have fewer winning trades but hold those winners for a higher profit/loss ratio. Of course, the best of all worlds is to be in the far right side of the matrix. A trader with 60% or more winning trades and only a slightly better profit/loss ratio than 1:1 has no chance of ruin.


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  #126 (permalink)
Neonmouse
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Silver Dragon View Post
Found this out of the Internet. Numbers look in line but would like some verfication.


Notes:
  • Cells highlighted in Yellow are what you fill in.
  • All other cells have formulas. Do not change!!
SD

You actually have mistake in your spreadsheet when calculating Z and A.
Pay attention to signs.

It must be like this:

Z = %profitable * avgwin% + %losing * avg loss%,
where avg loss% should be already with minus.

The same logic for A...

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  #127 (permalink)
 
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From another post.
SMCJB View Post
Then I built a quick Monte Carlo/Risk of Ruin spreadsheet. The spreadsheet calculates 500 simulations of 100 trades. The two illustrations show the impact of starting account size of a theoretical trading system with an average trade PnL of $500 and Standard Deviation of $1500. Notice how better the starting account size of $10k is than $5k. This is driven by the much lower number of simulations that get 'ruined'.




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  #128 (permalink)
 
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 brach 
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A very interesting thread that I'm obviously late to.

Just thought I would share something I read a while back on Johann Lotter's (aka jcl) "Financial Hacker" blog.

He uses a long-run theoretical math approach to argue that however you determine your % risk for each trade, the % should scale sub-linearly with the size of your account. Specifically, he suggests that % risk should scale proportionally to the square root of account size. i.e. if you double your account, the absolute amount risked should increase by (1.41/2) or approx 70.5% instead of 100%.

If you do scale linearly, in the long-run (and he does mean LONG run aka infinitely long), the risk of ruin is 100%. This may be too conservative for practical purposes because as Keynes said we're all dead in the long run... but I think it's still worth keeping in mind if scaling linearly makes you feel uncomfortable.

In addition to authoring this blog, jcl is the author of the "Black Book of Financial Hacking" and one of the lead developers of the zorro backtesting tool.

See section 9 in this blog post: https://financial-hacker.com/build-better-strategies-part-3-the-development-process/

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  #129 (permalink)
 
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Recently, @SMCJB made the below post in a different thread:



Here is the full post:


SMCJB View Post
Sorry @datahogg I wasn't trying to contradict you I was supporting your observation that these scenario's create very skewed distributions.

When it comes to something simple like coin flips, or anything were probabilities and payouts are fixed, it's often not hard to get actual results from closed form calculations rather than simulations. For example since 1/(0.5^20) = 1,048,576 we can say that if you flip a coin 20 times in a row, you have an approximate 1 in Million chance of getting 20 heads and also a 1 in Million chance of 20 tails.

The big limitation of this is that these calcs are all based upon final outcomes and do not consider path dependency which can be important. For example assume you start with $10k, lose 10% of your money 7 trades in a row and then make 10% of money in the next 8 trades. Simple calcs (0.9^7*1.1^*8) will tell you that you end up with $10253 a winning scenario. In reality at the end of the 7th trade your down to $4782 in equity, and hence if you need $5000 in margin to place the 8th trade you can't make the trade, you are 'ruined' and your final outcome is $4782 and not $10253.

If you flip a coin 50 times, you win 50% on a head, but lose 50% on a tail, and you consider yourself ruined when you lose 90% of your starting pot, then I believe almost 90% of sims/scenarios will end in you being ruined. Just under 7% will finish with less than they started but not be ruined (average 32.6% of starting pot). Finally the 3% of people who finish with more than they started with, finish with a pot on average almost 3000% of what they started with. This is heavily skewed by the top 0.00015% (1 in 6538) who average a return over 300,000%.

It's actually quite easy to convert these numbers based upon how much you want to risk. In the same 50/50 game with +50/-50 payouts, if you risk 6% of your pot, then this is the same as a 50/50 game with payout +3/-3 where you bet everything. No nobody is ruined, because even if you lose 50 times in a row you still have 21% of your initial pot (0.97^50). This is based upon betting 6% of your CURRENT pot at each bet. If you bet 6% of your INITIAL pot at each bet, the numbers are very different as obviously you can only lose 16 times more than you win before you are ruined

I really liked this post and talking about these topics, and it reminded me of my old old Risk of Ruin thread. So that is why I am cross-posting @SMCJB's contribution here, because I really want members to take a look at Risk of Ruin and learn about it, incorporate it into their thought process and their trading plans.

Mike

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  #130 (permalink)
 
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@kevinkdog just published a nice blog post on 'Risk of Ruin' at his site.

https://www.kjtradingsystems.com/risk-of-ruin.html

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