# certainty equivalent

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# certainty equivalent

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certainty equivalent

One of the statistics CVData shows is the CE (certainty equivalent). I’ve done a lot of reading on the topic, and I understand what the CE is supposed to represent from a generic investing perspective. I have started using it when I analyze games and spreads. BJ21 has a very detailed article on what it is, but I feel dumb trying to read the formulas

What is the formula CVData uses to compute the certainty equivalent?

One of the statistics CVData shows is the CE (certainty equivalent). I’ve done a lot of reading on the topic, and I understand what the CE is supposed to represent from a generic investing perspective. I have started using it when I analyze games and spreads. BJ21 has a very detailed article on what it is, but I feel dumb trying to read the formulas

What is the formula CVData uses to compute the certainty equivalent?

Eugh, the Certainty Equivalent makes my head hurt. As soon as I looked at the article I think you are referencing, I quickly appreciated Don Schlesinger’s general description of it.

Hopefully someone comes in here to give a good answer.

Spaw

Eugh, the Certainty Equivalent makes my head hurt.

From one mathie to another: Me too. I understand a lot of gambling math (and a lot of non-gambling math, up to and including the basics of differential equations). The only thing I get about CE is that it’s the amount of money I’d take not to play… but I don’t know why or how that number is derived :-/

Hmmm. Where is Assume_R when we need him ?

From one mathie to another: Me too. I understand a lot of gambling math (and a lot of non-gambling math, up to and including the basics of differential equations). The only thing I get about CE is that it’s the amount of money I’d take not to play… but I don’t know why or how that number is derived :-/

If you get a moment, could you send me the link to the page we were discussing. I can’t seem to find it and haven’t looked at it in a few months.

Thanks,

Spaw

This is the one I know of, though it isn’t by Don S.

http://www.bj21.com/bj_reference/pages/certaintyequivalentanalysis.shtml

I’ll have to flip through BJAIII when I get home and see if there’s anything in that about it.

This is the one I know of, though it isn’t by Don S.

http://www.bj21.com/bj_reference/pages/certaintyequivalentanalysis.shtml

I’ll have to flip through BJAIII when I get home and see if there’s anything in that about it.

Yes, this is it. Don Schlesinger doesn’t have anything other than generalities to describe CE.

Spaw

the kelly faq has some stuff on CE :

http://www.bjmath.com/bjmath/kelly/kellyfaq.htm (<- Archive copy of dead link)

Q2 thru Q5 ……

One of the statistics CVData shows is the CE (certainty equivalent). I’ve done a lot of reading on the topic, and I understand what the CE is supposed to represent from a generic investing perspective.

I think that CE is some negligible BS that MIT team came up with before they lost a million$s of OPM, yes? zg

My understanding

So I’ll try to explain as best as I understand it.

Firstly, the equation we use is WinRate – Std^2/(2*KellyFraction*Bankroll)

So your “Kelly Fraction” is essentially how we are going to define how “risky” you are as a person. The whole concept is, according to wikipedia, ” the guaranteed amount of money that an individual would view as equally desirable as a risky asset.”

So what it means, is based on your individual kelly fraction (which quantifies your risk, based on how much of a RoR you’d accept), this will tell you if it’s in your better interest to take a risky bet (i.e. a gamble), or a risk free bet (i.e. variance = 0).

Put it simply, for a given win rate, etc. of a game, and a given kelly fraction you play at, it would be better to take a job (we are defining a job as risk free) in which you are paid higher than your CE for the game you play.

So let’s say you have a win rate of $50, and the CE is $30 (given your bankroll, kelly fraction, etc.) If somebody offered you a full time job for $25/hour, don’t take it, because it’s better to spend your time with a semi-risky $50/hour. But if they offered you a full time job for $35/hour, take it.

Firstly, the equation we use is WinRate – Std^(2/(2*KellyFraction*Bankroll))

[ i’ve added parentheses to this, i think it’s equivalent but i want to check — Std = standard deviation, yes? ]

What if I’m in a game where the Kelly Fraction is hard to define, but I know my risk of ruin based on my bets (and win rate and standard deviation)? Is there a formula that can derive the kelly fraction from that information?

i’ve added parentheses to this, i think it’s equivalent but i want to check — Std = standard deviation, yes?

No, adding parentheses makes the units not work out. It is WinRate – Variance / (2 * KellyFraction * Bankroll)

What if I’m in a game where the Kelly Fraction is hard to define, but I know my risk of ruin based on my bets (and win rate and standard deviation)? Is there a formula that can derive the kelly fraction from that information?

I don’t know personally, but here’s a quote from the help file in cvcx which might help you. qfit could answer this better:

“Kelly Factor is an alternate method of specifying risk for those familiar with Kelly theory. A Kelly Factor of 1.0 equates to a risk of 13.5%. A factor of 0.5 means that you will be betting with double the bankroll required for a risk of 13.5%. In a perfect world, this would mean that yours bets would be half as much. But, this is not quite true because of bet simplification and the inability to bet fractions of a dollar. Some professionals play .33, .25 or even lower Kelly factors. These represent substantially less risk; and obviously less income.”

So I’ll try to explain as best as I understand it.

Firstly, the equation we use is WinRate – Std^2/(2*KellyFraction*Bankroll)

So your “Kelly Fraction” is essentially how we are going to define how “risky” you are as a person. The whole concept is, according to wikipedia, ” the guaranteed amount of money that an individual would view as equally desirable as a risky asset.”

So what it means, is based on your individual kelly fraction (which quantifies your risk, based on how much of a RoR you’d accept), this will tell you if it’s in your better interest to take a risky bet (i.e. a gamble), or a risk free bet (i.e. variance = 0).

Put it simply, for a given win rate, etc. of a game, and a given kelly fraction you play at, it would be better to take a job (we are defining a job as risk free) in which you are paid higher than your CE for the game you play.

So let’s say you have a win rate of $50, and the CE is $30 (given your bankroll, kelly fraction, etc.) If somebody offered you a full time job for $25/hour, don’t take it, because it’s better to spend your time with a semi-risky $50/hour. But if they offered you a full time job for $35/hour, take it.

In other words, since Kelly optimizes for log(bankroll), the CE would be

log(bankroll+CE) =

where outcome is a random variable with certain probability and odds, and <...> is the average over this random variable.

Is that correct ?

In other words, since Kelly optimizes for log(bankroll), the CE would be

log(bankroll+CE) =

where outcome is a random variable with certain probability and odds, and <...> is the average over this random variable.

Is that correct ?

Yes, that’s what A3 in Kelly FAQ (http://www.bjmath.com/bjmath/kelly/kellyfaq.htm (<- Archive copy of dead link)) says.

Thanks man. I didn’t know the FAQ yet. But then I would rather name it “utility equivalent certainty” to make the origin more clearly.

I Hate Risk

The probability of not losing 20% of bank with constant resizing kelly fractions:

kelly 20.0%

1/2 kelly 48.8%

1/3 kelly 67.2%

1/4 kelly 79.0%

1/5 kelly 86.6%

1/6 kelly 91.4%

1/8 kelly 96.4%

One can come close to eliminating ror or risk of drawdown at which point CE=WR almost, we can’t eliminate all variance.

happy variance

Confusion over CE

The probability of not losing 20% of bank with constant resizing kelly fractions:

kelly 20.0%

1/2 kelly 48.8%

1/3 kelly 67.2%

1/4 kelly 79.0%

1/5 kelly 86.6%

1/6 kelly 91.4%

1/8 kelly 96.4%

One can come close to eliminating ror or risk of drawdown at which point CE=WR almost, we can’t eliminate all variance.happy variance

If CE nearly equals WR, is that bad? Wouldn’t that suggest that you are severely under-betting your BR?

It is said that the ratio of CE to WR should be 0.5, when betting optimally.

OTOH, if CE nearly equals WR, wouldn’t that mean that the counter should only forgo the opportunity if somebody offers them their EV (or close to it) upfront? This would seem to suggest that CE approaching WR means that the opportunity is quite favorable, thus the counter requires more $$$ to pass-up the opportunity whereas if CE = 0.5 x EV he would require less money to pass up the opportunity.

So to reiterate, is CE approaching EV a good thing or a bad thing? It would seem that one can make a case for either side. Many thanks to anybody that can clarify this point of confusion.

MJ

So to reiterate, is CE approaching EV a good thing or a bad thing? It would seem that one can make a case for either side. Many thanks to anybody that can clarify this point of confusion.

MJ

Depends how you look at it.

Say you are betting a very small Kelly Fraction, such that your RoR is miniscule. Therefore your CE is close to your Win Rate. This means that you are pretty much guaranteed that level of income (CE).

Now, as your Kelly Fraction rises, your Win Rate increases but so does your RoR. And your CE is diminished due to the variance involved and the probability of losing a significant portion of the bankroll.

So the question becomes, how much Certainty do you want in that income stream. Higher CE/WR ratio maximizes the certainty that you will make that money. Maximizing the WR by increasing the Kelly Fraction decreases the CE/WR ratio.

I’ve always heard to maximize the CE as much as possible. You may not want it higher than .75 or .8, otherwise you may only be making peanuts.

wow

Well said paddywhack

I would add:

Most pros & teams probably play from 1/4 to 1/8 Kelly.

With small fractions of Kelly one does not have to resize bets on losses dramatically. Their long run is a lot shorter.

Probably at/beyond 1/8 Kelly one resizes so little that the long run is basically that of a fixed bettor, but with 0% ror.

It’s hard to be conservative with small banks.

Most APs fail due to variance, so eliminate it!

Depends how you look at it.

Say you are betting a very small Kelly Fraction, such that your RoR is miniscule. Therefore your CE is close to your Win Rate. This means that you are pretty much guaranteed that level of income (CE).

Thanks for your response. I do have a couple of questions. Why would using a small K-F (kelly-factor) make CE approach WR?

CE = EV – [Var / (2 * Br * K-F)]

Now, as your Kelly Fraction rises, your Win Rate increases but so does your RoR. And your CE is diminished due to the variance involved and the probability of losing a significant portion of the bankroll.

As you increase K-F, wouldn’t WR and Variance increase in direct proportion to each other, thereby leaving the ratio of CE/WR intact? I’m not trying to be argumentative, just unclear on how you arrive at these conclusions.

So the question becomes, how much Certainty do you want in that income stream. Higher CE/WR ratio maximizes the certainty that you will make that money.

The more certainty the better! So let me get this straight, the higher the ratio of CE/WR the more ‘certain’ I am of winning? I thought that ideally the ratio of CE/WR should be 0.5, thereby ensuring that optimal betting is being utilized.

MJ

optimal is not always as optimal does

Does bank preservation matter?

Kelly 50% chance of losing half

&

10% chance of losing 90%. Will table minimums bite you? Will it be worth it to continue?

With full kelly the long run may be beyond one’s career length.

Off the top of my head less then 1% chance of losing half with 1/4 Kelly

Overbetting Kelly is so damaging that with human limitations one should not get near it.

Why

Ok, maybe I’m just a newb when it comes to counting (only a few years in with little success) or maybe I am not capable of understanding this, but here’s my take… for what it’s worth to you math wizards…

Why? why go this far? You simply have to have the

to play this game. Individual or team, you need a bankroll andbankrollin accordance with said bankroll. You start spreading at a TC of +2 in units.disciplined / structured betsTeam play is a little different, but obviously requires a bigger bankroll than solo play. You are simply getting you’re big money in when you have the advantage and getting out when you don’t.

Is the reason why most AP’s fail is because they overthink what counting is, or is it because they only think like the above?

Ok, maybe I’m just a newb when it comes to counting (only a few years in with little success) or maybe I am not capable of understanding this, but here’s my take… for what it’s worth to you math wizards…

Why? why go this far? You simply have to have the

to play this game. Individual or team, you need a bankroll andbankrollin accordance with said bankroll. You start spreading at a TC of +2 in units.disciplined / structured betsTeam play is a little different, but obviously requires a bigger bankroll than solo play. You are simply getting you’re big money in when you have the advantage and getting out when you don’t.

Is the reason why most AP’s fail is because they overthink what counting is, or is it because they only think like the above?

Most fail because they over bet their bankroll and go bust. Other reasons are they imagine they have skills they don’t and they play crappy rules and bad penetration. Many see all index plays as equal for their counting system. Some indices are based on match ups with such a weak correlation for their count that little gain in EV is realized until well after the index is exceeded but it doubles your risk for a tiny gain in EV(ie you win your bet less often but with a higher reward so they almost balance each other out). Many soft doubles and splits fall in this category. A small gain in EV without a correlation strong enough for it to be much more than a very rough estimate that it is actually the right play. Other soft doubles are very strong plays after the index is exceeded. They have a high correlation to your count. It helps to understand all these types of things for your match ups.

Most fail because they over bet their bankroll and go bust. Other reasons are they imagine they have skills they don’t and they play crappy rules and bad penetration. Many see all index plays as equal for their counting system. Some indices are based on match ups with such a weak correlation for their count that little gain in EV is realized until well after the index is exceeded but it doubles your risk for a tiny gain in EV(ie you win your bet less often but with a higher reward so they almost balance each other out). Many soft doubles and splits fall in this category. A small gain in EV without a correlation strong enough for it to be much more than a very rough estimate that it is actually the right play. Other soft doubles are very strong plays after the index is exceeded. They have a high correlation to your count. It helps to understand all these types of things for your match ups.

So what you’re saying is many fail because they don’t have the discipline. They are incapable of understanding the small edge they have over time. But do things like this topic help these people? I don’t think so, I think it would make these types more confident in the abilities they think they possess, or it would totally discourage them. I don’t see counting cards as that complicated as long as you realize you must follow a simple system. You bet in units with the TC, you don’t gamble and only utilize certain indices. I respect the fact that most AP’s take counting to another level. You are only gaining a small edge over time, and need a bankroll to conquer variance. IMHO

Counting cards is easy. Taking money out of casinos is hard.