The Kelly criterion: How to size bets (2019)
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Kelly Criterion – how to calculate optimal bet sizes - https://news.ycombinator.com/item?id=27431627 - June 2021 (129 comments)
Kelly Criterion - https://news.ycombinator.com/item?id=26834333 - April 2021 (194 comments)
Log Optimal Betting – An interactive demo of the Kelly criterion - https://news.ycombinator.com/item?id=23894425 - July 2020 (1 comment)
Kelly Criterion - https://news.ycombinator.com/item?id=21559782 - Nov 2019 (1 comment)
Kelly Criterion (2007) - https://news.ycombinator.com/item?id=18484631 - Nov 2018 (96 comments - great top subthread!)
Kelly Criterion in detail - https://news.ycombinator.com/item?id=13143821 - Dec 2016 (8 comments)
Kelly Criterion in detail - https://news.ycombinator.com/item?id=9401821 - April 2015 (1 comment)
Kelly Criterion For Sport Betting - https://news.ycombinator.com/item?id=2504222 - May 2011 (23 comments)
Ed Thorp: It is realistic to multiply your capital by 1000 using Kelly Criterion - https://news.ycombinator.com/item?id=1119318 - Feb 2010 (1 comment)
I rremembered what Kelly Criterion was, that it was an ideal betting method, but could not remember the formula. Now I might remember both the next time it comes up. And maybe use it in my life!
Ie should I play the lottery?
1/45m - (1-1/45m)/1M
0.00000002 - 0.000001
-0.00000098
so, no.
You need liability insurance (until you’re ridiculously wealthy perhaps), but fire/structure coverage and collision coverage are much more optional if the home/car value is low enough relative to your net worth.
I forget who, but one person I respect a lot in risk management said that "the only surprising thing about insurance is that people don't get more of it."
But of course, it's not always a net gain. And even a rule of thumb like "for expensive things insure, otherwise don't" has problems. That rule would have lead me to get unemployment insurance, but doing the numbers I realised it would be a net loss, even considering the Kelly criterion.
You have to make the computations each time to bet rationally.
That's a weird formulation. To me, the most surprising thing is that people insure... wrong things. I mean, there are exactly two reasons to take insurance:
1. The economical effects of the event you insure against are beyond your comfort zone.
2. You are for some reason confident that the insurance company has miscalculated your risk profile.
Now, I ignore the second one. The question is, why people take travel insurances that cover lost sunglasses? I mean, to me, it would be obvious that the equilibrium is that people choose so high deductibles that they just can afford/are comfortable with, which means cheaper insurances for two reasons: Insurance company pays out less money and needs to do less work per paid out dollar. But high deductible insurances are almost non-existent.
I think the answer could be a quite mundane appeal to 'bundling'. i.e. I get very comprehensive travel insurance when travelling to the US due to the punitive cost of healthcare (your (1)). This comphrensive insurance can often cover unrelated and unneeded items, but it's hard to slice and dice the coverage exactly.
Essentially, we make all these tiny little bets every day, and while it's possible to hedge them[1], it's complicated compared to just straight-up money-based insurance.
[1]: I can for example reserve a table at a fancy restaurant halfway to the important meeting, so if I get stuck on my way and miss the meeting I can at least get a nice meal out of it, at the cost of the table reservation.
It is not always, and in fact there are common cases where it has significant positive expected outcomes.
Let's assume that you have sufficient wealth (say $40MM) that you can pay for a massive medical bill out of pocket. Let's furthermore say that you know, due to a hereditary illness in your family, that you have 90% chance you will be on the hook for a very large (say $1MM) bill when you're in the age range 20-30.
An american health insurance company legally cannot charge you more just because of preexisting conditions or family history, so health insurance will be a winning proposition for you.
Similarly, if you have information that the insurance company does not have, then you can "win" at other forms of insurance. If you have an ex-boyfriend who is prone to stealing bikes or setting homes on fire, then insurance covering those will have a higher expected value to you, and the insurance company is unlikely to account for that increased risk.
If you happen to know you're a bad driver, but have never been in an accident (only close calls), you might look normal on paper, and thus get a rate that has positive expected returns for you.
Said another way, insurance is not always a losing proposition. It can be a winning proposition if the insurance company doesn't understand the risks correctly or if laws prevent the company from accounting for certain risks.
[0] https://www.reuters.com/business/life-insurers-adapt-pandemi...
As an insurer, you're essentially a deposit-only bank with some special cases that allow you to withdraw (make a claim). You have a large amount of money that you can now invest and make actually meaningful profits. What you trade for that is the assurance that should someone require a large sum of money for a loss, you will pay for it.
I don't really now where people get the idea that insurance companies are just sitting on the stacks of cash they pull in from premiums. You have a minimum reserve you have to keep to assure you have enough to cover claims, just like a bank doesn't have your cash on hand all the time. (You all should watch It's a Wonderful Life sometime.) The long run expected gain from a "properly priced" insurance product is net zero (in reality its usually a loss). They make money off your money, not directly off selling insurance.
The insurance company isn't paying you out of the coffers of their wealthy owners. They're paying you out of the coffers from you and all your fellow insurance buyers' premiums. The primary transfering of money is from the little guy--- to the little guy. Any massive profits come from skimming a tiny bit of that at a very large scale. And competition pretty much dictates that that won't be predatory.
When I say 'inherently predatory', I don't mean that every insurance company is doing the equivalent of loan sharking, I mean that the concept of mandatory participation in a system that then also makes its own determination of how much wealth is reasonable to take from you in exchange for its service seems fundamentally immoral.
You know, when I write it like that, this applies to life in basically any situation --
* fully-capitalist (have to work, a market you have no control over determines your value)
* fully-communist (have to work, a government you have no control over determines your value)
* completely anarchist (have to work, the conditions of the world around you determine how much work you need to do to stay alive)
So I think what I'm actually saying might just be 'life isn't fair' which is kinda banal.
The service is obviously not worthless--some entity has to assess risk, coordinate, and administrate--but it is predicated on terms that make it (I would assert) immoral to transfer more than is necessary from those that participate in the service to those that own the service.
Every time you don't take insurance you're betting all your wealth on there being no ruin- level disaster.
In other words, when you are choosing between "a loss" and "no loss", then the correct Kelly bet is of course "no loss".
However, when you are choosing between "a loss" and "a different loss", which is the case when it comes to insurance, then you need to whip out your slide rule and do the numbers.
This is an example I used with another group of people in another context:
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Let's say you get the opportunity to try to hover a helicopter close to ground, for whatever reason. There's a real pilot next to you who will take control when you screw up (because hovering a helicopter is hard!)
However, there's a small (2 %) chance you will screw up so bad the other pilot won't be able to recover control and you crash the helicopter. You will be fine, but you will have to pay $10 k to repair the helicopter, if that happens.
You can get insurance before you go, which will cover $6 k of helicopter damage (so even with insurance, you have to pay $4 k in addition to the insurance premium if you crash), but cost you $150 up front.
Do you pay a $150 premium to reduce an unlikely (2 %) loss of $10 k down to a still sizeable $4 k?
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If we do the arithmetic expectations, we'll find that with insurance, the expectation is negative $200 if you don't go for the insurance, and negative $230 with the insurance. So always skip the insurance, right?
Not so fast. That is correct if we had effectively infinite money in the bank. If we have an infinite amount of money in the bank, we can repeat that "no insurance" bet over and over and get the arithmetic expectation.
In practise, we don't always have an effectively infinite amount of money compared to the losses in question, so we need to consider how the growth of what we have is affected by the losses.
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The answer then, according to the Kelly criterion, is "it depends". Specifically, it depends on how much money you have in the bank.
If you have more than $35 k in the bank, then the $10 k loss is small enough to not affect the growth of your money significantly. If you have less than that, the $10 k loss is sizeable enough that it's worth spending $150 to reduce it down to $4 k.
Going the other way around, if you have $20 k in your bank, you should be willing to spend as much as $186 on the insurance, to protect against the risk of halving your available money.
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In terms of how the calculation is done: I find it easiest to do it the way Bernoulli did it back in the 1700's when he invented the mathematical formulation of the Kelly criterion: use the geometric expecation. (This is equivalent to the arithmetic expectation of the log.)
Here's the equation set up to compute what wealth is needed to decline the insurance in the helicopter example: https://www.wolframalpha.com/input?i=solve+w%5Ep+*+%28w+-+L%...
(Hopefully the symbols are obvious, but in case they are not:
- w = current wealth
- L = loss with no insurance
- p = probability of no adverse event
- q = 1 - p = probability of adverse event
- c = premium of insurance
- d = deductible of insurance)
In other words, if you have $10 k in savings, and then skip the insurance and go down to $1 k, you might end up retiring with $10 k. Whereas if you do take the insurance and your savings stay at roughly $10 k, you can retire with $100 k – given the exact same day job, etc.
Your savings compound. That's the only requirement of the Kelly criterion, regardless of everything else.
The use case of the Kelly criterion is to determine the optimal size of your capital to put at risk, where the profit you're expecting to make is linearly related to that size.
In your example you have savings which will bring in some percentage no matter what. And you have the choice of taking an insurance or not. Taking the insurance would cut your profit, but most likely not in the linear way that the Kelly criterion assumes when it calculates the optimal bet size.
Insurance makes wealth grow faster Ole Peters, Alexander Adamou https://arxiv.org/abs/1507.04655
https://www.amazon.com/Kelly-Capital-Growth-Investment-Crite...
This is only partially tongue-in-cheek, since the only way to reduce variance is to bet lower amounts, but this will also reduce your expected return, all the way to zero at 0$ bets.
The downside of this is that Kelly's utility function has some very nice properties. In particular the total utility of a sequence of bets will turn into a sum which means you can ignore dependencies between events. Note for instance that the argument in this article still holds even if you've got very strong dependencies between coin flips, it could repeat the pattern HTHTH forever and the Kelly criterion would still give the same optimal proportion, though obviously there are better strategies if you don't restrict yourself to blindly betting on heads.
This is a "fractional Kelly" strategy, which optimises growth under the condition that you want to reduce variance.
Also, in the real world, you never accurately know how big your % edge actually is, so there's a real chance that you are over-betting when using Kelly stakes. Using reduced stakes is a way to compensate for this.
Runway of 500k, a 5% chance, 100:1 odds, so don't bet more than ~$22k on each bet/pivot.
plog(x+y) + (1-p)log(x-y).
Setting the derivative with respect to y equal to 0 yields p/(x+y) - (1-p)/(x-y) = 0.
This rearranges to give y = (2p - 1)x,
which is precisely the Kelly criterion. p log(x+y) + (1-p) log(x-y) = log(x) + C
where C is the Shannon capacity of the binary symmetric channel with cross-over probability p.By the same argument, the expected wealth after T rounds will be
log(x) + T C
So, in addition to the optimal strategy, we have also derived the rate of growth of wealth. This is also in tune with the motivation of Kelly's paper where he was showing a relationship between Shannon capacity and optimal gambling (without using a dynamic programming argument)Use the "link to this scenario" button if you want to compete with friends on the same seed.
In particular, in that Haghani and Dewey study they mention, the optimal strategy actually involved playing a lot safer that the Kelly bet. (Although the participants weren't told about the cap at the start of the game, so they would be reasonable to take more risk. Incidentally, it strikes me as slightly unethical to mislead the participants in a way that makes it more likely that they'll risk losing more money.)
In other words, it's prescriptive, not descriptive. The Kelly criterion says that if you want to maximise growth, you should adopt log utility. If you don't have log utility, you won't maximise growth.
(Though, as you point out, maximising growth isn't the only goal possible -- limiting drawdown is another useful goal. The linear combination of "no bet" and "full Kelly" is an optimal frontier that maximises growth given a particular limit to drawdown.)
I looked this up and you're right: the Kelly maximizes the expected geometric growth rate. However, the question to ask is: why do I want that? The obvious thing to want to maximize is not the expected geometric growth rate, but the expected amount of money (which it seems Kelly does NOT maximize).
The rationale to choose to maximize expected geometric growth rate is that it is equivalent to maximizing expected logarithmic utility, which is something that you actually want.
The reason why you want to do that is because, given unbounded amount of betting, the bankroll of someone following the Kelly strategy will, with probability 1, eventually permanently exceed that of any other strategy.
As far as it relates to my comment and comment: I think you're advancing a third answer to the "why" question, not showing why "maximizing expected geometric growth" is a better "why" than "maximizing (logarithmic) utility".
With that said, I still think the "maximizing (logarithmic) utility" answer is the only good motivation. My reasoning is that most people (myself included) define rationality to be: maximizing expected utility. From this, we can derive the Kelly criterion.
As for me, I often waffle between thinking this Kelly property I stated is important versus expected utility of some sort.
I feel we had this conversation in the past and it feels to me you're a bit stuck in thinking about it the backwards way.
Unless there is a cost to placing a bet, why take any risk at all?
The way they compare strategies (i.e. which is more likely to "be ahead" after N rounds) is more interesting, but it feels like they flipped the script on me :)
With this idea we can assign a dollar value to every possible bankroll. Those values should satisfy.
V(250) = 250
V(x) = max(x, max over 0<y<=x pV(x+y) + (1-p)V(x-y) - a)
I can't immediately see how to solve it though.Maybe that works if the probability of success is high enough and the initial epsilon is small enough. If that is not the case, it starts to sound like a martingale type strategy.
I guess on the down side that is A LOT of clicking. It is similar to how when playing a better team in basketball, you want to slow down the pace of the game to limit possessions.
There are other assumptions in there, like that there's no minimum bet and you can divide your bet to arbitrary precision. Always check your assumptions! I'm sure someone has modified the Kelly criterion for minimum bets and quantized bets, but a cursory search didn't turn it up immediately.
While it's often modelled as such we know it's not perfect (utility of money is bounded or even goes downwards after certain point while log is unbounded) and more importantly utility of money is different for different people.
That means that, while being an important illustration of the concept of utility of money, Kelly is most likely not a good practical guideline for most people. Many professional gamblers for example feel that something closer to 1/2 Kelly or 1/4 Kelly is better but again it all depends on your personal situation and what money means to you.
It makes no assumptions about utility functions.
There are several good reasons to use fractional Kelly strategies, but shapes of utility functions has nothing to do with it.
Shapes of utility function have everything to do with determining your bet sizes. Can you provide one reason to use Kelly that is not connected to the shape of the utility function?
Not to escalate but calling a very well known fact about Kelly a misconception doesn't make for a good start. I mean it's math you can verify or open Wikipedia and read the very first paragraph there.
It got mentioned in one chapter in a book that happened to be a collection of interviews of traders, out of about 30 books on trading that I had read.
Bet sizing can be used for money management and risk control for professional traders.
How did I do that?
I use to win money playing poker to pay for college books at beg of Semester using the same math strategy as it always has to be between I/15th and 1/20 if you have 60% odds
https://i.imgur.com/QUbOopz.jpg
Essentially using the Martingale system.
Of course, given a longer opportunity to invest, Kelly wins every time by growing exponentially: https://i.xkqr.org/kelly-vs-martingale-100.png
(I always went with 60% no matter what, in both extreme cases I never lost)
:)
The Kelly criterion is different and has a positive expected profit.
Why would the payoff be unlikely if you have a big edge?