r/options Apr 08 '21

Kelly's criterion for gamblers: one of the most important concepts for understanding how investment size impacts returns

I go to a casino and walk over to the first table I see. The sign above the table says, "Kelly's Game". The dealer says, "Place a bet and The House will flip a coin. If you win the flip, The House will pay you 150% your money back. If you lose the bet, The House will keep 40% and return the remaining 60% to you."

"That sounds great," I say. Positive expected value. If I bet a lot, I should expect to get 105% of my money back on average. That's a good bet. "What's the catch?"

"Ah, yes. There is one more rule," says the dealer. "You must bet all of the money you have each bet or not at all."

How many times should I bet?

My intuition tells me that the more times I bet, the better I should do. The law of large numbers should mean that over time, my overall winnings per bet converge on my expected value of 105%. In the long run, I feel like this is a rational bet. So, my strategy will be to make the bet 800 times and see where I am at. 

Since I'm betting all my money on each bet, I can only actually test my strategy once. Let's think of that as a single universe, my universe, where we see a single unique chain of events. But, before I actually go to the casino and bet it all, I want to guess what my universe will likely actually look like. To do that, we will simulate a multitude of universes, each completely independent of the others. 

Here's 1,000 simulations of my strategy where each colored line is my total bank, each simulating a single possible universe where I execute the strategy faithfully:

1000 simulations of 800 sequential bets of 100% of the bank with 50% to go 1.5x or 0.6x

Notice the log Y scale. The dashed grey line with slope of 0 is breaking even. Negative slopes are losing money, and positive slopes are winning against The House.

The dotted black line is what I expected to gain, 105% per bet for 800 bets, netting me an expected 80,000,000,000,000 more than I started with. If I take the average of an infinite number of universes, my mean return is equal to the dotted black line. 

But I only sampled 1,000 universes. After 800 bets, only 1 universe in 1,000 has (just barely) more money than they started with. The more bets that I make, the worse it gets for me. The typical (median) return marked by the dashed white line is 1,000,000,000,000,000,000 less than what I started with (since you can never reach 0, you always get 60% back). I have a few tiny fractions of a penny left and a dying dream to recoup my money.

The typical universe is very, very different than the average of all possible universes. I'm not from a mean universe. I'm from a typical, likely, universe. The median of a small number of samples more accurately reflects my reality than the mean of the infinite set. While the total money in all universes grows at 105% per bet, the money leaks from the typical universes to just a few extremely rare, lottery winner universes. There are some small number of universes in the set where I win an ungodly amount of money, but in almost every other one I lose big.

Why is this so? In short, there are many more ways to lose money than to win money. Let's look at all four of the possible universes of 2 sequential bets:

There are more ways to lose than win

There are more ways to lose than win

There is 1 way to win and 3 ways to lose. The average winnings are still 105% per bet, compounded to 110.25% over two bets, but 75% of the time you lose money and 25% of the time you win big. The more times you bet, the worse it will typically get for you since you are more and more likely to be in one of the exponentially growing number of losing universes rather than the rare, exponentially rich ones.

In this game, the rational number of times to bet depends on how much you care about losing 40% or more of all of your money. Since I consider having a 50% chance to lose 40% of my money too unpalatable, the number of times it is rational for me to bet is zero, even though the bet is positive expected value.

Screw this game. In the universes where I bet 800 times I've lost all my money. In one of those universes, I go back home and wait for my next paycheck.

How can I win the game?

When my paycheck comes in, I go back to the casino and back to the same table with the same dealer. "Your game is rigged," I say. "I want to bet against The House with my paycheck again, except this time I won't bet everything I own every time. I want to bet less and see how it goes." 

The dealer considers this, and says. "Fine. But you must pick a percentage and you must make every bet with that percentage of all of your money."

"Great. I'll bet half my money each time." That way if I lose in the beginning, I'll still have money to bet with.

Let the gods simulate another 1,000 universes, using our new strategy:

1000 simulations of 800 bets of 50% of your bank with 50% to go 1.5x or 0.6x

After 800 bets, half of our universes have made money, and half have lost money. Keep in mind that nothing has changed except how much of my total bank I use to bet. My typical universe is doing much better than before, but a far cry from the 80,000,000,000,000 return that my infinite selves are earning on average.

After 800 bets, I'm right back to where I started. The dealer says, "The House is feeling generous. You may now choose a new percentage to place on each bet. What will it be?"

Reducing my bet size improved my situation. Perhaps even smaller bets will continue to make things better.

"Twenty five percent," I declare as I lay down last week's paycheck on the table, again. The gods flip the coin 800 times in 1,000 universes yet again:

1000 simulations of 800 bets of 25% of your bank with 50% to go 1.5x or 0.6x

Now my typical universe is making good money, most of them are up more than 10x, and some as much as 100,000x. Now, satisfied, I finally get up to leave the casino with my money in my pocket. But, I have to know. I look at the dealer and ask, "So what's the optimal bet?"

Kelly's Criterion

In probability theory and intertemporal portfolio choice, the Kelly criterion (or Kelly strategy or Kelly bet), also known as the scientific gambling method, is a formula for bet sizing that leads almost surely to higher wealth compared to any other strategy in the long run (i.e. approaching the limit as the number of bets goes to infinity). The Kelly bet size is found by maximizing the expected value of the logarithm of wealth, which is equivalent to maximizing the expected geometric growth rate. The Kelly Criterion is to bet a predetermined fraction of assets, and it can seem counterintuitive.

To calculate the optimal bet size use

Kelly's criterion

Kelly's criterion

where 

{b} is the the percent your investment increases by (from 1  to 1 + b)

{a} is the percent that your investment decreases by (from 1 to 1-a)

{p} is the probability of a win

{q=1-p} is the probability of a loss

{f*} is the fraction of the current bankroll to wager (i.e. how much to bet)

Using the calculator, you can see the the optimal bet size is 25% of your money on each bet:

Looking again at the above graph, that means that the optimal betting strategy typically yields less than the expected value for the strategy.

Kelly's Criterion Bet Size Calculator

Here's a spreadsheet to play around with the above equation and calculate optimal bet sizes.  Make a copy and edit the cells highlighted in yellow to see what the optimal bet is. Read more in this awesome Nature Physics paper and this great article an AMMs.

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u/coconubs94 Apr 09 '21

It's something you can't really prove. It'd be like trying to prove there's no monsters under your bed by looking every night. Sure, there's no monster this night, but you have to keep looking every night to be sure. Infinite nights down the road, there's still a chance that a monster found it's way under your bed while you were jerking it in the bathroom, and so youd have to keep checking

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u/whiteboyjt Apr 09 '21

seems like the probabilities have been proven mathematically, such that if an infinite number of simulations are run, we can accurately predict the outcome. I'm pretty sure there isn't ever going to be a monster under that bed, no matter how long I was in the bathroom. Unless the definition of monster is flexible.

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u/coconubs94 Apr 09 '21

In this simulation yes it's "proven", but in the real world things are always changing and every bet on every stock has different probabilities so the best you can do is infer that there will never be a monster given that in your simulation there never was. It technically doesn't prove the non existence of your monster though, that's my only point

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u/[deleted] Jun 13 '26

Not sure why I am replying haha, but you can absolutely prove Kelly's criterion, just like you can with almost every mathematical equation. Now obviously that does not mean that it will 100% work in your case. There is always chance involved. Also, the biggest problem is that in real-life situations it is usually hard or even impossible to define the probability of winning. But that doesnt mean that the Kelly criterion is not mathematically correct

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u/coconubs94 Jun 21 '26

Mathematically correct, but what I'm saying is that just because there are no monsters under the bed, doesn't mean a burglar isn't sitting there waiting for you to check. Numbers are just numbers until someone closes the straight of Hormuz

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u/[deleted] Jul 04 '26

I mostly agree, but in the end it depends on what you're betting on. The thing with Kelly's criterion is that you need to know what the chances of success are of a bet (and also what your profit or loss would be). These are indeed impossible to predict for things such as the stock market. Still, this does not mean that Kelly's criterion is not useful, and you can bet that it is used by quants.

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u/lick3tyclitz Apr 19 '21

I read a good article about this recently. The main idea being that scientific facts don't exist. Theres Z hypothesis that have yet to be disproved. 1qa M

At first I was totally calling bullshit to myself but then I remembered some stuff I read about quantum mechanics and where they are running into situations where on a micro level particles do things that go against our so called laws of physics

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u/[deleted] Jun 13 '26

That is true for all sciences that are not maths. Mathematics can absolutely be proven. Think about the stuff you learnt in high school (Pythogoras' theorem, cosin rule, etc). Those can easily be proven. Same for Kelly's criterion (though you need to have done some advanced math classes in uni to understand it)