The intuition of fair odds (information theory)
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I'm reading about gambling in Elements of Information theory. As stated in the book, given that the gambler bets $o_i$-for-$1$ on horse $i$,
Fair odds (w.r.t some distribution): the odds is fair if $sum_i frac{1}{o_i} = 1$
Superfair odds: the odds is superfair if $sum_i frac{1}{o_i} < 1$
Subfair odds: the odds is subfair if $sum_i frac{1}{o_i} > 1$
Can anyone give me some intuition about these concepts (i.e. fair odds, superfaid odds and subfair odds) ?
probability statistics information-theory gambling
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I'm reading about gambling in Elements of Information theory. As stated in the book, given that the gambler bets $o_i$-for-$1$ on horse $i$,
Fair odds (w.r.t some distribution): the odds is fair if $sum_i frac{1}{o_i} = 1$
Superfair odds: the odds is superfair if $sum_i frac{1}{o_i} < 1$
Subfair odds: the odds is subfair if $sum_i frac{1}{o_i} > 1$
Can anyone give me some intuition about these concepts (i.e. fair odds, superfaid odds and subfair odds) ?
probability statistics information-theory gambling
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
I'm reading about gambling in Elements of Information theory. As stated in the book, given that the gambler bets $o_i$-for-$1$ on horse $i$,
Fair odds (w.r.t some distribution): the odds is fair if $sum_i frac{1}{o_i} = 1$
Superfair odds: the odds is superfair if $sum_i frac{1}{o_i} < 1$
Subfair odds: the odds is subfair if $sum_i frac{1}{o_i} > 1$
Can anyone give me some intuition about these concepts (i.e. fair odds, superfaid odds and subfair odds) ?
probability statistics information-theory gambling
I'm reading about gambling in Elements of Information theory. As stated in the book, given that the gambler bets $o_i$-for-$1$ on horse $i$,
Fair odds (w.r.t some distribution): the odds is fair if $sum_i frac{1}{o_i} = 1$
Superfair odds: the odds is superfair if $sum_i frac{1}{o_i} < 1$
Subfair odds: the odds is subfair if $sum_i frac{1}{o_i} > 1$
Can anyone give me some intuition about these concepts (i.e. fair odds, superfaid odds and subfair odds) ?
probability statistics information-theory gambling
probability statistics information-theory gambling
asked Nov 15 at 3:52
HOANG GIANG
53
53
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1 Answer
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From the point of the view of the house (who takes the bets) : let's assume $b_i$ is the amount bet on horse $i$, and let $B=sum_i b_i$ be the total bet. How should we pay, so that we (the house) don't lose or win? If $i$ is the winner, we should give the total $B$ to the gamblers who bet to it, so they will get $B$-for-$b_i$, or $o_i=B/b_i$ for $1$.
So, in this (fair) case, we'd have $sum 1/o_i = 1$.
Now, typically the house will want to profit a small share of the total bet, then the winners will get a total of $alpha B$ with $alpha lessapprox 1$ (conversely, if $alpha > 1$ then the house would lose something in each game... not a very usual scenario).
Hence, in general $o_i = alpha B/b_i$ and $sum 1/o_i = frac{1}{alpha}$ or
$$alpha = frac{1}{sum 1/o_i}$$
This says that ${sum 1/o_i} > 1 implies alpha < 1$ , which is the usual, subfair scenario (for the gamblers).
For example, in some bet site today, the odds for the ATP match Federer-Anderson are $o_1 = 1+4/11$ , $o_2 = 1+11/5$. So $alpha = frac{1}{sum 1/o_i}=0.9562$, so the house profits nearly $4.4%$ of the bet (subfair).
(BTW: Though the textbook is about Information Theory, this question actually has little to do with it)
add a comment |
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
1
down vote
accepted
From the point of the view of the house (who takes the bets) : let's assume $b_i$ is the amount bet on horse $i$, and let $B=sum_i b_i$ be the total bet. How should we pay, so that we (the house) don't lose or win? If $i$ is the winner, we should give the total $B$ to the gamblers who bet to it, so they will get $B$-for-$b_i$, or $o_i=B/b_i$ for $1$.
So, in this (fair) case, we'd have $sum 1/o_i = 1$.
Now, typically the house will want to profit a small share of the total bet, then the winners will get a total of $alpha B$ with $alpha lessapprox 1$ (conversely, if $alpha > 1$ then the house would lose something in each game... not a very usual scenario).
Hence, in general $o_i = alpha B/b_i$ and $sum 1/o_i = frac{1}{alpha}$ or
$$alpha = frac{1}{sum 1/o_i}$$
This says that ${sum 1/o_i} > 1 implies alpha < 1$ , which is the usual, subfair scenario (for the gamblers).
For example, in some bet site today, the odds for the ATP match Federer-Anderson are $o_1 = 1+4/11$ , $o_2 = 1+11/5$. So $alpha = frac{1}{sum 1/o_i}=0.9562$, so the house profits nearly $4.4%$ of the bet (subfair).
(BTW: Though the textbook is about Information Theory, this question actually has little to do with it)
add a comment |
up vote
1
down vote
accepted
From the point of the view of the house (who takes the bets) : let's assume $b_i$ is the amount bet on horse $i$, and let $B=sum_i b_i$ be the total bet. How should we pay, so that we (the house) don't lose or win? If $i$ is the winner, we should give the total $B$ to the gamblers who bet to it, so they will get $B$-for-$b_i$, or $o_i=B/b_i$ for $1$.
So, in this (fair) case, we'd have $sum 1/o_i = 1$.
Now, typically the house will want to profit a small share of the total bet, then the winners will get a total of $alpha B$ with $alpha lessapprox 1$ (conversely, if $alpha > 1$ then the house would lose something in each game... not a very usual scenario).
Hence, in general $o_i = alpha B/b_i$ and $sum 1/o_i = frac{1}{alpha}$ or
$$alpha = frac{1}{sum 1/o_i}$$
This says that ${sum 1/o_i} > 1 implies alpha < 1$ , which is the usual, subfair scenario (for the gamblers).
For example, in some bet site today, the odds for the ATP match Federer-Anderson are $o_1 = 1+4/11$ , $o_2 = 1+11/5$. So $alpha = frac{1}{sum 1/o_i}=0.9562$, so the house profits nearly $4.4%$ of the bet (subfair).
(BTW: Though the textbook is about Information Theory, this question actually has little to do with it)
add a comment |
up vote
1
down vote
accepted
up vote
1
down vote
accepted
From the point of the view of the house (who takes the bets) : let's assume $b_i$ is the amount bet on horse $i$, and let $B=sum_i b_i$ be the total bet. How should we pay, so that we (the house) don't lose or win? If $i$ is the winner, we should give the total $B$ to the gamblers who bet to it, so they will get $B$-for-$b_i$, or $o_i=B/b_i$ for $1$.
So, in this (fair) case, we'd have $sum 1/o_i = 1$.
Now, typically the house will want to profit a small share of the total bet, then the winners will get a total of $alpha B$ with $alpha lessapprox 1$ (conversely, if $alpha > 1$ then the house would lose something in each game... not a very usual scenario).
Hence, in general $o_i = alpha B/b_i$ and $sum 1/o_i = frac{1}{alpha}$ or
$$alpha = frac{1}{sum 1/o_i}$$
This says that ${sum 1/o_i} > 1 implies alpha < 1$ , which is the usual, subfair scenario (for the gamblers).
For example, in some bet site today, the odds for the ATP match Federer-Anderson are $o_1 = 1+4/11$ , $o_2 = 1+11/5$. So $alpha = frac{1}{sum 1/o_i}=0.9562$, so the house profits nearly $4.4%$ of the bet (subfair).
(BTW: Though the textbook is about Information Theory, this question actually has little to do with it)
From the point of the view of the house (who takes the bets) : let's assume $b_i$ is the amount bet on horse $i$, and let $B=sum_i b_i$ be the total bet. How should we pay, so that we (the house) don't lose or win? If $i$ is the winner, we should give the total $B$ to the gamblers who bet to it, so they will get $B$-for-$b_i$, or $o_i=B/b_i$ for $1$.
So, in this (fair) case, we'd have $sum 1/o_i = 1$.
Now, typically the house will want to profit a small share of the total bet, then the winners will get a total of $alpha B$ with $alpha lessapprox 1$ (conversely, if $alpha > 1$ then the house would lose something in each game... not a very usual scenario).
Hence, in general $o_i = alpha B/b_i$ and $sum 1/o_i = frac{1}{alpha}$ or
$$alpha = frac{1}{sum 1/o_i}$$
This says that ${sum 1/o_i} > 1 implies alpha < 1$ , which is the usual, subfair scenario (for the gamblers).
For example, in some bet site today, the odds for the ATP match Federer-Anderson are $o_1 = 1+4/11$ , $o_2 = 1+11/5$. So $alpha = frac{1}{sum 1/o_i}=0.9562$, so the house profits nearly $4.4%$ of the bet (subfair).
(BTW: Though the textbook is about Information Theory, this question actually has little to do with it)
edited Nov 15 at 19:40
answered Nov 15 at 19:32
leonbloy
39.6k645105
39.6k645105
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