Small tweaks to the EV and Market model #36
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| # If we don't bet, we don't have any expected returns. | ||
| if yes_shares == 0 and no_shares == 0: |
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Sometimes it happens the outcomes probs are 0 and 0
| expected_returns_pct = ( | ||
| # Assume that market starts at 50/50 and so the price is 0.5 at the time we are buying it, | ||
| # we can't use {yes,no}_outcome_price atm, because it would just cancel out to EV = 0.0, | ||
| # as it's the same as the probability. |
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Just added the comment because I confused myself in the morning 😄
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That's just confused me too! 😄 Maybe could do with adding a block comment at the start of the function, like:
"""
The expected value if betting on a binary market in its initialized state of 50:50 'yes' and 'no' shares, with the assumption that the correct `p_yes` is that of the market.
"""
Can also take away the # TODO on 319, as:
- the returned expected value is as a %, so the size of
bet_unitsdoesn't matter. - as you say, we can't calculate shares based on market odds if we're also using market odds as the 'correct' odds
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adding a block comment
Added
Can also take away the # TODO on 319, as:
I updated it, bet size actually should make a difference, but it doesn't in our simplified calculation atm. But I would leave the comment there, so we don't forget about it.
| ) -> t.List[Market]: | ||
| if number > 100: |
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It behaves differently if closed is not set, vs. if it's false or true.
So adding it to params only if it's not none, and removing this as it can return more markets than 100.
| @property | ||
| def yes_outcome_price(self) -> float: | ||
| # Use the outcome price if available, otherwise assume it's p_yes. | ||
| return self.outcomePrices[0] if self.outcomePrices else self.p_yes |
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Is this ever not == self.p_yes?
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Polymarket returns outcomePrices, so I thought, why not use it directly? I never seen self.outcomePrices[0] != self.p_yes (as we are doing p_yes=m_json["outcomePrices"][0] in get_polymarket_markets), but I have seen self.outcomePrices[1] != (1 - p_yes), so it does make sense to differ it.
| expected_returns_pct = ( | ||
| # Assume that market starts at 50/50 and so the price is 0.5 at the time we are buying it, | ||
| # we can't use {yes,no}_outcome_price atm, because it would just cancel out to EV = 0.0, | ||
| # as it's the same as the probability. |
There was a problem hiding this comment.
That's just confused me too! 😄 Maybe could do with adding a block comment at the start of the function, like:
"""
The expected value if betting on a binary market in its initialized state of 50:50 'yes' and 'no' shares, with the assumption that the correct `p_yes` is that of the market.
"""
Can also take away the # TODO on 319, as:
- the returned expected value is as a %, so the size of
bet_unitsdoesn't matter. - as you say, we can't calculate shares based on market odds if we're also using market odds as the 'correct' odds
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