Add simplified get_kelly_bet function, remove old #330

evangriffiths · 2024-07-30T20:57:13Z

No description provided.

coderabbitai · 2024-07-30T20:57:22Z

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Walkthrough

The recent changes enhance the betting strategy based on the Kelly Criterion by introducing an enumeration for bet outcomes, improving probability validation, and refining functions for optimal bet size calculations. These modifications increase code readability, robustness, and adaptability to varying market conditions. Additionally, new tests have been implemented to verify functionality under diverse scenarios, ensuring the reliability of the betting logic.

Changes

Files	Change Summary
`prediction_market_agent_tooling/.../kelly_criterion.py`	Introduced `BetDirection` enum for bet outcomes, added `check_is_valid_probability` for validation, defined `get_kelly_bet` and `get_kelly_criterion_bet` for optimal bet calculations. Enhanced clarity and robustness of the betting strategy implementation.
`tests/markets/test_betting_strategies.py`	Added `test_kelly_bet` to validate the `get_kelly_bet` function with multiple scenarios, enhancing test coverage for the Kelly Criterion logic.

Sequence Diagram(s)

sequenceDiagram
    participant User
    participant KellyCriterion
    participant Validator
    participant Outcome

    User->>KellyCriterion: Request bet calculation
    KellyCriterion->>Validator: Check if probabilities are valid
    Validator-->>KellyCriterion: Return validation result
    KellyCriterion->>Outcome: Calculate optimal bet size
    Outcome-->>KellyCriterion: Return bet size
    KellyCriterion-->>User: Provide bet size

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coderabbitai

Actionable comments posted: 2

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Commits

Files that changed from the base of the PR and between 1f4f58c and c6ece3f.

Files selected for processing (2)

prediction_market_agent_tooling/tools/betting_strategies/kelly_criterion.py (3 hunks)
tests/markets/test_betting_strategies.py (2 hunks)

Additional context used

Ruff

prediction_market_agent_tooling/tools/betting_strategies/kelly_criterion.py

179-179: Undefined name kelly_bet

(F821)

tests/markets/test_betting_strategies.py

233-233: Local variable max_bet is assigned to but never used

Remove assignment to unused variable max_bet

(F841)

234-234: Local variable confidence is assigned to but never used

Remove assignment to unused variable confidence

(F841)

Additional comments not posted (9)

prediction_market_agent_tooling/tools/betting_strategies/kelly_criterion.py (4)

17-19: LGTM! Enumeration for bet outcomes is correctly defined.

The BetOutcome class enhances code readability and maintainability by replacing raw string literals with defined values.

22-24: LGTM! Probability validation is correctly implemented.

The check_is_valid_probability function ensures that probability values are within the acceptable range of 0 to 1.

27-64: LGTM! Optimal bet size calculation is well-implemented.

The get_kelly_bet_simplified function correctly calculates the optimal bet size using the Kelly Criterion, with appropriate checks and handling of edge cases.

Line range hint 67-163:
LGTM! Kelly Criterion implementation is well-documented and handles edge cases.

The _get_kelly_criterion_bet function correctly implements the Kelly Criterion for changing market odds, with appropriate mathematical calculations and documentation.

tests/markets/test_betting_strategies.py (5)

Line range hint 65-76:
LGTM! Test for minimum bet to win is well-implemented.

The test_minimum_bet_to_win function correctly validates the minimum bet to win calculation with multiple scenarios.

Line range hint 89-102:
LGTM! Test for minimum bet to win in Manifold market is well-implemented.

The test_minimum_bet_to_win_manifold function correctly validates the minimum bet to win calculation for the Manifold market with multiple scenarios.

Line range hint 114-135:
LGTM! Test for market moving bet is well-implemented.

The test_get_market_moving_bet function correctly validates the market moving bet calculation with multiple scenarios.

Line range hint 147-159:
LGTM! Test for Kelly Criterion bet is well-implemented.

The test_kelly_criterion_bet function correctly validates the Kelly Criterion bet calculation with multiple scenarios.

Line range hint 171-183:
LGTM! Test for stretch bet calculation is well-implemented.

The test_stretch_bet_between function correctly validates the stretch bet calculation with multiple scenarios.

tests/markets/test_betting_strategies.py

coderabbitai

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Commits

Files that changed from the base of the PR and between c6ece3f and d2b3f87.

Files selected for processing (1)

prediction_market_agent_tooling/tools/betting_strategies/kelly_criterion.py (3 hunks)

Additional context used

Ruff

prediction_market_agent_tooling/tools/betting_strategies/kelly_criterion.py

179-179: Undefined name kelly_bet

(F821)

Additional comments not posted (3)

prediction_market_agent_tooling/tools/betting_strategies/kelly_criterion.py (3)

17-20: LGTM!

The BetOutcome enumeration is correctly implemented.

22-24: LGTM!

The check_is_valid_probability function correctly validates probability values.

27-64: LGTM!

The get_kelly_bet_simplified function is well-structured and correctly implements the Kelly Criterion for calculating the optimal bet amount.

prediction_market_agent_tooling/tools/betting_strategies/kelly_criterion.py

gabrielfior · 2024-07-30T21:31:31Z

prediction_market_agent_tooling/tools/betting_strategies/kelly_criterion.py

+    kelly_fraction = edge / odds
+
+    # Ensure bet size is non-negative does not exceed the wallet balance
+    bet_size = max(min(kelly_fraction * max_bet, max_bet), 0)


From my reading of the Wikipedia article, I was under the impression it is possible that bet size is negative, hence we should bet on the opposite direction.
Is that also possible/desirable here?

Yes, that's one option. I figured there are 3 ways of writing this:

user passes in p_yes, market_p_yes. Returns a tuple of [bet_direction, bet amount]

user passes in p_yes, market_p_yes. Returns signed 'yes' bet_amount (i.e. -ve amount means 'no' direction)

user passes in p_yes, market_p_yes, intended bet_direction. Returns bet_amount if > 0, else 0

I went with (3). Do you prefer one of the others (or something else)?

I like (1) better because you can simply pass the resulting bet_direction and bet_amount into whatever function is placing bets. Not a strong opinion on this though - if the ability to "switch" bet outcomes is covered here, then I'm happy.

Fair enough, have changed to (1)

gabrielfior · 2024-07-30T21:33:33Z

tests/markets/test_betting_strategies.py

+    assert (
+        get_kelly_bet_simplified(
+            market_p_yes=omen_market.current_p_yes,
+            estimated_p_yes=est_p_yes,
+            max_bet=10,
+            confidence=1.0,
+            bet_outcome=bet_outcome,
+        )
+        > 0
+    )


I thought the formula presented a closed form, thus the test could simply assert the formula was calculated properly for a few conditions, or is it not the case here?

assert the formula was calculated properly

How would that look like, without duplicating the code for the calculation in the test?

coderabbitai

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Commits

Files that changed from the base of the PR and between d2b3f87 and 02e1818.

Files selected for processing (1)

prediction_market_agent_tooling/tools/betting_strategies/kelly_criterion.py (2 hunks)

Files skipped from review as they are similar to previous changes (1)

prediction_market_agent_tooling/tools/betting_strategies/kelly_criterion.py

coderabbitai

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Commits

Files that changed from the base of the PR and between 02e1818 and 43b52b6.

Files selected for processing (2)

prediction_market_agent_tooling/tools/betting_strategies/kelly_criterion.py (2 hunks)
tests/markets/test_betting_strategies.py (2 hunks)

Files skipped from review as they are similar to previous changes (2)

prediction_market_agent_tooling/tools/betting_strategies/kelly_criterion.py
tests/markets/test_betting_strategies.py

gabrielfior · 2024-07-30T22:18:29Z

prediction_market_agent_tooling/tools/betting_strategies/kelly_criterion.py

@@ -20,6 +80,7 @@ def _get_kelly_criterion_bet(

    Taken from https://github.com/valory-xyz/trader/blob/main/strategies/kelly_criterion/kelly_criterion.py

+    Takes into account how the bet changes the market odds.


Can we remove _get_kelly_criterion_bet? It's not used anywhere and your approach is well integrated with the whole market classes we have in order to determine a bet size.

prediction_market_agent_tooling/tools/betting_strategies/kelly_criterion.py

kongzii · 2024-07-31T07:26:15Z

prediction_market_agent_tooling/tools/betting_strategies/kelly_criterion.py

+    - q = 1-p is the probability of a loss
+    - b is the proportion of the bet gained with a win
+
+    'Simplified' in that it is assumes that the bet does not change the market odds.


Are there any significant differences between using simplified and using the original? (in terms of final bet size)

They're close when the max bet value is <= to market volume, but they diverge after that (tbh I was expecting them to diverge much sooner!)

(#331 to reproduce graph)

…_criterion.py Co-authored-by: Peter Jung <[email protected]>

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Commits

Files that changed from the base of the PR and between 43b52b6 and e2c02d1.

Files selected for processing (1)

prediction_market_agent_tooling/tools/betting_strategies/kelly_criterion.py (2 hunks)

Files skipped from review as they are similar to previous changes (1)

prediction_market_agent_tooling/tools/betting_strategies/kelly_criterion.py

…osis/prediction-market-agent-tooling into evan/add-kelly-bet-simplified

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Files that changed from the base of the PR and between e2c02d1 and c9e70c0.

Files selected for processing (2)

prediction_market_agent_tooling/tools/betting_strategies/kelly_criterion.py (1 hunks)
tests/markets/test_betting_strategies.py (3 hunks)

Files skipped from review as they are similar to previous changes (1)

tests/markets/test_betting_strategies.py

Additional comments not posted (7)

prediction_market_agent_tooling/tools/betting_strategies/kelly_criterion.py (7)

4-6: LGTM!

The BetOutcome class is well-defined and enhances code readability by replacing raw string literals with a defined set of values.

9-11: LGTM!

The check_is_valid_probability function is well-implemented and ensures that probability values are within the acceptable range.

14-20: Well-documented function.

The get_kelly_bet function is well-documented and provides a clear explanation of the Kelly Criterion formula and its parameters.

39-41: Ensure probability values are valid.

The function correctly validates the probability values using the check_is_valid_probability function.

43-48: Clear differentiation of bet outcomes.

The function correctly differentiates between "Yes" and "No" bet outcomes using the BetOutcome enumeration.

50-57: Handle edge cases and calculate Kelly fraction.

The function handles the edge case where market_prob is zero and correctly calculates the Kelly fraction.

59-61: Ensure non-negative bet size.

The function ensures that the bet size is non-negative and does not exceed the maximum bet.

evangriffiths · 2024-07-31T11:25:59Z

How does the bet size change with 'market p_yes'?

import numpy as np
from prediction_market_agent_tooling.tools.betting_strategies.kelly_criterion import (
    BetDirection,
    KellyBet,
    get_kelly_bet,
)

xdai_amounts_simplified = []
market_p_yess = np.linspace(0.01, 0.99, 100)
max_bet = 2
est_p_yes = 0.3
for market_p_yes in market_p_yess:
    kelly_bet: KellyBet = get_kelly_bet(
        market_p_yes=market_p_yes,
        estimated_p_yes=est_p_yes,
        max_bet=max_bet,
        confidence=1,
    )
    kelly_bet_signed = (
        kelly_bet.size if kelly_bet.direction == BetDirection.YES else -kelly_bet.size
    )
    # kelly_bet_signed = kelly_bet.size
    xdai_amounts_simplified.append(kelly_bet_signed)

# Plot the results
from matplotlib import pyplot as plt

plt.plot(
    market_p_yess,
    xdai_amounts_simplified,
)
plt.xlabel("Market p_yes")
plt.ylabel("Bet Amount")
plt.title(f"Kelly Bet ({max_bet=}, est_p_yes={est_p_yes:.3g})")
plt.legend()
plt.show()

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Commits

Files that changed from the base of the PR and between c9e70c0 and 82c9ff7.

Files selected for processing (2)

prediction_market_agent_tooling/tools/betting_strategies/kelly_criterion.py (1 hunks)
tests/markets/test_betting_strategies.py (3 hunks)

Files skipped from review as they are similar to previous changes (1)

tests/markets/test_betting_strategies.py

Additional comments not posted (4)

prediction_market_agent_tooling/tools/betting_strategies/kelly_criterion.py (4)

6-8: LGTM!

The BetDirection enum is correctly implemented, improving code readability and maintainability.

11-13: LGTM!

The KellyBet class is correctly implemented using Pydantic, enhancing data validation and structure.

16-18: LGTM!

The check_is_valid_probability function is correctly implemented, ensuring probability values are within the valid range.

21-67: LGTM!

The get_kelly_bet function is well-documented and correctly implemented, enhancing the betting strategy based on the Kelly Criterion.

evangriffiths · 2024-07-31T11:29:08Z

How does the bet size change with 'estimated p_yes'?

import numpy as np
from prediction_market_agent_tooling.tools.betting_strategies.kelly_criterion import (
    BetDirection,
    KellyBet,
    get_kelly_bet,
)

bet_amounts = []
est_p_yess = np.linspace(0.01, 0.99, 100)
max_bet = 2
market_p_yes = 0.65
for est_p_yes in est_p_yess:
    kelly_bet: KellyBet = get_kelly_bet(
        market_p_yes=market_p_yes,
        estimated_p_yes=est_p_yes,
        max_bet=max_bet,
        confidence=1,
    )
    kelly_bet_signed = (
        kelly_bet.size if kelly_bet.direction == BetDirection.YES else -kelly_bet.size
    )
    bet_amounts.append(kelly_bet_signed)

# Plot the results
from matplotlib import pyplot as plt

plt.plot(est_p_yess, bet_amounts)
plt.xlabel("Estimated p_yes")
plt.ylabel("Bet Amount")
plt.title(f"Kelly Bet ({max_bet=}, {market_p_yes=})")
plt.show()

evangriffiths · 2024-07-31T12:39:43Z

pytest failure unrelated

Add get_kelly_bet_simplified

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Capitalize BetOutcome strings

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Fix mypy

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Update prediction_market_agent_tooling/tools/betting_strategies/kelly…

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…_criterion.py Co-authored-by: Peter Jung <[email protected]>

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evangriffiths added 2 commits July 31, 2024 11:32

Remove old kelly bet function

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Merge branch 'evan/add-kelly-bet-simplified' of https://github.com/gn…

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…osis/prediction-market-agent-tooling into evan/add-kelly-bet-simplified

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Kelly bet returns size and direction

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evangriffiths changed the title ~~Add get_kelly_bet_simplified~~ Add simplified get_kelly_bet function, remove old Jul 31, 2024

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Update package version

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evangriffiths merged commit 5244dbf into main Jul 31, 2024
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evangriffiths deleted the evan/add-kelly-bet-simplified branch July 31, 2024 12:39

This was referenced Sep 9, 2024

383 move rebalancing logic involving previous positions to strategy #387

Merged

Integrate AgentMarket.outcome_token_pool into betting strategies #389

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Some scripts for plotting graphs to help understand how kelly bet behaves #399

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This was referenced Sep 17, 2024

Fix kelly bet if token pool is exactly balanced #408

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Compare agent bet histories with kelly strategy #419

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Allow dynamic bet amounts based on market - remove 'adjust_bet_amount' #430

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Create OmenMarket out of blockchain events #441

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404 add methods to pmat for storing prediction into ipfs and adding that to contract mapping #446

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Add max_price_impact parameter to KellyBettingStrategy #433

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Add simplified get_kelly_bet function, remove old #330

Add simplified get_kelly_bet function, remove old #330

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evangriffiths commented Jul 31, 2024

		@@ -20,6 +80,7 @@ def _get_kelly_criterion_bet(

		Taken from https://github.com/valory-xyz/trader/blob/main/strategies/kelly_criterion/kelly_criterion.py

		Takes into account how the bet changes the market odds.

Add simplified get_kelly_bet function, remove old #330

Add simplified get_kelly_bet function, remove old #330

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How does the bet size change with 'market p_yes'?

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evangriffiths commented Jul 31, 2024

How does the bet size change with 'estimated p_yes'?

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