Getting Started

Installation

You can install keeks using pip:

pip install keeks

Basic Usage

Here’s a simple example of how to use keeks to simulate a betting strategy:

from keeks.bankroll import BankRoll
from keeks.binary_strategies.kelly import KellyCriterion
from keeks.simulators.repeated_binary import RepeatedBinarySimulator

# Create a bankroll with initial funds
bankroll = BankRoll(initial_funds=1000.0, max_draw_down=0.3)

# Create a Kelly Criterion strategy
# Parameters: payoff, loss, transaction_cost
strategy = KellyCriterion(payoff=1.0, loss=1.0, transaction_cost=0.01)

# Create a simulator with a fixed probability
# Parameters: payoff, loss, transaction_costs, probability, trials
simulator = RepeatedBinarySimulator(
    payoff=1.0,
    loss=1.0,
    transaction_costs=0.01,
    probability=0.55,  # 55% chance of winning
    trials=1000
)

# Run the simulation
simulator.evaluate_strategy(strategy, bankroll)

# Plot the results
bankroll.plot_history()

Using Different Strategies

Keeks provides several betting strategies:

1. Kelly Criterion: Optimal bet sizing based on probability and odds

   from keeks.binary_strategies import KellyCriterion
   strategy = KellyCriterion(payoff=1.0, loss=1.0, transaction_cost=0.01)
   

2. Fractional Kelly: A more conservative version of Kelly

   from keeks.binary_strategies import FractionalKellyCriterion
   strategy = FractionalKellyCriterion(payoff=1.0, loss=1.0, transaction_cost=0.01, fraction=0.5)
   

3. Drawdown-Adjusted Kelly: Kelly variant that accounts for drawdown tolerance

   from keeks.binary_strategies import DrawdownAdjustedKelly
   strategy = DrawdownAdjustedKelly(payoff=1.0, loss=1.0, transaction_cost=0.01, max_acceptable_drawdown=0.2)
   

4. OptimalF: Ralph Vince’s method for maximizing geometric growth rate

   from keeks.binary_strategies.simple import OptimalF
   strategy = OptimalF(payoff=1.0, loss=1.0, transaction_cost=0.01, win_rate=0.55)
   

5. Fixed Fraction: Simple strategy that bets a constant percentage

   from keeks.binary_strategies import FixedFractionStrategy
   strategy = FixedFractionStrategy(fraction=0.05, min_probability=0.5)
   

6. CPPI: Constant Proportion Portfolio Insurance for capital preservation

   from keeks.binary_strategies import CPPIStrategy
   strategy = CPPIStrategy(floor_fraction=0.5, multiplier=2.0, initial_bankroll=1000.0)
   
   # Remember to update the CPPI strategy with the current bankroll value
   # before each evaluation
   strategy.update_bankroll(current_bankroll)
   

7. Dynamic Bankroll Management: Adaptive allocation based on recent performance

   from keeks.binary_strategies import DynamicBankrollManagement
   strategy = DynamicBankrollManagement(base_fraction=0.1, payoff=1.0, loss=1.0)
   
   # After each bet, update the strategy with the result
   strategy.record_result(won=True, return_pct=0.05, current_bankroll=1050.0)
   

8. Naive Strategy: Simple strategy that bets full amount when expected value is positive

   from keeks.binary_strategies import NaiveStrategy
   strategy = NaiveStrategy(payoff=1.0, loss=1.0, transaction_cost=0.01)
   

Using Different Simulators

Keeks provides several simulators:

1. RepeatedBinarySimulator: Simulates repeated bets with a fixed probability

2. RandomBinarySimulator: Simulates bets with random probabilities

3. RandomUncertainBinarySimulator: Adds uncertainty to the actual outcome probabilities