BaseStrategy
class backtide.strategies.base.BaseStrategy()[source]
Abstract base class for all strategies.
Subclass it to create a custom strategy.
Example
from backtide.strategies import BaseStrategy
class MyStrategy(BaseStrategy):
def __init__(self, threshold=0.02):
self.threshold = threshold
def evaluate(self, data, portfolio, state, indicators):
orders = []
# Your logic here ...
return orders
Methods
| evaluate | Evaluate the strategy and return orders. |
| log | Write a message to the experiment log. |
method backtide.strategies.baseevaluate(data, portfolio, state, indicators)[source]
Evaluate the strategy and return orders.
| Parameters |
data : dict[str, np.array | pd.DataFrame | pl.DataFrame]
Keys are the experiment's symbols and values are the historical
OHLCV data available up to the current bar.
portfolio : Portfolio
Current portfolio holdings (cash, positions and open orders).
state : State
Current simulation state.
indicators : dict[str, dict[str, np.array | pd.DataFrame | pl.DataFrame]] | None
The first keys are the indicator names. The second keys are the
experiment's symbols. The values are the pre-computed indicator
values.
None if no indicators were selected.
|
| Returns |
list[Order]
Orders to place this tick.
|
method backtide.strategies.baselog(message, level="info")[source]
Write a message to the experiment log.
Messages appear in the live log viewer while the experiment
runs and are persisted to the experiment's logs.txt file.
Example
def evaluate(self, data, portfolio, state, indicators):
self.log(f"Bar {state.bar_index}: evaluating...")
...
| Parameters |
The message to log.
level : str | LogLevel, default="info"
Tracing log level. Choose from: "error", "warn", "info", "debug".
|