try something

auto_trading/indicators/lastVariation.py

@@ -0,0 +1,30 @@
+"""Dumb indicator, for testing purposes."""
+import pandas as pd  # type: ignore
+
+from ..interfaces import Indicator
+
+
+class LastVariation(Indicator):
+    """If last value is greater than current value return 1 otherwise -1."""
+
+    def __init__(self, value: pd.Series):
+        """Save the value."""
+        super().__init__()
+        self.value = value
+
+    def __call__(self, data: pd.DataFrame) -> pd.Series:
+        """Return a dataframe of valuation of each stock from the input data.
+
+        Args:
+            data (DataFrame): Time-Stock valuated candlestick data.
+                For each time and each stock give (high, low, open, close).
+
+        Returns:
+            DataFrame: Stock valuated float.
+                For each stock give -1 if realy bad and +1 if realy good.
+        """
+        if self.value[-1]["close"] >= self.value[-2]["close"]:
+            return 1
+        else:
+            return -1
+        # return self.value

auto_trading/strat/buyhighselllow.py

@@ -0,0 +1,47 @@
+from typing import List
+
+import pandas as pd  # type: ignore
+
+from ..orders import Long
+from ..interfaces import Strategy, Order, PTFState
+from ..indicators.lastVariation import LastVariation
+
+class BuyHighSellLow(Strategy):
+    """Just hold some stock."""
+
+    def __init__(self, to_hold: str):
+        """Init the class"""
+        super().__init__()
+        self.to_hold = to_hold
+
+    def execute(
+        self, data: pd.DataFrame, indicators_results: pd.DataFrame, state: PTFState
+    ) -> List[Order]:
+        """Just hold the value [to_hold].
+
+        Args:
+            data (DataFrame): The Data broker output.
+                For each time and each stock give (high, low, open, close).
+
+            indicators_results (DataFrame): Indicator-Stock valuated float.
+                For each indicator and each stock give -1 if realy bad and +1 if realy good.
+
+        Returns:
+            List[Order]: A list of orders to execute.
+        """
+        orders = []
+        # if I have some money
+        if (balance := state.balance) > 0:
+            # I calculate the value of the stock
+            market_price = data.loc[data.index[-1][0]].close.to_dict().get(self.to_hold)
+            if market_price is None:
+                # retry later
+                return []
+
+            amount = balance / market_price
+            # and I buy it all at market price
+            if LastVariation(self.to_hold):
+                orders.append(Long(stock=self.to_hold, amount=amount, price=market_price))
+            else:
+                orders.append(Short(stock=self.to_hold, amount=amount, price=market_price))
+        return orders  # type: ignore

main.py

@@ -2,6 +2,7 @@ import pandas as pd  # type: ignore
 
 from auto_trading.broker.backtest import Backtest
 from auto_trading.strat.hold import Hold
+from auto_trading.strat.buyhighselllow import BuyHighSellLow
 from auto_trading.ptf.in_memory import InMemoryPortfolio
 from auto_trading.bot import Bot
 
@@ -14,7 +15,7 @@ if __name__ == "__main__":
     ptf = InMemoryPortfolio(
         base_balance=100, change_rate_getter=lambda: bt.current_change
     )
-    strategy = Hold("GOOGL")
+    strategy = BuyHighSellLow("WLTW")
 
     bot = Bot(ptf, strategy, bt)