QuantChat: Finance of the Future

Strategy Studio

Describe your trading strategy and I'll generate deployable Python code

main.py

··32 lines

1from nautilus_trader.trading.strategy import Strategy
2
3
4class GeneratedStrategy(Strategy):
5    def on_start(self) -> None:
6        self.universe = ['BUILD', 'MEAN', 'SPY', 'THAT']
7        self.log.info("Preparing QuantChat draft strategy")
8        # Brief received:
9        # Build a mean-reversion SPY strategy that buys oversold hourly pullbacks and
10        # scales out into strength.
11        self.log.info("Adding RSI confirmation to the signal stack")
12
13    def on_bar(self, bar) -> None:
14        signal = self._mean_reversion_signal(bar)
15        size = self._position_size(bar)
16        if signal == "enter" and size > 0:
17            self._enter_position(bar, size)
18        elif signal == "exit":
19            self.close_all_positions()
20
21    def _mean_reversion_signal(self, bar) -> str:
22        # TODO: combine RSI state with price confirmation.
23        return "hold"
24
25    def _position_size(self, bar) -> float:
26        # TODO: size positions using the risk budget from the brief.
27        # TODO: add stop-loss and portfolio guardrails.
28        return 0.0
29
30    def _enter_position(self, bar, size: float) -> None:
31        # TODO: submit the order once signals and sizing are finalized.
32        return None

Strategy Studio

Describe your trading strategy and I'll generate deployable Python code

1from nautilus_trader.trading.strategy import Strategy 2 3 4class GeneratedStrategy(Strategy): 5 def on_start(self) -> None: 6 self.universe = ['BUILD', 'MEAN', 'SPY', 'THAT'] 7 self.log.info("Preparing QuantChat draft strategy") 8 # Brief received: 9 # Build a mean-reversion SPY strategy that buys oversold hourly pullbacks and 10 # scales out into strength. 11 self.log.info("Adding RSI confirmation to the signal stack") 12 13 def on_bar(self, bar) -> None: 14 signal = self._mean_reversion_signal(bar) 15 size = self._position_size(bar) 16 if signal == "enter" and size > 0: 17 self._enter_position(bar, size) 18 elif signal == "exit": 19 self.close_all_positions() 20 21 def _mean_reversion_signal(self, bar) -> str: 22 # TODO: combine RSI state with price confirmation. 23 return "hold" 24 25 def _position_size(self, bar) -> float: 26 # TODO: size positions using the risk budget from the brief. 27 # TODO: add stop-loss and portfolio guardrails. 28 return 0.0 29 30 def _enter_position(self, bar, size: float) -> None: 31 # TODO: submit the order once signals and sizing are finalized. 32 return None