feat(streaming): add live trading orchestrator pipeline #63
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| self._sync_position_manager() | ||
| if qty > 0: | ||
| if self.position_manager is not None: | ||
| self.position_manager.open_position(symbol, qty, price) |
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When a position manager is configured, _handle_signal copies the portfolio’s post-trade cash into the PositionManager and then immediately calls position_manager.open_position(...). PositionManager.open_position/close_position adjust cash themselves, so this ordering subtracts the notional a second time on buys and adds it twice on sells. The position manager’s portfolio_value and risk guard will therefore drift from the actual portfolio on every trade, leading to incorrect risk halts or position sizing in live trading whenever a position manager config is supplied.
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| symbol = message.get("symbol") | ||
| if not symbol: | ||
| continue | ||
| self._update_history(message) | ||
| price = float( |
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The consumer loop assumes incoming messages already expose standard keys (symbol, price/close) and immediately skips anything missing them. StreamingGateway currently forwards provider payloads untouched (the adapters don’t rewrite Alpaca/IB fields and MessageProcessor is a pass‑through), so real provider messages that use keys like S/p will be dropped and no history, features, or trades will ever be produced. The live trading pipeline will therefore sit idle when connected to the shipped adapters unless the messages are normalized before they hit this code.
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| history = self._history.get(symbol) | ||
| history = pd.concat([history, row]) if history is not None else row | ||
| self._history[symbol] = history.tail(self.history_window) |
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Incoming streaming bars are appended to _history without reordering, so any late or replayed messages are treated as the newest rows before tail(self.history_window) trims the buffer. When providers replay buffered ticks after reconnects (or deliver out-of-order messages), an older bar can displace the true latest tick and the feature generator will run on stale prices, producing incorrect signals and trades. Sorting or de-duping by timestamp before trimming would avoid using misordered data.
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…-implementation Harden live trading price handling and risk updates
AKKI0511
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analyze-quanttradeai-for-new-feature-implementation
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Summary
Testing
Codex Task