https://grafioschtrader.github.io/gt-user-manual/en/algoalert/historicalrun/index.htmlWork in Progress - Target version V0.38.0 The implementation of alerts and rule-based trading is not yet complete. This documentation describes the planned and partially implemented functionality. A historical replay evaluates the strategies of a simulation environment on every trading day after its opening date and books the resulting orders as ordinary transactions inside the simulation. This shows how your allocation and your strategies would have behaved in the past, without touching your real portfolio.HugoenSat, 19 Sep 2026 22:54:47 +0100https://grafioschtrader.github.io/gt-user-manual/en/algoalert/historicalrun/environment/index.htmlSat, 19 Sep 2026 10:00:00 +0100https://grafioschtrader.github.io/gt-user-manual/en/algoalert/historicalrun/environment/index.htmlWork in Progress - Target version V0.38.0 The implementation of alerts and rule-based trading is not yet complete. This documentation describes the planned and partially implemented functionality. A simulation environment is a separated copy of your portfolios and accounts as of a day in the past. It is a tenant of its own: whatever you book, change or delete inside it stays inside it and never touches your real portfolio. How an environment comes about is described under Rule based trading.https://grafioschtrader.github.io/gt-user-manual/en/algoalert/historicalrun/standingorders/index.htmlSat, 19 Sep 2026 22:54:47 +0100https://grafioschtrader.github.io/gt-user-manual/en/algoalert/historicalrun/standingorders/index.htmlWork in Progress - Target version V0.38.0 The implementation of alerts and rule-based trading is not yet complete. This documentation describes the planned and partially implemented functionality. Cash standing orders are compatible with Historical Replay. For example, this lets a replay model a savings plan in which new money regularly enters the simulation environment. Security standing orders are not supported in a simulation; purchases and sales there result from the replay’s strategies and rebalancing.