Using Bots to Automate Profit Targets and Stop Losses

You know the routine: you’ve opened a new position and it's time to enter your profit target and stop-loss orders. It is a repetitive, time consuming process that involves calculating return percentages and manually entering orders through your broker. Now there’s a better way.

Bots efficiently automate your trade exits using pre-defined profit targets and stop losses.

Automating profit targets and stop losses is a key feature of the autotrading platform and very straightforward when using the decision recipe that evaluates whether a position’s premium has increased or decreased by a certain percentage.

In this video example, the bot trades a weekly put credit spread that enters a new position every Wednesday (automating trade entries for specific dates is easy with bot event automations). We want to exit the trade when the position’s premium has decreased by 50% (a 50% profit) or increased by 200% (a loss 2x the original premium received).

With broker platforms, you can enter an order to exit a trade, but that must be done manually for every position. With automation, you can create one template as a framework and reuse the same criteria repeatedly throughout the same bot or multiple bots in your portfolio. 

Using the Option Alpha platform, you can create a monitor automation with the defined profit and loss targets built-in so you don’t have to go through the order entry process. Plus, the automation can be saved to your library and reused for any bot in the portfolio to manage put credit spread positions.

The loop positions action is a useful tool for monitor automations because it manages all positions of a certain type. Because this bot enters short put spreads, for example, the repeater action can be set to only reference short put spreads as it evaluates the automation criteria.

With a repeater action in place, the decision recipes tell the bot what to monitor. This bot example manages positions by looking for opportunities to exit based on return relative to the initial premium, so a decision recipe that evaluates if the position’s premium has increased or decreased is used. Any percentage can be set as a target or stop. 

You can also group, or “nest,” decision recipes using an and/or function, which forces the bot to evaluate multiple position properties before moving through the automation. In this example, the bot checks to see if the premium has decreased by 50% OR increased by 200% from the trade’s entry price.

A closing action is added to the automation to exit the trade if the answer is “Yes.” If neither criterion is met, the automation will simply end, and the whole process is run again at the next interval.

Now that the monitor automation is complete, it is saved to your library so it can easily be reused in other bots. You can also create a copy and edit the automation. For example, another bot could use this automation with a slight modification, such as exiting at a 25% profit.

This is one of many examples of how automating the order entry process can save you time and stress when managing positions. A single automation can be created and replicated to monitor your portfolio for profit targets and stop losses.