Scanner automations allow you to filter for your trading plan’s specific criteria. You can automate the entire process to ensure the bot only enters trades that meet your requirements.
Opportunity recipes evaluate potential trading opportunities. Bots reference market data to determine if an order should be sent to your broker based on your predefined parameters. An order is sent only if your specific criteria are met.
You can add a loop symbol action to the beginning of a scanner to filter through multiple symbols, and the bot will apply the automations decisions to every ticker.
For example, you can use a decision recipe to evaluate opportunity probabilities such as the probability of profit, the probability of max loss, or the probability of an option being in-the-money.
Bots are also intelligent enough to automatically reference an open position action to evaluate opportunities for the exact position type you want to enter.
You can always test the automation’s logic in real-time with live market data to see if the bot will open a position based on the automation’s decisions and current market conditions.
You can make informed decisions using automation and offload tedious processes onto a bot. Easily combine multiple probability analysis decisions with grouped decisions so you can be confident your strategy’s pre-entry checklist is complete before opening a new position.
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In this video, I want to show you how to combine multiple probability analysis decisions inside of your automations.
Now, probability analysis is something that a lot of traders use to filter for potential trades. They look for a high probability trades that needs certain criteria and thresholds for their systems. But did you know that you could automate all of this inside of your bots on Option Alpha? You can use multiple probability analysis decisions to make sure that you're only submitting trades that meet your strict criteria.
So in this video, we're going to show you how to do that here inside of our demo scanner automation.
First, we're going to be looping through in this automation a number of different symbols. Notice that we're going to be looping through and looking for positions in SPY, FXI, GLD, and EFA. Next, we have an open position action. This open position action is set up to specifically enter a short put spread position in any of the symbols that we're currently looping through. And we're going to be entering a short put spread closest to 30 days with a 30 delta short strike, a ten delta long strike, and only one contract.
Again, this is just an example of how you can set it up, and you can modify and edit any of these fields for your particular strategy. Now, what we're going to do is we're going to go ahead and precede this open position action with a set of decisions. Decisions that check probability matrix for our potential trade that we might enter.
We're going to go down to our list of opportunities. Now, opportunity-based recipes are exactly what they sound like. They're recipes that help your bot evaluate potential trading opportunities. And because you don't have an existing position like position recipes at the bottom, you are still looking for market criteria and data that would help you evaluate whether or not to submit the order to your broker.
In this case, we're going to be using multiple probability analysis decisions that helps ensure that the bot only submit an order to our broker if our specific criteria are met. We're going to actually use this recipe down here, and we're going to modify some of the fields inside of this recipe formula.
First thing that we have to do is we have to select our potential trading opportunity. Now because bots are smart and recognize the already built out an open position action to open a short put spread, you can reevaluate that same potential position just using the recent evaluation here for that opportunity.
That means that the bot will still continuously pull in the information for that potential trade that you're about to enter to now start to run some analysis and create some data points so you can use for your potential decision. Once we're good to go with that opportunity, we just simply go to the next field.
The first one that we're going to build out is the chance of profit. We've built out some of these in other videos, but we're going to combine a bunch of them here inside of this video. We want to first check and see if the chance of profit on our potential trade that we're about to submit to our broker is more than 70%. So we'll go here, and we'll change this to chance of profit being more than 70%. Once we're good to go here, we simply hit save.
That adds the first decision to our decision action. But in this case, instead of saving it to our automation editor, we're going to group this with another decision. We're going to use the exact same recipe; just use some more modified fields.
And again, the bots are smart enough and intelligent enough to recognize you probably want to analyze the exact same opportunity that you just looked at, just with a different combination. So it pulls up that recipe opportunity already for you, and now you can change some of the fields or variables. In this example, what we're going to do this time, is we're going to check and see if the chance of max loss is below some threshold that we want.
Now, we're going to change this to max loss vs. the chance of profit because we want to make sure that the possibility or the probability of a max loss scenario with our potential trade is lower than our maximum threshold we're willing to accept. So, in this case, we're going to say that we want to check and make sure that the chance of max loss is less than 20%.
So if the probability of max loss is greater than 20%, we do not want the bot to continue forward, and we want the bot to go down the no path and not entering order or send the order to our broker. Once we're good to go here, we simply can save and then add this to our list of decisions.
So at this point, we've now created a group set of decisions. We want the bot to follow the yes path if both of these decisions are true. And we use the and statement here to make sure that the bot does that. Notice you can always flip this statement from and, or or, but in our case it's a more logical scenario to use the and statement in this example.
We want to make sure that the chance of profit is more than 70%, and the chance of max loss is less than 20%. Both of those statements have to be true in order for us to allow the bot to continue down the yes path and open a new position. Once we're good to go with our group of decisions, we can simply hit save and add this to proceed the yes path.
Now, when the automation runs, it's going to loop through our ticker symbols that we've put into our symbol loop. SPY, FXI, GLD, and EFA. For each of those symbols, it's going to pull the information for potential short put spread trading opportunity. And check and see if the chance of profit is more than 70%, and the chance of max loss is less than 20%.
We can actually test this logic by just simply running a test inside of our bot right now. Notice when I ran the test, the first symbol that it looped through is SPY. And you'll notice that it encountered a no response. We can dig into the details here and see where it failed. And noticed it failed at the very first decision.
We told the bot that it had to make sure it encountered both of those decisions, and they both had to be true. So if the bot fails at the first decision, it doesn't even bother making the next decision because it already failed the logic test in here that you told it to check, and it sent it down the no path.
In this case, the short put spread probability of profit is 69.88%. So it's pretty close, but it actually wasn't exactly where we need it to be. So for SPY to simply continue down the no path and end it. Let's check the next ticker.
In this case, for FXI, you'll notice that it did actually result in a yes answer. So, we can dig into the details here for this potential decision. Notice in the test that the probability of profit was 70.33% for the short put spread, which was above our threshold, so that was a yes answer and continue to the next decision. And the probability of max loss is less than 20%.
In this case, the probability of max loss factoring in all of the break events and the deltas and the strikes of the potential trade ended up being 10.73%. So that was less than our 20% threshold, so if we were to turn this bot on, we should expect that immediately when the automation starts running that it would enter a position in FXI. And you can see here that it simulates what that position would be.
We can check this for the other ones like GLD. And you can see, GLD also evaluated yes for both statements. The probability of profit is more than 70%. The probability of max loss was significantly less than 20%, and so what if continued down the yes path.
For EFA, however, which is our last ticker symbol, you can see that it failed. And in this case, it again failed at the first decision. It failed here because the chance of profit was less than our threshold that we set. So bots would not continue down the yes path and would not submit an order to your broker.
So this is how cool it is to use automations inside of your bots on Option Alpha. You can combine multiple probability analysis decisions right here into your automations. And you can use these decisions to make more informed and smarter choices about the trades that you enter and offload all of the tedious and time-consuming processes that you do now manually.
You can offload all of that to the bots and let them make perfect decisions without forgetting to make these decisions every single time automations run.