October 27th, 2021

Using APIs to Assist in Implementing Artificial Intelligence to your Stock Picking Process

Written By: Davison Westmoreland

APIs – it stands for application programming interface(s) – can sound very complicated, but they are merely a way to take complex data and put it into a format that matches your existing process. Using APIs can help investment managers implement artificial intelligence in a way that works for them. If using AI and machine learning sounds advanced, let alone APIs, we will demonstrate some ways that all investment managers – fundamental and quantitative – can benefit from these tools. 

We’ll walk through a few simple examples.

Fundamental manager use case

A fundamental asset manager has found success using artificial intelligence to create asset management models within their stock universe. They trade their portfolio weekly and every Sunday, they like to look over the trade recommendations they created within our investment management platform – Boosted Insights. However, they prefer to look at the information in Excel, and the dense signals Excel download file that they can create within Boosted Insights doesn’t quite fit their needs. The manager has no programming experience so they reach out to our customer success team to see how it can be done. Our customer success experts walk the person through downloading Python and using some of the many API “functions” (small segments of code that tell the computer what to do). Within minutes, the fundamental manager has transformed the AI recommendations they created within Boosted Insights into something that they can use in their stock picking and trading process. They are using AI and ML on their terms. 

Quantitative manager use case

A quantitative investment manager sees the value in our finance specific machine learning (especially the data cleaning and normalizations) and wants to use Boosted Insights to create models with very specific alternative data that they purchased. Though our data upload functionality within the platform is very intuitive, the quant wants to use the same CSV file they currently use with their process and have an API call update their data within Boosted Insights. Having some programming expertise, they already know their way around Python but referencing our list of API functions [IS THERE ANY REASON TO NOT LINK THIS], they see that there is already an API that works for their needs. They can update their data both internally and within our platform in one go, thereby saving them time and effort. This allows the quant user to advance their use of AI and ML but in a way that is convenient to them. 

Quantamental manager use case

A quantamental asset manager wants to examine the outputs of their model in great detail. Our easy-to-use interface surfaces much of the same information, but the user feels that they would prefer to see the signals in an Excel format. We do offer Excel downloads with precise information on each stock recommendation our machine learning algorithms make, but this user has a very specific use case that would be helped with an API function. It doesn’t currently exist in our library of calls, but they reach out to their dedicated customer success team to see if they can help. Our team of developers is always able to help and they create a specialized API function specific to this user’s needs. The asset manager gets exactly the information they need from our AI and ML in a format they find simpler. 

Takeaways

API use is often an enterprise only function with many cloud-based platforms. We know that to see success with artificial intelligence, making it straightforward (while remaining technically advanced and cutting edge in a data science capacity) can help asset managers. Here at Boosted.ai, every user can make use of APIs to help them implement (or continue to use) AI, in a way that is organic to their process. For more information on APIs and how they can help you use AI and ML in a way that works for you, reach out to us here

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