We have written about how hedge funds are trying to contain costs by trading more efficiently. We are also seeing cost containment and efficiencies through the use of AI. Similar to consulting, AI can make analysts more efficient at some of their core tasks through summarizing and sifting through data in reports. The use of AI through EDGAR filing is not new, but has become a core part of the work by both discretionary and quantitative researchers.
AI is being used as:
- information summary tool
- focused search tool
- quick news analysis tool
- pre-screening tool along with quant analysis
- simple idea generator
- proprietary prompt tool
While not a research replacement, AI is not a research adjunct that allows hedge funds to run leaner shops with less costs on junior analyst development. The objective is to make senior analysts more efficient by reducing drudgery. Many firms have spent money on proprietary prompt libraries that can be applied to stock sets to serve as an alternative filtering mechanism. This can be especially powerful when linked with proprietary databases.
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