Irene Aldridge has co-authored research on interpreting artificial intelligence and building trading strategies from data. A draft of the working paper can be found on SSRN. Title: What Data Series Matter? Explaining key trends and factors generated by Artificial Intelligence Abstract: We show a simple way to let the data speak for themselves. Specifically, we show how a large mixed bag of data, potentially embedded with missing data points and collinearities, and therefore unsuitable for traditional econometric analysis, can be useful in building fast and meaningful big data and artificial intelligence analyses and predictions. What’s more, our technique helps the results of the analyses toRead More →

Irene Aldridge will speak on the panel titled “Fintech and the Future of Finance” on Thursday, March 4, 2021, along with Anand Autar of ING and Caroline Tarnok of Coinbase. The panel will be moderated by John Bowden of ING. Here is the link to the event: https://netforum.avectra.com/eweb/DynamicPage.aspx?Site=CMCAS&WebCode=210225FintechPanelRead More →

Not to scare the humans. As many of us know, the state of AI in Finance is still often best explained by this meme: An interesting new study, citing, ahem, moi, however, suggests that machine learning is very capable of beating at least some traders. Specifically, the study applies modern methods to technical analysis, an old workhorse of many chartists, and finds that machine learning is certainly way better than manual labor. Here is the link to the study: https://www.hindawi.com/journals/complexity/2020/8285149/Read More →