Andrew Todd

Andrew Todd


Personal profile

Personal Statement

Developing and evaluating new and emerging artificial intelligence (AI) methods to extract useful information from unstructured financial text datasets. In particular, I am applying B.E.R.T to Earnings Call Transcripts to unearth sentiment within the calls and evalaute any relationships said sentiment has with financial market movements. To add an extra element to my thesis I have also been researching multimodal sentiment analysis techniques - particularly the combination of text + audio. If successful, I will be combining PRAAT and B.E.R.T to extensively analyse the characteristics produced in earnings calls.


Drawing earnings call data from FinnHub (, I will be attempting to add to the literature the first classified dataset of its kind. If successful, this dataset could be used by a plethora of academics to continue bringing the area of research forward.

Education/Academic qualification

Master of Science, Financial Technology, Strathclyde Business School

1 Sept 201928 Aug 2020

Award Date: 28 Aug 2020

Bachelor of Mathematics and Statistics, Mathematics, Statistics and Finance, University Of Strathclyde

1 Sept 201520 Jun 2019

Award Date: 20 Jun 2019

Doctor of Science, Classification of Unstructured Financial Text in Earnings Call Transcripts, Strathclyde Business School

External positions


1 Apr 2021 → …


1 Jun 20191 Aug 2019

Gallagher, Gallagher

1 Jun 20181 Aug 2018


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