‘It has been a pleasure to see the relationship between SigTech and Boston University mature and develop since our initial collaboration in early 2020. We at SigTech passionately believe that the continued evolution of quantitative finance depends upon the next generation of financial engineers. We have been delighted to work with this cohort of bright and intellectually curious young people, and look forward to following their careers with interest.’ - Andrew Liddle, Chief Operating Officer at SigTech
From this year’s cohort, two students distinguished themselves with their elegant and insightful approach; applying quantitative techniques to textual sources of data and deriving innovative equity strategies.
Yihao Yao developed his strategy by extracting information from financial news sources - via a word-to-vector model - and assigning a sentiment score based on the presence of a select set of words. This provided Yihao with a textual knowledge base which was cross-referenced against quantitative data available on the SigTech platform. The result was a strategy that predicted movements in equity markets.
Jiasheng Pan also focused on discerning market sentiment from textual sources. Identifying Twitter as an opinion aggregator, Jiasheng used APIs, semi-structured learning, and dictionary matching to scrape tweets and garner sentiment. This allowed for the construction of a strategy capable of predicting movements in equities.
Whilst both recognised the difficulty of working with unstructured data, they found the SigTech platform to be intuitive and comprehensive. Yihao remarked that the ability to interrogate unstructured data sets would become increasingly important to maintaining an edge in the investment world and that the functionality of the SigTech platform deftly facilitated such an ambition. After university Yihao and Jiasheng hope to pursue careers in either quantitative analysis or data science.
‘Working with these bright individuals was an incredibly rewarding experience; I had as much to learn from them as they did from me. The future of the SigTech platform is determined by its users and to see it applied in projects that involve machine learning and wrangling unstructured data successfully is very exciting!' - Katya Lait, Data Engineer at SigTech
SigTech looks forward to continuing to work with the next generation of quants, both in academia and the wider world of quantitative finance. To find out more about our collaboration with tertiary institutions, please visit our Academia page.
This document is not, and should not be construed as financial advice or an invitation to purchase financial products. It is provided for information purposes only and is subject to the terms and conditions of our disclaimer which can be accessed at: https://www.sigtech.com/legal/general-disclaimer