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Alternative Data, Big Data, and Applications to Finance

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Fintech with Artificial Intelligence, Big Data, and Blockchain

Part of the book series: Blockchain Technologies ((BT))

Abstract

Financial technology has often been touted as revolutionary for financial services. The promise of financial technology can be ascribed to a handful of key ideas: cloud computing, smart contracts on the blockchain, machine learning/AI, and finally—big and alternative data. This chapter focuses on the last concept, big and alternative data, and unpacks the meaning behind this term as well as its applications. We explore applications to various domains such as quantitative trading, macroeconomic measurement, credit scoring, corporate social responsibility, and more.

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Notes

  1. 1.

    To be more precise, there exists an investment strategy that provides statistically robust “alpha,” relative to a benchmark regression. A typical benchmark is the market returns or the Fama-French three-factor model.

  2. 2.

    \( \frac{{{\text{sales}}_{t} - {\text{sales}}_{{\left\{ {t - 4} \right\}}} }}{\sigma } \) where \( \sigma \) is the standard deviation of the prior annual sales growth \( {\text{sales}}_{t - k} - {\text{sales}}_{t - k - 4} \).

  3. 3.

    There exists a handful of studies in this vein today, but their data are subject to massive back-filling issues. LinkedIn launched in 2007, with most databases gathering this data emerging in 2013. Many of these studies on employee turnover back-fill the history, leading to many issues related to survivorship bias. Further, it is not clear that the time an employee moves is equal to when it is reported on a Web site such as LinkedIn, because employees may do so on a lag or delay.

  4. 4.

    Reuters, July 18, 2018. “UPDATE 1-Ghana’s economy seen up to 40 pct bigger after data overhaul—officials.”

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Acknowledgements

This chapter draws on material from Dr. Alan Kwan’s course, “Big Data in Finance,” taught at the University of Hong Kong, as well as research by both Ben Charoenwong and Alan Kwan. We thank Emmett Kilduff at Eagle Alpha and Vinesh Jha at Extract Alpha for allowing us to re-print statistics from their companies’ respective whitepapers, and Chalinee Charoenwong for assistance.

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Authors and Affiliations

  1. National University of Singapore, 15 Kent Ridge Dr. 7-69, Singapore, 119245, Singapore

    Ben Charoenwong

  2. University of Hong Kong, K.K. Leung Building 923, University Dr., Pokfulam, Hong Kong

    Alan Kwan

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  1. Ben Charoenwong
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  2. Alan Kwan
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Correspondence to Alan Kwan .

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Editors and Affiliations

  1. Ewha Womans University, Seoul, Korea (Republic of)

    Paul Moon Sub Choi

  2. The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong

    Seth H. Huang

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Charoenwong, B., Kwan, A. (2021). Alternative Data, Big Data, and Applications to Finance. In: Choi, P.M.S., Huang, S.H. (eds) Fintech with Artificial Intelligence, Big Data, and Blockchain. Blockchain Technologies. Springer, Singapore. https://doi.org/10.1007/978-981-33-6137-9_2

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  • DOI: https://doi.org/10.1007/978-981-33-6137-9_2

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