I am researching a number of topics in the philosophy of finance including the relationship between asset prices and valuation methodologies, and the assumptions of behavioural finance.
Information in Financial Markets
in Scientific Discovery in the Social Sciences pg 87-102
https://www.springer.com/gp/book/9783030237684#
Much of the academic, and professional, discussion of finance assumes that it is clear what information is relevant to pricing securities. This paper argues that this isn’t clear at all, and that different investors often make use of different data. If true, this throws doubt on the idea of an ‘intrinsic price’ of an asset.
Differential Information, Arbitrage and Subjective Value
TOPOI (2019) https://doi.org/10.1007/s11245-019-09661-6
This paper explores the implications of the unclarity about what ‘information’ means in financial markets. It argues that a security can trade at different prices because some investors may not see it as the same security at all. Not all instances of mispricing are genuine cases of mispricing.
Full abstracts are available at https://philpeople.org/profiles/catherine-greene-1
Book Review
Business Ethics Quarterly 30:4 613-616.
DOI: https://doi.org/10.1017/beq.2020.35
A Crisis of Beliefs: Investor psychology and financial fragility by Nicola Gennaioli and Andrey Shleifer. Princeton, NJ: Princeton University Press.
I am researching the applications of my PhD to the philosophy of social science.
2021: Historical counterfactuals, transition periods and the constraints on imagination. The Journal of the International Society for the History of Philosophy of Science (HOPOS)
https://doi.org/10.1086/712937
Counterfactual analysis often receives a bad press in academic history. Considering how the world might have been seems to have more in common with fiction than history. In this paper I argue that, while many criticisms of counterfactual analysis are correct, counterfactual analysis can still play an important role in historical analysis, by showing that the current state of the world was not inevitable.
Nomadic Concepts, Variable Choice, and the Social Sciences
Philosophy of the Social Sciences 2019
https://doi.org/10.1177/0048393119878783
Defining and choosing the right variables is difficult in the social sciences. This paper presents a framework for understanding when variables are more or less useful. It allows us to understand why it is easier to work with concepts like ‘inflation’ than concepts like ‘happiness’.
Full abstracts are available at https://philpeople.org/profiles/catherine-greene-1
AI and the Social Sciences: Why all variables are not created equal
Res Publica 2022
https://doi.org/10.1007/s11158-022-09544-5
This article argues that many of the variables we want to use in algorithms are difficult to quantify. It demonstrates this by analysing survey data used to predict reoffending.
Big Data and the reference class problem: What can we legitimately infer about individuals?
Computer Ethics- Philosophical Inquiry (CEPE) Proceedings 1 (2019). 2019
https://doi.org/10.25884/hc6t-ds11
AI systems are increasingly able to make predictions about individuals. These predictions often rely on generalisations about what similar people tend to do. This paper provides criteria for judging when using such generalisations is ethical.
Mind the Gap: Virtue Ethics and the Financial Crisis
Midwest Studies in Philosophy 42 (1): 174-190. 2018 https://doi.org/10.1111/misp.12089
This paper argues that regulation is not sufficient to encourage ethical behaviour among financial professionals. It argues that a virtue ethics approach is required.
Full abstracts are available at https://philpeople.org/profiles/catherine-greene-1
January 2022: AI and the Social Sciences. Contextual Ethics II. Abo Akademi University. Online
August 2021: What can finance teach us about social ontology? Social Ontology 2021. Online
July 2021: Why all variables aren’t created equal. CEPE/IACAP Joint Conference: The Philosophy and Ethics of Artificial Intelligence. Online
November 2020: Sacrificing accuracy for precision: Why all variables are not created equal. University of Copenhagen workshop on algorithmic fairness, online
December 2019: What does behavioural finance explain? Invited talk at the Erasmus Institute for Philosophy & Economics, Rotterdam
July 2019: Derivative intentions and predictable behaviour: Why the two are incompatible. BSPC Conference, Durham
May 2019: Big data and the reference class problem: What can we legitimately infer about individuals? CEPE 2019- Cybersecurity and Cybersecuritization, Old Dominion University
April 2019: Derivative intentions and predictable behaviour: Why the two are incompatible. The Philosophy of the Social Sciences Roundtable, Burlington Virginia
March 2019: Nomadic concepts: Hacking’s human kinds and social science concepts. Conference on the philosophy of Ian Hacking, Hungarian Academy of Sciences
December 2018: Differential information and arbitrage: Why the law of one price is (sometimes) false. Finance and Society, Edinburgh
Apr 2016: Counterfactuals. LSE Choice Group, London
Oct 2015: Information in financial markets at Philosophy of Finance, Cambridge
July 2015: What’s the value of financial assets? at Understanding Value IV, Sheffield
Jan 2015: Scientific Discovery in Finance at Scientific Discovery in the Social Sciences, London