Use this URL to cite or link to this record in EThOS:
Title: The foundations of theoretical finance
Author: Theobald, Stuart
ISNI:       0000 0004 6349 5020
Awarding Body: London School of Economics and Political Science (LSE)
Current Institution: London School of Economics and Political Science (University of London)
Date of Award: 2016
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Please try the link below.
Access from Institution:
This thesis provides an account of the ontological, methodological and epistemological foundations of theoretical finance. I argue that these are linked: financial theory is not just a positive enquiry into the nature of the world, but also a means to engineer it. A core feature of its methodology is a modelling approach that conceives of risk as being identical with the volatility of financial market returns. I argue that this can be justified from the perspective of finance as a positive science, because it successfully points to some real features by using idealisations and simplifications. However, I argue that this feature makes theoretical finance inadequate for the task of designing institutions in certain specific ways. I argue that the epistemic demands we make of models in the service of finance theory are different to the demands we should make of models that are used as blueprints for institutions. A failure to appreciate this difference contributed to the financial crisis and our failure to anticipate it. Finance theory has various effects on the financial system so is causally caught up in social ontology, a notion known as “performativity”. I argue that financial theory and its models affect the workings of the financial system in three ways: they provide positive accounts of the financial system that individuals can learn from, they provide normative calculative devices to determine optimal decisions, and finally they provides blueprints for the design of financial institutions. We have in the past assumed that models that succeed in supporting financial theories because of their coherence and validation by data will also be successful blueprints. However, good tests of blueprints should be inductive and assess for unexpected properties, quite unlike how we test theory models. It follows that we have insufficient reason to assume good theory models are good blueprints.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
Keywords: HG Finance