Mathematics and Finance: Some Philosophical Remarks

Ippoliti, Emiliano

doi:10.1007/s11245-020-09706-1

Cited by 5 publications

(3 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Finansjalizacja oznacza przekształcanie coraz większej liczby procesów i zjawisk społeczno-gospodarczych w transakcje finansowe. Jest to zjawisko bardzo złożone i dynamiczne, a jego modelowanie tradycyjnymi metodami matematycznymi i statystycznymi może być bardzo trudne (Ippoliti, 2021). Jednak dzięki zastosowaniu metod uczenia maszynowego, możliwe jest dokładniejsze zrozumienie i przewidywanie tego zjawiska, co pozwala na lepsze podejmowanie decyzji biznesowych i inwestycyjnych (Dara, 2022).…”

Section: Wprowadzenieunclassified

Application of machine learning for financialization modeling

Korytnicka

2023

HSSR

View full text Add to dashboard Cite

Research objective: The objective of this article is to present the application of machine learning techniques in modeling the phenomenon of financialization and analyze their effectiveness in predicting and understanding this phenomenon. Methodology: The methodology is based on data collection and processing from various sources. Subsequently, machine learning techniques such as regression, classification, decision trees, and neural networks were applied to train predictive models and analyze the phenomenon of financialization. Main conclusions: Data analysis using machine learning techniques allowed for the identification of key factors and patterns related to financialization. It has been demonstrated that machine learning models can effectively predict financialization trends and provide insight into the mechanisms and factors influencing this phenomenon. Application of the study: The study has significant implications for various fields, such as economics, finance, and economic policy. The application of machine learning techniques in modeling financialization can aid in making better investment decisions, assessing risk, monitoring financial stability, and developing more effective regulatory strategies. Originality/Novelty of the study: This article contributes an original perspective to the scientific literature by focusing on the application of machine learning techniques in the context of financialization. The work presents a new insight into this phenomenon and provides evidence of the effectiveness of machine learning-based models in analyzing and forecasting financialization.

show abstract

Section: Wprowadzenieunclassified

Application of machine learning for financialization modeling

Korytnicka

2023

HSSR

View full text Add to dashboard Cite

show abstract

“…Nowadays, the financialization of the word, the controversial process that makes finance an organizing principle of modern societies (Epstein, 2005), has intertwined finance with every aspects of the life of people, institutions and societies, up to a point that the financial system raises many issues that are prominently philosophical in kind, that is, ethical, epistemological, methodological (see De Bruin et al, 2020;Ippoliti, 2020a for an overview).…”

Section: Philosophy For Financementioning

confidence: 99%

“…Of course, this approach is a legitimate and economic way of building a mathematical finance (see also Ippoliti, 2020aIppoliti, , 2020b. In more detail, the strategy of S2 is to use axioms (which embed hypotheses on financial entities) and deductively draw conclusions from them.…”

Section: Philosophy and Mathematical Financementioning

confidence: 99%

Why Finance Needs Philosophy (and Vice Versa): Some Epistemic and Methodological Issues

Ippoliti

2021

Found Sci

Self Cite

View full text Add to dashboard Cite

As the world economy has for better or worse become more and more dependent on the financial markets, a rethinking of the role of finance in both theory and practice is necessary. I argue that such a rethinking requires a new look at the theories of finance that is philosophical in kind. In effect, as Martha Nussbaum claims, if the absence of philosophy in economics is arguably one of the main reasons for the flaws in certain economic theories, the absence of philosophy in finance is one the main reasons for the flaws in our theories on financial systems. In this paper I discuss the mutual relations and benefits between finance and philosophy. First, I examine the contribution that philosophy can offer to finance by analyzing a few critical issues in financial ontology (Section 2.1), financial methodology (Section 2.2) and financial mathematics (Section 2.3). I argue that philosophy is essential to enabling finance to achieve the goals for which it was designed, not only because it is a valuable external addition, but also internally, since philosophy is the proper tool for bringing about new theories and approaches. Then, I examine the contribution that finance can offer to philosophy by analyzing the relationship between theory and practice (Section 3.1), data and hypothesis (Section 3.2), and prediction, description and control (Section 3.3) in the context of financial systems. I argue that finance can help us to rethink some philosophical tenets on these issues.

show abstract

On the heuristic power of mathematical representations

Ippoliti

2022

Synthese

View full text Add to dashboard Cite

I argue that mathematical representations can have heuristic power since their construction can be ampliative. To this end, I examine how a representation (a) introduces elements and properties into the represented object that it does not contain at the beginning of its construction, and (b) how it guides the manipulations of the represented object in ways that restructure its components by gradually adding new pieces of information to produce a hypothesis in order to solve a problem.In addition, I defend an ‘inferential’ approach to the heuristic power of representations by arguing that these representations draw on ampliative inferences such as analogies and inductions. In effect, in order to construct a representation, we have to ‘assimilate’ diverse things, and this requires identifying similarities between them. These similarities form the basis for ampliative inferences that gradually build hypotheses to solve a problem.To support my thesis, I analyse two examples. The first one is intra-field (intra-mathematical), that is, the construction of an algebraic representation of 3-manifolds; the second is inter-fields, that is, the construction of a topological representation of DNA supercoiling.

show abstract

Mathematics and Finance: Some Philosophical Remarks

Cited by 5 publications

References 19 publications

Application of machine learning for financialization modeling

Application of machine learning for financialization modeling

Why Finance Needs Philosophy (and Vice Versa): Some Epistemic and Methodological Issues

On the heuristic power of mathematical representations

Contact Info

Product

Resources

About