Frontiers of Quantitative Financial Modelling: A Literature Review on the Evolution in Financial and Risk Modelling after the Financial Crisis (2008-2019)

85 Pages Posted: 18 Feb 2021 Last revised: 28 Mar 2022

See all articles by Markus Vogl

Markus Vogl

Markus Vogl {Business & Data Science}

Date Written: January 12, 2021

Abstract

Abstract:

This study provides a holistic and quantitative overview of over 800 mathematical methods (e.g. financial and risk models, statistical tests, statistics and advanced algorithms) taken out of sampled scientific literature on financial and risk modelling by applying a bibliometric approach from 2008–2019 and a citation network analysis. I present a content analysis of journals, main topics, applied data sets and frontiers within quantitative modelling and highlight details about quantitative features such as implemented models, algorithms and aggregated model-family combinations. Moreover, I describe explications and ties to empirical stylised facts (e.g. asymmetry or nonlinearity). Finally, I discuss insights, such as my main finding, namely the non-existence of a “single-best”-approach as well as the future prospects.


Highlights:

• Quantitative overview of model evolution in financial and risk modelling
• Sophisticated overview of stylised facts (e.g. multifractality or nonlinearities)
• Quantitative features overview (e.g. implemented models or aggregated model-families)
• A content analysis (e.g. employed data sets, statements) is properly deduced
• Main statement is the non-existence of a “single-best”-approach

Keywords: literature review, financial modelling, risk modelling, quantitative finance, quantitative model families, citation network, bibliographic analysis

JEL Classification: C01, C02, C22, G01, G11, G12, G13, G14, G17

Suggested Citation

Vogl, Markus, Frontiers of Quantitative Financial Modelling: A Literature Review on the Evolution in Financial and Risk Modelling after the Financial Crisis (2008-2019) (January 12, 2021). Available at SSRN: https://ssrn.com/abstract=3764570 or http://dx.doi.org/10.2139/ssrn.3764570

Markus Vogl (Contact Author)

Markus Vogl {Business & Data Science} ( email )

Adelheidstraße 51
Wiesbaden, Hessen 65185
Germany

HOME PAGE: http://www.vogl-datascience.de

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