Financial Market Crash Prediction Through Analysis of Stable and Pareto Distributions

Jesus Enrique Molina Muñoz; Andrés Mora Valencia; Javier Perote

doi:DOI https://doi.org/10.1007/978-3-030-78965-7

Financial Market Crash Prediction Through Analysis of Stable and Pareto Distributions

Jesus Enrique Molina Muñoz, Andrés Mora Valencia, Javier Perote

urosario

Research output: Chapter in Book/Inform › Chapter (peer-reviewed) › peer-review

Abstract

This manuscript proposes a market crash forecasting methodology based on the analysis of the shape parameter of the alpha-stable distribution. Moreover, the parameters of Pareto type II distribution are also employed for comparison purposes. The model performance is assessed by Quadratic Probability Score, Logarithmic Probability Score, and Directional Accuracy measures. Our applications for developed and emerging markets show a good accuracy for alpha-stable distribution and replicability of the results. Thus, our model is an adequate early warning system for future crashes.

Original language	English (US)
Title of host publication	Mathematical and Statistical Methods for Actuarial Sciences and Finance
Place of Publication	Suiza
Publisher	Springer
Chapter	52
Pages	1-10
Number of pages	10
Edition	1
ISBN (Electronic)	978-3-030-78965-7
DOIs	https://doi.org/DOI https://doi.org/10.1007/978-3-030-78965-7
State	Published - Dec 14 2021
Event	MAF 2020 - 9th International Conference MATHEMATICAL AND STATISTICAL METHODS FOR ACTUARIAL SCIENCES AND FINANCE - https://www.unige.ch/maf2020/, Suiza, Switzerland Duration: Apr 15 2020 → Apr 17 2020 https://www.unige.ch/maf2020/

Conference

Conference	MAF 2020 - 9th International Conference MATHEMATICAL AND STATISTICAL METHODS FOR ACTUARIAL SCIENCES AND FINANCE
Country/Territory	Switzerland
City	Suiza
Period	4/15/20 → 4/17/20
Internet address	https://www.unige.ch/maf2020/

Access to Document

DOI https://doi.org/10.1007/978-3-030-78965-7

Cite this

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title = "Financial Market Crash Prediction Through Analysis of Stable and Pareto Distributions",

abstract = "This manuscript proposes a market crash forecasting methodology based on the analysis of the shape parameter of the alpha-stable distribution. Moreover, the parameters of Pareto type II distribution are also employed for comparison purposes. The model performance is assessed by Quadratic Probability Score, Logarithmic Probability Score, and Directional Accuracy measures. Our applications for developed and emerging markets show a good accuracy for alpha-stable distribution and replicability of the results. Thus, our model is an adequate early warning system for future crashes.",

author = "{Molina Mu{\~n}oz}, {Jesus Enrique} and {Mora Valencia}, Andr{\'e}s and Javier Perote",

year = "2021",

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booktitle = "Mathematical and Statistical Methods for Actuarial Sciences and Finance",

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note = "MAF 2020 - 9th International Conference MATHEMATICAL AND STATISTICAL METHODS FOR ACTUARIAL SCIENCES AND FINANCE<br/> ; Conference date: 15-04-2020 Through 17-04-2020",

url = "https://www.unige.ch/maf2020/",

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Molina Muñoz, JE, Mora Valencia, A & Perote , J 2021, Financial Market Crash Prediction Through Analysis of Stable and Pareto Distributions. in Mathematical and Statistical Methods for Actuarial Sciences and Finance. 1 edn, Springer, Suiza, pp. 1-10, MAF 2020 - 9th International Conference MATHEMATICAL AND STATISTICAL METHODS FOR ACTUARIAL SCIENCES AND FINANCE
, Suiza, Switzerland, 4/15/20. https://doi.org/DOI https://doi.org/10.1007/978-3-030-78965-7

TY - CHAP

T1 - Financial Market Crash Prediction Through Analysis of Stable and Pareto Distributions

AU - Molina Muñoz, Jesus Enrique

AU - Mora Valencia, Andrés

AU - Perote , Javier

PY - 2021/12/14

Y1 - 2021/12/14

N2 - This manuscript proposes a market crash forecasting methodology based on the analysis of the shape parameter of the alpha-stable distribution. Moreover, the parameters of Pareto type II distribution are also employed for comparison purposes. The model performance is assessed by Quadratic Probability Score, Logarithmic Probability Score, and Directional Accuracy measures. Our applications for developed and emerging markets show a good accuracy for alpha-stable distribution and replicability of the results. Thus, our model is an adequate early warning system for future crashes.

AB - This manuscript proposes a market crash forecasting methodology based on the analysis of the shape parameter of the alpha-stable distribution. Moreover, the parameters of Pareto type II distribution are also employed for comparison purposes. The model performance is assessed by Quadratic Probability Score, Logarithmic Probability Score, and Directional Accuracy measures. Our applications for developed and emerging markets show a good accuracy for alpha-stable distribution and replicability of the results. Thus, our model is an adequate early warning system for future crashes.

U2 - DOI https://doi.org/10.1007/978-3-030-78965-7

DO - DOI https://doi.org/10.1007/978-3-030-78965-7

M3 - Chapter (peer-reviewed)

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EP - 10

BT - Mathematical and Statistical Methods for Actuarial Sciences and Finance

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T2 - MAF 2020 - 9th International Conference MATHEMATICAL AND STATISTICAL METHODS FOR ACTUARIAL SCIENCES AND FINANCE<br/>

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