Quantifying Systemic Risk by Solutions of the Mean-Variance Risk Model.
The world is still recovering from the financial crisis peaking in September 2008. The triggering event was the bankruptcy of Lehman Brothers. To detect such turmoils, one can investigate the time-dependent behaviour of correlations between assets or indices. These cross-correlations have been conne...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2016-01-01
|
| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC4924827?pdf=render |
| _version_ | 1818043436028133376 |
|---|---|
| author | Jan Jurczyk Alexander Eckrot Ingo Morgenstern |
| author_facet | Jan Jurczyk Alexander Eckrot Ingo Morgenstern |
| author_sort | Jan Jurczyk |
| collection | DOAJ |
| description | The world is still recovering from the financial crisis peaking in September 2008. The triggering event was the bankruptcy of Lehman Brothers. To detect such turmoils, one can investigate the time-dependent behaviour of correlations between assets or indices. These cross-correlations have been connected to the systemic risks within markets by several studies in the aftermath of this crisis. We study 37 different US indices which cover almost all aspects of the US economy and show that monitoring an average investor's behaviour can be used to quantify times of increased risk. In this paper the overall investing strategy is approximated by the ground-states of the mean-variance model along the efficient frontier bound to real world constraints. Changes in the behaviour of the average investor is utlilized as a early warning sign. |
| first_indexed | 2024-12-10T09:02:11Z |
| format | Article |
| id | doaj.art-8c5fa4d4473943d1b5490a66bf6ea78b |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-10T09:02:11Z |
| publishDate | 2016-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-8c5fa4d4473943d1b5490a66bf6ea78b2022-12-22T01:55:14ZengPublic Library of Science (PLoS)PLoS ONE1932-62032016-01-01116e015844410.1371/journal.pone.0158444Quantifying Systemic Risk by Solutions of the Mean-Variance Risk Model.Jan JurczykAlexander EckrotIngo MorgensternThe world is still recovering from the financial crisis peaking in September 2008. The triggering event was the bankruptcy of Lehman Brothers. To detect such turmoils, one can investigate the time-dependent behaviour of correlations between assets or indices. These cross-correlations have been connected to the systemic risks within markets by several studies in the aftermath of this crisis. We study 37 different US indices which cover almost all aspects of the US economy and show that monitoring an average investor's behaviour can be used to quantify times of increased risk. In this paper the overall investing strategy is approximated by the ground-states of the mean-variance model along the efficient frontier bound to real world constraints. Changes in the behaviour of the average investor is utlilized as a early warning sign.http://europepmc.org/articles/PMC4924827?pdf=render |
| spellingShingle | Jan Jurczyk Alexander Eckrot Ingo Morgenstern Quantifying Systemic Risk by Solutions of the Mean-Variance Risk Model. PLoS ONE |
| title | Quantifying Systemic Risk by Solutions of the Mean-Variance Risk Model. |
| title_full | Quantifying Systemic Risk by Solutions of the Mean-Variance Risk Model. |
| title_fullStr | Quantifying Systemic Risk by Solutions of the Mean-Variance Risk Model. |
| title_full_unstemmed | Quantifying Systemic Risk by Solutions of the Mean-Variance Risk Model. |
| title_short | Quantifying Systemic Risk by Solutions of the Mean-Variance Risk Model. |
| title_sort | quantifying systemic risk by solutions of the mean variance risk model |
| url | http://europepmc.org/articles/PMC4924827?pdf=render |
| work_keys_str_mv | AT janjurczyk quantifyingsystemicriskbysolutionsofthemeanvarianceriskmodel AT alexandereckrot quantifyingsystemicriskbysolutionsofthemeanvarianceriskmodel AT ingomorgenstern quantifyingsystemicriskbysolutionsofthemeanvarianceriskmodel |