Please use this identifier to cite or link to this item:
https://hdl.handle.net/2445/185282
Title: | Non-Normal Market Losses and Spatial Dependence Using Uncertainty Indices |
Author: | Bolancé Losilla, Catalina Acuña, Carlos Torra Porras, Salvador |
Keywords: | Anàlisi espacial (Estadística) Risc (Economia) Borsa de valors Incertesa (Teoria de la informació) Spatial analysis (Statistics) Risk Stock-exchange Uncertainty (Information theory) |
Issue Date: | 15-Apr-2022 |
Publisher: | MDPI |
Abstract: | We analyse spatial dependence between the risks of stock markets. An alternative definition of neighbour is used and is based on a proposed exogenous criterion obtained with a dynamic Google Trends Uncertainty Index (GTUI) designed specifically for this analysis. We show the impact of systemic risk on spatial dependence related to the most significant financial crises from 2005: the Lehman Brothers bankruptcy, the sub-prime mortgage crisis, the European debt crisis, Brexit and the COVID-19 pandemic, which also affected the financial markets. The risks are measured using the monthly variance or volatility and the monthly Value-at-Risk (VaR) of the filtered losses associated with the analysed indices. Given that the analysed risk measures follow non-normal distributions and the number of neighbours changes over time, we carry out a simulation study to check how these characteristics affect the results of global and local inference using Moran's I statistic. Lastly, we analyse the global spatial dependence between the risks of 46 stock markets and we study the local spatial dependence for 10 benchmark stock markets worldwide. |
Note: | Reproducció del document publicat a: https://doi.org/10.3390/math10081317 |
It is part of: | Mathematics, 2022, vol. 10(8), num. 1317, p. 1-23 |
URI: | https://hdl.handle.net/2445/185282 |
Related resource: | https://doi.org/10.3390/math10081317 |
ISSN: | 2227-7390 |
Appears in Collections: | Articles publicats en revistes (Econometria, Estadística i Economia Aplicada) |
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