Financial contagion and the TIR-MIDAS model

Ye, Wuyi; Jiang, Kunliang; Liu, Xiaoquan

doi:10.1016/j.frl.2020.101589

Cited by 5 publications

(2 citation statements)

References 20 publications

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“…However, at scale D8, risk contagion contributions mainly come from African, Asian, South American, and Oceanic markets; and this result is different from that at the most approximate scale D1. Nevertheless, the results of the literature [4,19,38,49] concerning forecasting future return fluctuations focus on the main developed countries, which agree with our results at the most approximate scale, in other words, the long-run characteristics. e results at the exquisite scales vary so much from each other that we ascribe this to the economic uncertainty of each country in the short run.…”

Section: Complexitysupporting

confidence: 90%

Multiscale Tail Risk Connectedness of Global Stock Markets: A LASSO‐Based Network Topology Approach

Zhang

Ding

et al. 2022

Complexity

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Due to the advent of deglobalization and regional integration, this article aims to adopt LASSO-based network connectedness to estimate the multiscale tail risk spillover effects of global stock markets. The results show that tail risk varies across frequencies and shocks. In static analysis, the risk is centered mostly on the developed European and North American markets at a low frequency (long term), and regionalization is imposed on the moderate frequency (midterm). Moreover, emerging markets could be sources of risk spillover, especially at the highest frequency (short term) where there is no absolute risk center. In dynamic analysis, we use rolling window estimation and find that different frequencies identify distinct episodes of shocks, which provides us with the reason for the diverse risk centers at different time scales in static analysis. Our findings provide heterogeneous financial practitioners, regulators, and investors with diverse characteristics of stock markets under multiple time horizons and help them operate their own trading strategies.

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Section: Complexitysupporting

confidence: 90%

Multiscale Tail Risk Connectedness of Global Stock Markets: A LASSO‐Based Network Topology Approach

Zhang

Ding

et al. 2022

Complexity

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“…In this way, it could be taken into consideration so that a country in a specific pattern could emigrate to another with greater benefit from imposing changes that tend to modify its own macroeconomic variables. Some works, such as those by Gkillas et al [13] and Ye et al [14], show empirical evidence that macroeconomic variables can determine the size of the contagion. In this research, we take Altınbaş et al [15] as a reference to examine contagion through the fundamental channel, considering macroeconomic variables that could potentiate this situation.…”

Section: Introductionmentioning

confidence: 99%

Contagion Patterns Classification in Stock Indices: A Functional Clustering Analysis Using Decision Trees

Razo-De-Anda,

Romero-Castro,

Venegas-Martínez

2023

Mathematics

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This paper aims to identify the main determinants of the countries that present contagion during the period 2000–2021, based on the determination of the behavior patterns of 18 stock market indices of 15 of the main economies. To do that, first, the B-spline method and Bezier curves are used to smooth observations by minimizing the noise. Subsequently, the Functional Principal Component Analysis (FPCA) methodology is applied. Then, the K-means clustering algorithm is used to determine the main groups using the silhouette method and cross-validation, considering the sum of squares of the distances as the function to minimize. Finally, classification trees and macroeconomic and financial analyses are used to determine the rules of variables that give a direct explanation of the contagion (clustering) between the stock indices. The main empirical results obtained suggest that the most significant macroeconomic variables are the Gross Domestic Product, the Consumer Price Index, and Foreign Direct Investment, while in the financial aspect and the most representative are Domestic Credit and number of companies listed on the stock market. It is worth noticing that government spending does not have a significant effect at any time as a determinant of contagion. Finally, it is important to mention, and surprising, that Mexico’s IPC was not clustered in the same group of US stock market indices anytime, despite the strong commercial relationship and the geographical closeness.

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Unleashing the Potential of Mixed Frequency Data: Measuring Risk with Dynamic Tail Index Regression Model

An,

Tian

2024

Comput Econ

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Financial contagion and the TIR-MIDAS model

Cited by 5 publications

References 20 publications

Multiscale Tail Risk Connectedness of Global Stock Markets: A LASSO‐Based Network Topology Approach

Multiscale Tail Risk Connectedness of Global Stock Markets: A LASSO‐Based Network Topology Approach

Contagion Patterns Classification in Stock Indices: A Functional Clustering Analysis Using Decision Trees

Unleashing the Potential of Mixed Frequency Data: Measuring Risk with Dynamic Tail Index Regression Model

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