Measuring the risk of Chinese Fintech industry: evidence from the stock index

Yinhong Yao; Jianping Li; Xiaolei Sun

doi:10.1016/j.frl.2020.101564

Measuring the risk of Chinese Fintech industry: evidence from the stock index

Yinhong Yao
, Jianping Li
, Xiaolei Sun^*

^*Corresponding author for this work

CAS - Institutes of Science and Development
University of Chinese Academy of Sciences

Research output: Contribution to journal › Article › peer-review

33 Scopus citations

Abstract

This study measures the risk of the emerging Fintech industry in China and identifies its influencing risk factors by calculating the tail risk of Fintech stock index. The expectile regression model that includes the lagged returns and macroeconomic risk factors is used to calculate the Expectile Value-at-Risk (EVaR). Based on the 1230 daily returns of Fintech index ranges from July 2, 2014, to September 10, 2019, the empirical results indicate that the Fintech industry possesses a higher risk, and is affected by both the past development and internal macroeconomic condition.

Original language	English
Article number	101564
Journal	Finance Research Letters
Volume	39
DOIs	https://doi.org/10.1016/j.frl.2020.101564
State	Published - Mar 2021
Externally published	Yes

Keywords

Expected shortfall (ES)
Expectile regression model
Expectile Value at Risk (EVaR)
Financial Technology (Fintech)
Tail risk

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10.1016/j.frl.2020.101564

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title = "Measuring the risk of Chinese Fintech industry: evidence from the stock index",

abstract = "This study measures the risk of the emerging Fintech industry in China and identifies its influencing risk factors by calculating the tail risk of Fintech stock index. The expectile regression model that includes the lagged returns and macroeconomic risk factors is used to calculate the Expectile Value-at-Risk (EVaR). Based on the 1230 daily returns of Fintech index ranges from July 2, 2014, to September 10, 2019, the empirical results indicate that the Fintech industry possesses a higher risk, and is affected by both the past development and internal macroeconomic condition.",

keywords = "Expected shortfall (ES), Expectile regression model, Expectile Value at Risk (EVaR), Financial Technology (Fintech), Tail risk",

author = "Yinhong Yao and Jianping Li and Xiaolei Sun",

note = "Publisher Copyright: {\textcopyright} 2020 Elsevier Inc.",

year = "2021",

month = mar,

doi = "10.1016/j.frl.2020.101564",

language = "英语",

volume = "39",

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T1 - Measuring the risk of Chinese Fintech industry

T2 - evidence from the stock index

AU - Yao, Yinhong

AU - Li, Jianping

AU - Sun, Xiaolei

PY - 2021/3

Y1 - 2021/3

N2 - This study measures the risk of the emerging Fintech industry in China and identifies its influencing risk factors by calculating the tail risk of Fintech stock index. The expectile regression model that includes the lagged returns and macroeconomic risk factors is used to calculate the Expectile Value-at-Risk (EVaR). Based on the 1230 daily returns of Fintech index ranges from July 2, 2014, to September 10, 2019, the empirical results indicate that the Fintech industry possesses a higher risk, and is affected by both the past development and internal macroeconomic condition.

AB - This study measures the risk of the emerging Fintech industry in China and identifies its influencing risk factors by calculating the tail risk of Fintech stock index. The expectile regression model that includes the lagged returns and macroeconomic risk factors is used to calculate the Expectile Value-at-Risk (EVaR). Based on the 1230 daily returns of Fintech index ranges from July 2, 2014, to September 10, 2019, the empirical results indicate that the Fintech industry possesses a higher risk, and is affected by both the past development and internal macroeconomic condition.

KW - Expected shortfall (ES)

KW - Expectile regression model

KW - Expectile Value at Risk (EVaR)

KW - Financial Technology (Fintech)

KW - Tail risk

UR - https://www.scopus.com/pages/publications/85085173288

U2 - 10.1016/j.frl.2020.101564

DO - 10.1016/j.frl.2020.101564

M3 - 文章

AN - SCOPUS:85085173288

SN - 1544-6123

VL - 39

JO - Finance Research Letters

JF - Finance Research Letters

M1 - 101564

ER -

Measuring the risk of Chinese Fintech industry: evidence from the stock index

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Keywords

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