Skewness Preference and Market Anomalies

2018 ◽  
Author(s):  
Alok Kumar ◽  
Mehrshad Motahari ◽  
Richard Taffler
Keyword(s):  
Market Anomalies ◽  
Skewness Preference

How are Shorts Informed: Evidence from Market Anomalies

2011 ◽  
Author(s):  
Juan (Julie) Wu ◽  
Andrew (Jianzhong) Zhang
Keyword(s):  
Market Anomalies

Skewness Preference, Value and Size Effects

2005 ◽  
Author(s):  
Suchi Mishra ◽  
Richard A. DeFusco ◽  
Arun J. Prakash
Keyword(s):  
Size Effects ◽  
Skewness Preference

Portfolio choice with skewness preference and wealth-dependent risk aversion

2019 ◽  
Vol 19 (11) ◽  
pp. 1905-1919
Author(s):  
Congming Mu ◽  
Weidong Tian ◽  
Jinqiang Yang
Keyword(s):  
Risk Aversion ◽  
Portfolio Choice ◽  
Skewness Preference

Political uncertainty, market anomalies and Presidential honeymoons

2020 ◽  
Vol 113 ◽  
pp. 105749 ◽  
Author(s):  
Kam Fong Chan ◽  
Philip Gray ◽  
Stephen Gray ◽  
Angel Zhong
Keyword(s):  
Political Uncertainty ◽  
Market Anomalies

scholarly journals Financial Contagion: A Tale of Three Bubbles

2021 ◽  
Vol 14 (5) ◽  
pp. 229
Author(s):  
Nathan Burks ◽  
Adetokunbo Fadahunsi ◽  
Ann Marie Hibbert
Keyword(s):  
Spillover Effects ◽  
Financial Contagion ◽  
Housing Crisis ◽  
Market Anomalies ◽  
Volatility Clustering ◽  
Asset Bubbles ◽  
Potential Benefits ◽  
Chinese Markets ◽  
Composite Indexes ◽  
Robust Evidence

The primary purpose of the study is to identify and measure the properties of asset bubbles, volatility clustering, and financial contagion during three recent financial market anomalies that originated in the U.S. and Chinese markets. In particular, we focus on the 2000 DotCom Bubble, the 2008 Housing Crisis, and the 2015 Chinese Bubble. We employ three main empirical methods; the LPPL model to identify asset bubbles, the DCC-GARCH model to measure volatility clustering, and the Diebold-Yilmaz volatility spillover index to measure the level of financial contagion. We provide robust evidence that during the DotCom bubble there was very limited spillover between the S&P 500, the Shanghai, and the Shenzhen Composite Indexes. However, there was significantly more spillover effects in the two more recent crises, i.e., the Housing crisis and the 2015 Chinese Bubble. Together, these results highlight the fact that as financial markets have become more globalized, there are greater levels of volatility transmission and correspondingly fewer potential benefits from international diversification.

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