09/04/2021 - Bitcoin versus high-performance technology stocks in diversifying against global stock market indices - Speaker: Stephen Chan (American University of Sharjah)
UFSCar/USP joint Seminar
Scheduled for:
April 9, 2021, at 2:00 pm
Scheduled for:
April 9, 2021, at 2:00 pm
(GMT-03:00) Brasilia Standard Time - Sao Paulo
Speaker:
Stephen Chan (American University of Sharjah)
Title:
Title:
Bitcoin versus high-performance technology stocks in diversifying against global stock market indices
Abstract:
Abstract:
The paper investigates Bitcoin in finance but from the perspective of technology. Through comparing the relationship between the returns of Bitcoin and high-performance technology stocks, and a range of global stock markets, we investigate whether there is any evidence of potential hedging and diversification properties and whether these are conditional on the states of the respective markets. We implement a quantile-on-quantile regression method to examine the relationship between both Bitcoin returns and technology stock returns, and stock market returns at varying quantiles. Our results show that although Bitcoin and high-performance technology stocks arguably share many similarities, it is clear that Bitcoin exhibits significant differences compared with high-performance technology stocks in terms of the diversification properties against global stock markets. From a financial perspective, this may suggest that individuals do not see and treat Bitcoin as a technology (or a technology company), but rather further supports the view of Bitcoin as a potential investment for financial gain (given its diversification properties).
Bio:
Stephen Chan is an assistant professor at the American University of Sharjah, UAE. He was awarded the EPSRC Doctoral Prize Fellowship in 2016 at the University of Manchester, UK. His research areas include extreme value analysis and distribution theory in analyzing financial commodities data, Blockchain and cryptocurrencies data. He co-developed and co-wrote an R package, entitled 'VaRES', for computing value at risk and expected shortfall. He is a co-author of the book Extreme Events in Finance: A Handbook of Extreme Value Theory and its Applications.