Are Benefits from Oil - Stocks Diversification Gone? A New Evidence from a Dynamic Copulas and High Frequency Data

2013 ◽  
Author(s):  
Krenar Avdulaj ◽  
Jozef Barunik
Keyword(s):  
High Frequency ◽  
High Frequency Data ◽  
Frequency Data ◽  
New Evidence

scholarly journals Discovering interlinkages between major cryptocurrencies using high-frequency data: new evidence from COVID-19 pandemic

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Imran Yousaf ◽  
Shoaib Ali
Keyword(s):  
High Frequency ◽  
Portfolio Diversification ◽  
High Frequency Data ◽  
Volatility Spillover ◽  
Frequency Data ◽  
Optimal Weights ◽  
Hedging Effectiveness ◽  
Hedge Ratios ◽  
Portfolio Managers ◽  
New Evidence

Abstract Through the application of the VAR-AGARCH model to intra-day data for three cryptocurrencies (Bitcoin, Ethereum, and Litecoin), this study examines the return and volatility spillover between these cryptocurrencies during the pre-COVID-19 period and the COVID-19 period. We also estimate the optimal weights, hedge ratios, and hedging effectiveness during both sample periods. We find that the return spillovers vary across the two periods for the Bitcoin–Ethereum, Bitcoin–Litecoin, and Ethereum–Litecoin pairs. However, the volatility transmissions are found to be different during the two sample periods for the Bitcoin–Ethereum and Bitcoin–Litecoin pairs. The constant conditional correlations between all pairs of cryptocurrencies are observed to be higher during the COVID-19 period compared to the pre-COVID-19 period. Based on optimal weights, investors are advised to decrease their investments (a) in Bitcoin for the portfolios of Bitcoin/Ethereum and Bitcoin/Litecoin and (b) in Ethereum for the portfolios of Ethereum/Litecoin during the COVID-19 period. All hedge ratios are found to be higher during the COVID-19 period, implying a higher hedging cost compared to the pre-COVID-19 period. Last, the hedging effectiveness is higher during the COVID-19 period compared to the pre-COVID-19 period. Overall, these findings provide useful information to portfolio managers and policymakers regarding portfolio diversification, hedging, forecasting, and risk management.

Forecasting Exchange Rate Realized Volatility Through Decomposition Using High-Frequency Data

2017 ◽  
Author(s):  
Rim mname Lamouchi ◽  
Russell mname Davidson ◽  
Ibrahim mname Fatnassi ◽  
Abderazak Ben mname Maatoug
Keyword(s):  
Exchange Rate ◽  
High Frequency ◽  
Realized Volatility ◽  
High Frequency Data ◽  
Frequency Data
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