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A dataset on tail risk of commodities markets
Robert J Powell1, Duc H Vo2, Thach N Pham2
1Edith Cowan University, Australia.
Data in Brief
|October 4, 2017
Summary
This dataset explores commodity market tail risk and its connection to Asian equity markets. It provides daily price data for 24 commodities and three share market indices from 2004-2015.
Area of Science:
- Finance
- Econometrics
- Data Science
Background:
- Commodity markets exhibit significant price volatility.
- Understanding tail risk is crucial for financial market stability.
- The relationship between commodity and equity markets warrants further investigation.
Purpose of the Study:
- To provide a comprehensive dataset for analyzing commodity tail risk.
- To facilitate the examination of commodity price movements and their extreme events.
- To enable research into the association between commodity markets and Asian equity markets.
Main Methods:
- Dataset compilation of daily prices for 24 S&P GSCI commodities (2004-2015).
- Inclusion of daily prices for World, Asia, and South East Asia share market indices.
- Annual segmentation of data to identify the worst 5% of price movements.
Main Results:
- The dataset allows for the measurement of commodity tail risk using Conditional Value at Risk (CVaR).
- Analysis of changes in tail risk across different commodities and time periods is enabled.
- The data supports the investigation of correlations between commodity and equity market performance.
Conclusions:
- The dataset is a valuable resource for researchers studying financial market risk.
- It offers insights into the interconnectedness of global commodity and equity markets.
- The data can inform risk management strategies in both commodity and equity investments.
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