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Commodity markets present several challenges for quantitative modeling. These include high volatilities, small sample data sets, and physical, operational complexity. In addition, the set of traded products in commodity markets is more limited than in financial or equity markets, making value...
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The aim of this study is to enhance the understanding of volatility dynamics in commodity returns, such as gold and … capturing volatility clustering, asymmetry, and long-term memory effects in asset returns. By employing models like sGARCH …, eGARCH, gjrGARCH, and FIGARCH, the research offers a nuanced understanding of volatility evolution and its impact on asset …
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This paper evaluates how different types of speculation affect the volatility of commodities' futures prices. We adopt …-2010 analyzed at weekly frequency. Using GARCH models we find that speculation significantly affects volatility of returns: short … term speculation has a positive and significant impact on volatility, while long term speculation generally has a negative …
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