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"Carbon Spectacular" - Exploring the Path to Enhance the Precision of Fiscal and Tax Support for Innovative Technologies in Energy Conservation and Emission Reduction

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  • Amalia, Shendy
  • Effendi, Kharisya Ayu
  • Riantani, Suskim

Abstract

This research explores the impact of macroeconomic factors on the volatility of tin commodity futures contract prices, with a focus on inflation, interest rates and forward prices. The volatility of tin futures prices is important to investment strategies and risk management. Understanding the influence of these macroeconomic variables helps in making better investment decisions. The independent variables analyzed include inflation (X1), interest rates (X2), and forward prices (X3). Inflation reflects general price increases that can increase production costs and affect commodity prices. Interest rates are borrowing costs that influence investment decisions through the cost of capital. Forward prices reflect market expectations of future commodity prices. The dependent variable is the volatility of the tin commodity futures contract price (Y). This research methodology uses linear regression to analyze historical data from the three macroeconomic variables. Data is collected from economic reports, financial market data, and government publications. Analysis is carried out to determine the influence of each variable on futures price volatility. The research results show that inflation and forward prices have a significant influence on the volatility of tin futures contract prices, while interest rates have no significant influence. Increased inflation leads to increases in production costs and prices of goods, increasing future price uncertainty and volatility. High forward prices reflect expectations of future increases in commodity prices, which also increases volatility. Meanwhile, interest rates do not significantly affect borrowing costs, so they have no impact on futures contract price volatility.

Suggested Citation

  • Amalia, Shendy & Effendi, Kharisya Ayu & Riantani, Suskim, 2024. ""Carbon Spectacular" - Exploring the Path to Enhance the Precision of Fiscal and Tax Support for Innovative Technologies in Energy Conservation and Emission Reduction," OSF Preprints 4rydm, Center for Open Science.
  • Handle: RePEc:osf:osfxxx:4rydm
    DOI: 10.31219/osf.io/4rydm
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    References listed on IDEAS

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    1. Kilian, Lutz & Lee, Thomas K., 2014. "Quantifying the speculative component in the real price of oil: The role of global oil inventories," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 71-87.
    2. Simona Delle Chiaie & Laurent Ferrara & Domenico Giannone, 2022. "Common factors of commodity prices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 461-476, April.
    3. Lutz Kilian, 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," American Economic Review, American Economic Association, vol. 99(3), pages 1053-1069, June.
    4. Lutz Kilian & Daniel P. Murphy, 2014. "The Role Of Inventories And Speculative Trading In The Global Market For Crude Oil," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(3), pages 454-478, April.
    5. Simona Bigerna & Maria Chiara D’Errico & Paolo Polinori & Paul Simshauser, 2023. "Net-Zero Policy vs Energy Security: The Impact on GCC Countries," The Energy Journal, , vol. 44(1_suppl), pages 1-32, November.
    6. Xinyu Wang & Lele Zhang & Qiuying Cheng & Song Shi & Huawei Niu, 2022. "What drives risk in China’s soybean futures market? Evidence from a flexible GARCH-MIDAS model," Journal of Applied Economics, Taylor & Francis Journals, vol. 25(1), pages 454-475, December.
    7. Gary Gorton & K. Geert Rouwenhorst, 2004. "Facts and Fantasies about Commodity Futures," NBER Working Papers 10595, National Bureau of Economic Research, Inc.
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