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題名 原物料相關公司股價對於原物料價格是否存在預測能力，以鋰與鐵礦砂為例
Can related stock prices accurately predict commodity prices, using lithium and iron ore as examples?作者 焦祖傑
Chiao, Tsu-Chieh貢獻者 張元晨
焦祖傑
Chiao, Tsu-Chieh關鍵詞 原物料
電動車
鋰
電池級碳酸鋰
鐵礦砂
預測能力
股價
Commodity
Electric vehicle
Lithium
Battery-grade lithium carbonate
Iron ore
Predictive ability
Stock price日期 2023 上傳時間 2-Aug-2023 13:01:05 (UTC+8) 摘要 由於電動車在近年蓬勃發展，現階段最主流的電動車電池為鋰電池，故本文選取電池級碳酸鋰作為研究對象，同時納入傳統產業鐵礦砂作為對照的研究對象，並選取原物料相關的公司作為樣本，探討原物料相關公司股價對於原物料價格是否存在預測能力，分為鋰礦商、鋰電池製造商、鐵礦商與鋼鐵公司，進一步比較這兩個產業相關公司股價對於原物料價格的預測能力。實證結果發現在特定的樣本內與樣本外比例與預測期間時，相關公司股價走勢對原物料價格走勢顯著地存在預測能力，在樣本內的預測能力，除了鋰電池製造商統計上不顯著以外，在鋰礦商、鐵礦商與鋼鐵公司皆具有統計上顯著的預測能力，公司股價與原物料價格存在顯著正向關係，同時在樣本外預測能力方面，本研究發現電池級碳酸鋰相關公司的預測能力優於鐵礦砂相關公司。
Due to the vigorous development of electric vehicles in recent years, the most mainstream electric vehicle batteries at this stage are lithium batteries. Therefore, this paper selects battery-grade lithium carbonate as the research object. Since lithium is an emerging industry in recent years, this paper also includes iron ore, a traditional industry, as a research object. The companies related to these commodities are selected as samples to investigate the predictive power of their stock prices.The empirical results indicate that, within a specific in-sample and out-of-sample ratio and forecast period, the related stock prices demonstrate significant predictive ability for commodity prices. However, the predictive ability of lithium battery manufacturers in the sample is statistically insignificant, while lithium miners, iron miners, and steel companies show statistically significant results. There exists a significant positive relationship between related stock prices and commodity prices. When considering the out-of-sample data, the predictive ability of companies related to battery-grade lithium carbonate is superior to that of companies related to iron ore.參考文獻 Akram, Q.F. (2009). Commodity prices, interest rates and the dollar. Energy Economics, 31(6), 838-851Alam, M.M. and G. Uddin (2009). Relationship between Interest Rate and Stock Price: Empirical Evidence from Developed and Developing Countries. International Journal of Business and Management, 4(3), 43-51Alexius, A. and D. Spång (2018). Stock prices and GDP in the long run. Journal of Applied Finance & Banking, 8(4), 107-126Andries, A.M., I. Ihnatov, and A.K. Tiwari (2014). Analyzing time–frequency relationship between interest rate, stock price and exchange rate through continuous wavelet. Economic Modelling, 41, 227-238Campbell, J., and S. Thompson (2008). Predicting excess stock returns out of sample:Can anything beat the historical average?. The Review of Financial Studies, 21(4), 1509-31Chen, Y., K. Rogoff, and B. Rossi (2010). Can exchange rates forecast commodityprices?. The Quarterly Journal of Economics, 125(3), 1145-94Chen, S. (2014). Forecasting crude oil price movements with oil-sensitive stocks. Economic Inquiry, 52(2), 830-44Chen, S. (2016). Commodity prices and related equity prices. The Canadian Journal of Economics, 49(3), 949-967Diebold, F.X., and R.S. Mariano (1995). Comparing predictive accuracy. J. Bus. Econ. Stat. 13, 253–263.Faisal, F., P.M. Muhamad, and T. Tursoy (2016). Impact of Economic Growth, Foreign Direct Investment and Financial Development on Stock Prices in China: Empirical Evidence from Time Series Analysis. International Journal of Economics and Financial Issues, 6(4), 1998-2006Frankel, J.A. (2014). Effects of speculation and interest rates in a “carry trade” model of commodity prices. Journal of International Money and Finance, 42, 88-112Jiang, Y., G. Tian, and B. Mo (2020). Spillover and quantile linkage between oil price shocks and stock returns: new evidence from G7 countries. Financial Innovation, 6(42)Kilian, L., and C. Vega (2011). Do Energy Prices Respond to U.S. Macroeconomic News? A Test of the Hypothesis of Predetermined Energy Prices. The Review of Economics and Statistics, 93(2), 660-671Rossi, B. (2012). The changing relationship between commodity prices and equity prices in commodity exporting countries. IMF Economic Review, 60(4), 533-69Wang, Q., and R. Balvers (2021). Determinants and predictability of commodity producer returns. Journal of Banking & Finance, 133, 278-287Wei, P., and Y. Chang (2016). The Relationship between Equity and Commodity Markets during the Credit Crisis. Academia Economic Papers, 44(1), 93-125Zhang, Y., and J. Wang (2019) Do high-frequency stock market data help forecast crude oil prices? Evidence from the MIDAS models. Energy Economics, 78, 192-201參考資料1. mining.com (https://www.mining.com/)2. elements.visualcapitalist.com (https://elements.visualcapitalist.com/)3. miningintelligence.com (https://www.miningintelligence.com/)4. worldsteel.org (https://worldsteel.org/)5. investing.com(https://www.investing.com/ 描述 碩士
國立政治大學
財務管理學系
110357035資料來源 http://thesis.lib.nccu.edu.tw/record/#G0110357035 資料類型 thesis dc.contributor.advisor 張元晨 zh_TW dc.contributor.author (Authors) 焦祖傑 zh_TW dc.contributor.author (Authors) Chiao, Tsu-Chieh en_US dc.creator (作者) 焦祖傑 zh_TW dc.creator (作者) Chiao, Tsu-Chieh en_US dc.date (日期) 2023 en_US dc.date.accessioned 2-Aug-2023 13:01:05 (UTC+8) - dc.date.available 2-Aug-2023 13:01:05 (UTC+8) - dc.date.issued (上傳時間) 2-Aug-2023 13:01:05 (UTC+8) - dc.identifier (Other Identifiers) G0110357035 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/146293 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 財務管理學系 zh_TW dc.description (描述) 110357035 zh_TW dc.description.abstract (摘要) 由於電動車在近年蓬勃發展，現階段最主流的電動車電池為鋰電池，故本文選取電池級碳酸鋰作為研究對象，同時納入傳統產業鐵礦砂作為對照的研究對象，並選取原物料相關的公司作為樣本，探討原物料相關公司股價對於原物料價格是否存在預測能力，分為鋰礦商、鋰電池製造商、鐵礦商與鋼鐵公司，進一步比較這兩個產業相關公司股價對於原物料價格的預測能力。實證結果發現在特定的樣本內與樣本外比例與預測期間時，相關公司股價走勢對原物料價格走勢顯著地存在預測能力，在樣本內的預測能力，除了鋰電池製造商統計上不顯著以外，在鋰礦商、鐵礦商與鋼鐵公司皆具有統計上顯著的預測能力，公司股價與原物料價格存在顯著正向關係，同時在樣本外預測能力方面，本研究發現電池級碳酸鋰相關公司的預測能力優於鐵礦砂相關公司。 zh_TW dc.description.abstract (摘要) Due to the vigorous development of electric vehicles in recent years, the most mainstream electric vehicle batteries at this stage are lithium batteries. Therefore, this paper selects battery-grade lithium carbonate as the research object. Since lithium is an emerging industry in recent years, this paper also includes iron ore, a traditional industry, as a research object. The companies related to these commodities are selected as samples to investigate the predictive power of their stock prices.The empirical results indicate that, within a specific in-sample and out-of-sample ratio and forecast period, the related stock prices demonstrate significant predictive ability for commodity prices. However, the predictive ability of lithium battery manufacturers in the sample is statistically insignificant, while lithium miners, iron miners, and steel companies show statistically significant results. There exists a significant positive relationship between related stock prices and commodity prices. When considering the out-of-sample data, the predictive ability of companies related to battery-grade lithium carbonate is superior to that of companies related to iron ore. en_US dc.description.tableofcontents 第一章 緒論 7第一節 研究背景與動機 7第二節 研究目的 8第三節 研究架構 9第二章 文獻回顧 10第一節 與原物料價格相關的變數探討 10第二節 與股票價格相關的變數探討 13第三章 研究方法 16第一節 樣本資料與來源 16第二節 變數定義 18第三節 研究假說 19第四節 實證研究模型 20第四章 實證結果 23第一節 敘述統計 23第二節 單根檢定 24第三節 樣本內預測 24第四節 樣本外預測 26第五章 結論 31第一節 本文結論 31第二節 未來研究之建議 32參考文獻 34參考資料 35 zh_TW dc.format.extent 1633108 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0110357035 en_US dc.subject (關鍵詞) 原物料 zh_TW dc.subject (關鍵詞) 電動車 zh_TW dc.subject (關鍵詞) 鋰 zh_TW dc.subject (關鍵詞) 電池級碳酸鋰 zh_TW dc.subject (關鍵詞) 鐵礦砂 zh_TW dc.subject (關鍵詞) 預測能力 zh_TW dc.subject (關鍵詞) 股價 zh_TW dc.subject (關鍵詞) Commodity en_US dc.subject (關鍵詞) Electric vehicle en_US dc.subject (關鍵詞) Lithium en_US dc.subject (關鍵詞) Battery-grade lithium carbonate en_US dc.subject (關鍵詞) Iron ore en_US dc.subject (關鍵詞) Predictive ability en_US dc.subject (關鍵詞) Stock price en_US dc.title (題名) 原物料相關公司股價對於原物料價格是否存在預測能力，以鋰與鐵礦砂為例 zh_TW dc.title (題名) Can related stock prices accurately predict commodity prices, using lithium and iron ore as examples? en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) Akram, Q.F. (2009). Commodity prices, interest rates and the dollar. Energy Economics, 31(6), 838-851Alam, M.M. and G. Uddin (2009). Relationship between Interest Rate and Stock Price: Empirical Evidence from Developed and Developing Countries. International Journal of Business and Management, 4(3), 43-51Alexius, A. and D. Spång (2018). Stock prices and GDP in the long run. Journal of Applied Finance & Banking, 8(4), 107-126Andries, A.M., I. Ihnatov, and A.K. Tiwari (2014). Analyzing time–frequency relationship between interest rate, stock price and exchange rate through continuous wavelet. Economic Modelling, 41, 227-238Campbell, J., and S. Thompson (2008). Predicting excess stock returns out of sample:Can anything beat the historical average?. The Review of Financial Studies, 21(4), 1509-31Chen, Y., K. Rogoff, and B. Rossi (2010). Can exchange rates forecast commodityprices?. The Quarterly Journal of Economics, 125(3), 1145-94Chen, S. (2014). Forecasting crude oil price movements with oil-sensitive stocks. Economic Inquiry, 52(2), 830-44Chen, S. (2016). Commodity prices and related equity prices. The Canadian Journal of Economics, 49(3), 949-967Diebold, F.X., and R.S. Mariano (1995). Comparing predictive accuracy. J. Bus. Econ. Stat. 13, 253–263.Faisal, F., P.M. Muhamad, and T. Tursoy (2016). Impact of Economic Growth, Foreign Direct Investment and Financial Development on Stock Prices in China: Empirical Evidence from Time Series Analysis. International Journal of Economics and Financial Issues, 6(4), 1998-2006Frankel, J.A. (2014). Effects of speculation and interest rates in a “carry trade” model of commodity prices. Journal of International Money and Finance, 42, 88-112Jiang, Y., G. Tian, and B. Mo (2020). Spillover and quantile linkage between oil price shocks and stock returns: new evidence from G7 countries. Financial Innovation, 6(42)Kilian, L., and C. Vega (2011). Do Energy Prices Respond to U.S. Macroeconomic News? A Test of the Hypothesis of Predetermined Energy Prices. The Review of Economics and Statistics, 93(2), 660-671Rossi, B. (2012). The changing relationship between commodity prices and equity prices in commodity exporting countries. IMF Economic Review, 60(4), 533-69Wang, Q., and R. Balvers (2021). Determinants and predictability of commodity producer returns. Journal of Banking & Finance, 133, 278-287Wei, P., and Y. Chang (2016). The Relationship between Equity and Commodity Markets during the Credit Crisis. Academia Economic Papers, 44(1), 93-125Zhang, Y., and J. Wang (2019) Do high-frequency stock market data help forecast crude oil prices? Evidence from the MIDAS models. Energy Economics, 78, 192-201參考資料1. mining.com (https://www.mining.com/)2. elements.visualcapitalist.com (https://elements.visualcapitalist.com/)3. miningintelligence.com (https://www.miningintelligence.com/)4. worldsteel.org (https://worldsteel.org/)5. investing.com(https://www.investing.com/ zh_TW
