政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/146293

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/146293

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政大機構典藏 > 商學院 > 財務管理學系 > 學位論文 > Item 140.119/146293

請使用永久網址來引用或連結此文件: https://nccur.lib.nccu.edu.tw/handle/140.119/146293

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:	2023-08-02 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), 838-851 Alam, 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), 43-51 Alexius, A. and D. Spång (2018). Stock prices and GDP in the long run. Journal of Applied Finance & Banking, 8(4), 107-126 Andries, 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, 227-238 Campbell, 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), 1509-31 Chen, Y., K. Rogoff, and B. Rossi (2010). Can exchange rates forecast commodity prices?. The Quarterly Journal of Economics, 125(3), 1145-94 Chen, S. (2014). Forecasting crude oil price movements with oil-sensitive stocks. Economic Inquiry, 52(2), 830-44 Chen, S. (2016). Commodity prices and related equity prices. The Canadian Journal of Economics, 49(3), 949-967 Diebold, 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), 1998-2006 Frankel, J.A. (2014). Effects of speculation and interest rates in a “carry trade” model of commodity prices. Journal of International Money and Finance, 42, 88-112 Jiang, 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), 660-671 Rossi, B. (2012). The changing relationship between commodity prices and equity prices in commodity exporting countries. IMF Economic Review, 60(4), 533-69 Wang, Q., and R. Balvers (2021). Determinants and predictability of commodity producer returns. Journal of Banking & Finance, 133, 278-287 Wei, P., and Y. Chang (2016). The Relationship between Equity and Commodity Markets during the Credit Crisis. Academia Economic Papers, 44(1), 93-125 Zhang, 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
顯示於類別:	[財務管理學系] 學位論文

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