鐵礦砂作為全球主要的工業原料之一，其期貨市場的波動性對經濟具有重要影 響。本文旨在探討鐵礦砂期貨報酬率與情緒指標之間的相關性，特別是銅、銀、金、 鉑等金屬的情緒指標是否能夠預測鐵礦砂期貨價格。本研究利用 2019 年至 2023 年芝 加哥商品交易所的數據，分析 COVID-19 疫情前後不同金屬情緒指標對鐵礦砂期貨報 酬率的影響。研究結果表明，銅的情緒指標對鐵礦砂期貨價格有顯著的預測能力，而 銀、金和鉑的情緒指標則影響不顯著。透過對不同情緒組合的迴歸分析，本研究發 現，高情緒指標的投資表現優於低情緒指標的投資表現，尤其是在銅的情緒指標方 面。勝算比的迴歸分析進一步證實了這一點，銅的情緒指標顯著提升了模型的解釋 力。本文強調，利用機構投資人的情緒指標進行投資組合策略，可以在期貨市場中獲 得顯著的投資回報。銅的情緒指標作為預測工具，顯示出其在鐵礦砂期貨市場中的有 效性。此外，本文的研究方法包括對樣本資料的篩選和統計分析，使用了 Consensus Ins.公司的每週情緒指數，對銅、銀、金和鉑的情緒指標進行了詳細研究。總結來說， 本研究填補了鐵礦砂期貨市場中情緒指標預測效能的研究空白，證實了銅的情緒指標 對鐵礦砂期貨價格具有顯著預測能力，並指出情緒指標在期貨市場投資策略中的應用 價值。然而，本研究也指出需要更多的樣本數據和更長的研究期間來驗證結果的普遍 性，以期提高預測的可靠性和實用性。;Iron ore, as one of the world′s major industrial raw materials, significantly impacts the economy due to its market volatility. This study explores the correlation between iron ore futures returns and sentiment indicators, particularly whether the sentiment indicators of metals such as copper, silver, gold, and platinum can predict iron ore futures prices. Using data from the Chicago Mercantile Exchange from 2019 to 2023, this study analyzes the impact of different metal sentiment indicators on iron ore futures returns before and after the COVID-19 pandemic. The results show that copper′s sentiment indicator can significantly predict iron ore futures prices, while silver, gold, and platinum indicators do not. Regression analysis reveals that high sentiment indicators outperform low ones in investment performance, especially for copper. Further analysis confirms that copper′s sentiment indicator significantly improves the model′s explanatory power. This study highlights that using institutional investors′ sentiment indicators in investment strategies can yield significant returns in the futures market, with copper′s sentiment indicator proving particularly effective. The research includes data screening and statistical analysis using the weekly sentiment index from Consensus Ins. In summary, this study fills a research gap, confirming copper′s sentiment indicator as a significant predictor of iron ore futures prices and emphasizing the value of sentiment indicators in investment strategies. However, it also notes the need for more data and a longer research period to verify these results and enhance prediction reliability.
