| 研究生: |
吳建璋 Wu, Chien-Chang |
|---|---|
| 論文名稱: |
點時成金!大數據因果分析法於貴金屬策略採購之研究 The Midas Touch! Hedge Strategies for Procurement of Precious Metals using Causal Analysis of Big Data |
| 指導教授: |
李昇暾
Li, Sheng-Tun |
| 學位類別: |
碩士 Master |
| 系所名稱: |
管理學院 - 高階管理碩士在職專班(EMBA) Executive Master of Business Administration (EMBA) |
| 論文出版年: | 2019 |
| 畢業學年度: | 107 |
| 語文別: | 中文 |
| 論文頁數: | 60 |
| 中文關鍵詞: | 貴金屬 、銀價 、道瓊工業平均指數 、美國十年期國債利率 、單根檢定 、因果檢定 |
| 外文關鍵詞: | Precious metal prices, Silver Price, ETF, Dow Jones Industrial Average (DJIA), 10-Year Treasury Rate, Unit root test, VAR (vector autoregression), Granger Causality Test, Google Trend |
| 相關次數: | 點閱:84 下載:2 |
| 分享至: |
| 查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
身處科技發達的年代,貴金屬不單只是拿來做美觀的飾品外,尚運用在工業科技上,尤以白銀因其導電性、延展性及抗腐蝕性佳,常被大量用於半導體及電子電氣產品上,成為市場不可或缺的原材,運用廣泛且大量。除此之外,亦因貴金屬被視為世界通用的交易媒介,保值能力強,成為許多投資客投資的產品選項,因此也影響著貴金屬交易市場上價格的漲跌。
本研究主要的目的,希望藉由各項大數據的資料庫中,找出影響貴金屬漲跌的相關要素,包含金融商品市場資訊和Google Trend關鍵字的網路聲量,先利用迴歸分析找出相關要素對貴金屬價格的影響,再針對相關要素執行單根檢定和因果檢定,看何種變數間存有因果關係,建立一套演算程式模型預估貴金屬的漲跌,協助以貴金屬為原材的產業之採購人員,預測貴金屬未來的價格走向,擬定適當的避險採購策略,降低材料成本,管控風險提高企業利潤。
實證結果發現,銀價、金價及白金價都與其自身交易基金ETF及美國十年期國債利率互為因果之關係,道瓊工業平均指數(Dow Jones Industrial Average,DJIA)和銀價、金價、銅價互為因果關係,美元匯率影響金價,同時油價影響白金價。此外本文亦探討Google Trend關鍵字Silver Prices、Gold Prices、Platinum Prices和Copper Prices的搜尋量和貴金屬價格之關聯性。
In the age of fast and advanced technology, precious metals are not only mere used as decorative objects but also used in industrial technology. Due to its outstanding conductivity, ductility and corrosion resistance, silver in particular is often used in semiconductors and electronic applications. It has become an indispensable material in the market. In addition, because precious metals are regarded as the universal trading medium, the intrinsic value of precious metals appeal greatly to investors and consumers. It has become one of the major investment components for investors, which affect the fluctuations of the precious metal market.
The main purpose of this study is to find out the factors affecting the up and down of precious metals by using unit root test and VAR model from the various big data, including the Google search volume and financial commodity trends to explore the causal relationship between precious metal prices and establish an algorithm program. The program model can assist purchasers of related industries with precious metals as raw materials, predicting future price trend of precious metals and formulating appropriate and formulating appropriate hedging procurement strategies for reducing material costs and increasing the enterprise profit.
The empirical results show that silver price, gold price and platinum price are mutually causal relationship with their own trading fund ETF and US 10 Year Treasury Rate. Dow Jones Industrial Average (DJIA) and silver price, gold price, and copper price are mutually causal. The exchange rate of the US dollar affects the price of gold, while the price of oil affects the price of platinum. In addition, this study also explores the relevance of the volume of Google search with keywords, Silver Prices, Gold Prices, Platinum Prices, and Copper Prices to the precious metal prices.
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校內:2024-06-10公開