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  • 學位論文

觀聲量,探股市!比特幣的網路聲量與市場價格對其概念股股價之關聯研究

Study on the Relations of the Social Network Volume of Bitcoin and Bitcoin Price to Taiwan Bitcoin Concept Stock Price

指導教授 : 金志聿

摘要


比特幣在金融市場的價值逐漸提高,帶動一波全民「挖礦」熱潮,形成以比特幣產業鏈為概念的比特幣概念股,過往研究指出比特幣價格波動和比特幣概念股股價具有連動關係,然而現今大量訊息於社群媒體流竄,投資人買賣股票的決策易受到網路訊息與大眾對該股票相關議題評價而影響,因此,本研究將進一步探討比特幣價格、比特幣網路聲量與其正負面情緒比對比特幣概念股之影響。 本研究蒐集2020年8月10日至2021年8月6日之比特幣網路聲量與其正負面情緒比、比特幣價格及比特幣概念股股價,利用時間序列分析中的向量自迴歸模型 (Vector Autoregression Model) 建立股價預測模型,透過Granger因果分析觀察是否有領先與落後關係存在於變數間,並利用衝擊反應函數與預測誤差異變數分解來檢視變數間的動態關係,最後以均方根誤差(Root-Mean-Squre Error)比較納入網路聲量後的複合模型,其預測誤差是否低於過去僅納入比特幣價格之單因子模型。本研究主要發現包含 (1)比特幣價格與網路聲量對概念股公司股價有影響,但依不同公司之結果存在差異; (2)挖礦效能相關產業之概念股公司,其公司股價易受到比特幣價格與比特幣網路聲量波動所影響;(3)公司規模較小的公司股價易受比特幣網路聲量波動而影響,規模較大的公司則不易受網路聲量波動影響;(4)納入比特幣網路聲量之複合模型對預測股價準確率優於過去僅比特幣價格之單因子模型。本研究為網路聲量對公司股價的影響提供不同視角,以延伸網路聲量於概念股股價預測的實際應用。

並列摘要


This study applies Vector Auto Regression (VAR) Model to construct a stock priceprediction model based on following collected data: Bitcoin price, Taiwan's bitcoin network volume, Bitcoin's positive/negative emotional ratio and Taiwan's bitcoin concept stock price. The data was collected from 10 Aug 2020 to 6 Aug 2021. The results show that: (1) The Bitcoin's price and network volume have different impacts on company’s concept stock price based on their share capital. (2) The stock prices of Bitcoin mining performance-related products suppliers are more easily to be affected by Bitcoin’s price and network volume fluctuation. (3) Those companies who are defined small and medium scale are easily to be affected by the volume of the Bitcoin network. (4) This study proposed a prediction model which accuracy is higher than the single-factor model in the past researches by adding bitcoin network volume into consideration. We offer a different perspective on the impact of network volume to company stock prices, and further application of network volume to predict stock price could be discussed.

參考文獻


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