FinTech初探：超漲與超跌股票在處置期間的股價反應與交易策略探討

Abstract

FinTech在近年來已經成為金融業在長期低利時代，期盼能找到下一個黃金世代的努力目標，根據Accenture的資料顯示2015年全球FinTech的投資金額已經達到222.6億美元，近兩年複合成長率超過1倍，但其中大數據、機器人顧問理財與自動化交易與等服務在國內證券業的應用目前尚較為貧乏，FinTech時代即將來臨，傳統券商能否有更好的商業模式為本研究所欲探知的問題。 本研究透過對現在證券業的觀察與創新發想，提出結合Robo-Advisors與Algotrade的運作概念而建構的Robo-AA平台，認為相較傳統券商有下列五項優點：1.能夠將客製化的顧問諮詢服務普及到更多的散戶。2.資料分析結果的共享程度高，可提高分析結果的運用效率。3.易於建立大量的個人交易策略庫。4.以大數據分析使用者的喜好代替人力推薦可降低人力成本。5.策略淘汰機制可以減少使用者在理財上花費的時間。 另外，本研究透過有關於處置股票的假設性提問實際模擬Robo-AA平台執行結果後，本研究發現1.如果將投資人提出的問題進行本質分析後，確實有助於提高顧問諮詢的深度。2.策略的淘汰機制除了減少投資人管理資產的時間外，在本文的實證模擬中，整體投資組合的平均報酬率也確實得到提升。

FinTech has become the next golden growth target in this prolong period of low interest rate. According to Accenture’s data, global investment in FinTech reached US$22.26B in 2015, with a compound annual growth rate exceeding 100% over the past two years. However, services such as big data, robo-advisor, and automated trading are not widely seen in the securities industry in this country. As the era of FinTech fast approaches, this study aims to examine the opportunity for traditional securities houses to design a better business model. With innovation and the observations on the current securities industry, this study proposes and constructs a Robo-AA platform by combining the operating concepts of Robo-Advisors and Algotrade. This platform compares favorabley to traditional securities houses in the following five areas: 1) it extends customized consulting services to more retail investors; 2) it increases the shareabiliity of analysis results and improves the utilization efficiency of these results; 3) it is much easier to establish a large databases of personal trading strategies; 4) it lowers the labor cost by using big data for analysis instead of relying on consultants for recommendations; and 5) it reduces the time required for users on financial management by introducing strategy elimination mechanisms. In addition, by using the Robo-AA platform to simulate empirically some hypothetical scenarios related to disposal of shares, this study has obtained the following results: 1)Analyzing the hypothetical scenarios with this platform can indeed improve the depth and quality of the consultation, and 2)Strategy elimination mechanisms can not only reduce the time spent on asset management by the investor, but also increase the average return of the overall investment portfolio, as demonstrated in the empirical simulation in this study.