Introduction: Technology, Finance, and Trade in Emerging Markets

Kim, Young Jun; Cin, Beom Cheol; Cho, Kwanghee; Yi, Junesuh

doi:10.1080/1540496x.2015.1061385

Cited by 3 publications

(3 citation statements)

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“…Furthermore, the impact that puts on a predicted P/BV ratio can be explained. The results show that with the adoption of technology, investor's decision-making has been influenced by several technology indices [30], which leads to the improvement of prediction accuracy as well as the reduction of the room of arbitrage. Therefore, the traded prices of stocks will become closer and closer to the intrinsic value of assets and will be in accordance with the efficient market hypothesis.…”

Section: Results Analysis With the Lda Modelmentioning

confidence: 99%

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An Investigation on Factors Affecting Stock Valuation Using Text Mining for Automated Trading

et al. 2019

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Predicted price-to-book value ratios (P/BV) are widely used for the valuation of listed common stocks. However, with the application of automated trading system (ATS), the existing indicators that are applied in the method are losing their effectiveness in the Chinese market. Combining qualitative research with the text mining method, this study explores and validates those ignored factors to improve the accuracy of the stock valuation. On the basis of the principal of the existing valuation method, we clarify the scope of the factors that affects the P/BV ratio prediction. Through semi-structured interviews that are designed with six first-level factors which are taken from the literature, we then excavate some second-level factors. After that, with three corpuses including samples form Sina.com.cn, Xueqiu.com, and CSDN.net, four first-level factors and thirteen second-level factors have been verified step by step through the Latent Dirichlet Allocation (LDA) model. In the process, two other new factors and three sub-factors are also found. Furthermore, based on the factor correlation that was found in a data analysis, a factor relationship model was built. The results can be used in a stock valuation in future work as the basis of the indicator system for the prediction of P/BV ratio.

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Section: Results Analysis With the Lda Modelmentioning

confidence: 99%

“…The technology factor has penetrated throughout the industry. It refers to the high-tech, for example, the data structures and algorithms [16], which is applied in the construction of automated trading systems and the design of automated trading strategies [30].…”

Section: Valuation Factorsmentioning

confidence: 99%

An Investigation on Factors Affecting Stock Valuation Using Text Mining for Automated Trading

et al. 2019

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“…Technology, which is an automated trading agent factor, has penetrated throughout all sorts of industries including trading [19]. Advanced technology can improve firm performance to a great extent.…”

Section: Evaluation Factors For the Object Of Atsmentioning

confidence: 99%

Exploring Evaluation Factors and Framework for the Object of Automated Trading System

Huang¹,

Cheng²,

Hou³

et al. 2019

Proceedings of the Annual Hawaii International Conference on System Sciences

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Automated trading system (ATS) is a computer program that combines different trading rules to find optimal trading opportunities. The objects of ATS, which are financial assets, need evaluation because that is of great significance for stakeholders and market orders. From the perspectives of dealers, agents, external environment, and objects themselves, this study explored factors in evaluating and choosing the object of ATS. Based on design science research (DSR), we presented a preliminary evaluation framework and conducted semi-structured interviews with twelve trading participants engaged in different occupations. By analyzing the data collected, we validated eight factors from literatures and found four new factors and fifty-four sub-factors. Additionally, this paper developed a relationship model of factors. The results could be used in future work to explore and validate more evaluation factors by using data mining.

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Financial Technology: Review of Trends, Approaches and Management

et al. 2020

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Technological innovation and digitization have posed a challenge to the financial sector globally. Fintech is the term used to designate the application of new technologies to financial services. The aim of the study is to analyse this research subject worldwide during the period 1975–2019. To this end, bibliometric techniques were applied to 2012 articles, obtaining findings of the productivity of scientific research, of the main thematic axes and their evolution. Scientific activity increased, mainly in the past decade, with 45% of publications. The main thematic areas were Business, Management and Accounting, Engineering, Social Sciences and Computer Science. Seven research lines were identified, aimed at analysing the aspects financial, economic, technology transfer, investment, innovation, partnerships and institutions and commercial. Future research lines should develop analyses on banking, financial services trade, territorial development, legal, management, research methodologies and the sustainability of financial technologies. It was verified that there is a growing and dynamic interest in scientific activity on financial technologies at an international level. The findings obtained are a complement to the knowledge of financial technologies and allow the relationship between science and technology to be established, and to inform the decision-making process.

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Introduction: Technology, Finance, and Trade in Emerging Markets

Cited by 3 publications

References 0 publications

An Investigation on Factors Affecting Stock Valuation Using Text Mining for Automated Trading

An Investigation on Factors Affecting Stock Valuation Using Text Mining for Automated Trading

Exploring Evaluation Factors and Framework for the Object of Automated Trading System

Financial Technology: Review of Trends, Approaches and Management

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