Textual analysis and machine leaning: Crack unstructured data in finance and accounting

Li, Guo; Shi, Feng; Tu, Jun

doi:10.1016/j.jfds.2017.02.001

Cited by 83 publications

(26 citation statements)

References 20 publications

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“…It is worth noting that in absence of any statistical assumption on the distribution of this error term, the previous equation would be simply a tautology and would be of no help in supporting the identification of the key parameters of the regression models presented in the next Section. Several studies employed textual analysis to better understand the narrative adopted in company reports [124][125][126][127][128][129][130][131]. In this respect, the analysis of tones (positive/negative/neutral) is particularly widespread, especially in terms of market's reaction [132][133][134][135][136][137][138][139][140].…”

Section: Data Collectionmentioning

confidence: 99%

Sustainability Disclosure in Integrated Reporting: Does It Matter to Investors? A Cheap Talk Approach

Camodeca

Almici

Sagliaschi³

2018

Sustainability

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The purpose of this study is to investigate the value-relevance of corporate sustainability disclosure through integrated reporting. Sustainability disclosure is subject to managers’ discretion. Besides, it is often hardly verifiable. In this respect, integrated reporting could provide the means for a verifiable disclosure, otherwise, in the jargon of game theory, it could be considered as a cheap talk. This paper investigates which of these hypotheses is most likely to occur in reality. In order to do this, a simple theoretical framework is introduced, where sustainability of corporate performances is modelled as a tail-risk for shareholders. Costless signaling games (cheap talk) and persuasion games are reviewed within this context, in order to derive competing theories of sustainability disclosure’s value relevance through integrated reporting. These alternative theories are tested empirically consistent with the theoretical framework presented, in order to identify key-parameters. In this respect, a systematic textual analysis (artificial intelligence) of integrated reports was employed as to build a synthetic measure of sustainability disclosure. The application of this methodology on a sample of European listed companies showed that sustainability disclosure through integrated reporting has no effect on market-valuations, confirming the null hypothesis of integrated reporting resulting in a cheap talk’s babbling equilibrium.

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Section: Data Collectionmentioning

confidence: 99%

Sustainability Disclosure in Integrated Reporting: Does It Matter to Investors? A Cheap Talk Approach

Camodeca

Almici

Sagliaschi³

2018

Sustainability

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“…The article Empirical Analysis of the Link between Politics and Stock Market Behavior investigates the impact of EPU on the U.S. stock market from two perspectives: domestic policy and international perspective [13]. Besides, the research method is text analysis, which further confirms the correlation between the stock market and politics.…”

Section: A Text Analysis In American Presidential Speechmentioning

confidence: 92%

Application of Textual Analysis in Economic Policy Uncertainty

Xu¹,

Hu²,

Tian³

2019

Proceedings of the Fourth International Conference on Economic and Business Management (FEBM 2019)

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After the financial crisis, in order to alleviate the attendant rising unemployment, inflation, balance of payments imbalances, and the economic downturn, the government has to consider more involvement in addressing market failures by designating economic policies. This paper mainly introduces the economic policy uncertainty and some economic problems resulted from it. This paper explores the feasibility of textual analysis in solving EPU problems by method of case study and points out the limitations in the application process. Through literature review, the limitations of text analysis in China have been found-high context culture and a large number of unrelated economic policy reports have become obstacles. Based on the methodology of EPU and text analysis, the cases of the United States and Tunisia were analyzed to confirm the role of text analysis in measuring EPU issues. Finally, the conclusion is drawn that China should refer to the above two cases and combine the national conditions to solve the EPU problem.

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“…Moreover, topics and interrelated sentiments are spontaneously take out from the texts in a message board using supervised machine learning techniques. This paper shows textual investigation and machine learning technique to a greater extent, widespread over time in recent times owing to the increasing need to handle lots of texts from firm specific news inflows and Securities and Exchange Commission filings, etc using Neural network [11].…”

Section: This Paper Determines How the Dow Jonesmentioning

confidence: 99%

“…The various forecasting models focused the various qualitative information such as historical quotes, financial verbs, sentimental values, firm specific news. The forecasting model [1,8,9] discussed the verbs in financial news, [2] referred five parts of speech textual representation, [3] referred the publication of press releases, [4] stated historical quotes, [5,6,[10][11][12][13][14] discussed sentimental value information, [7] referred financial indicators for the annual reports and model [11] referred firms specific news. Our forecasting model concentrates the most frequently occurring words in information technology related companies.…”

Section: Proposed Systemmentioning

confidence: 99%

Prediction of Stock Prices Using Unstructured and Semi-structured Qualitative Data – A Neural Network Approach

Rajakumar¹,

Jegatheesan²,

Chandy³

et al. 2019

IJIES

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As more interest by the people about stock markets is growing substantially bigger, the more their thinking is directed to a systematic method to predict stock prices that vary. There is an increasing appreciation that unstructured qualitative data contain awfully precious information, helpful for a variety of reason. It is this motivation that has fascinated awareness of researchers and specialized into the interesting and demanding area of stock market prediction using qualitative news and events. In this paper, a framework for stock price movement prediction using news, company newsletter and financial information was presented. Financial information and events were processed and multilayer feed forward network trained using back propagation was employed to empirically explore the intricate relationships between events and the stock market prices. Among the various industries we chose to focus on the Information Technology (IT) sector since it is most prevalent and applicable to the Indian markets. The stock prices and the relevant unstructured information for six IT companies were collected and filtered based on set of keywords. Our research has proven that the stock price can be accurately predicted from news articles by furnishing the empirical results that were obtained after training the multilayer neural networks.

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Textual analysis and machine leaning: Crack unstructured data in finance and accounting

Cited by 83 publications

References 20 publications

Sustainability Disclosure in Integrated Reporting: Does It Matter to Investors? A Cheap Talk Approach

Sustainability Disclosure in Integrated Reporting: Does It Matter to Investors? A Cheap Talk Approach

Application of Textual Analysis in Economic Policy Uncertainty

Prediction of Stock Prices Using Unstructured and Semi-structured Qualitative Data – A Neural Network Approach

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