News-Based Trading Strategies

Feuerriegel, Stefan; Prendinger, Helmut

doi:10.2139/ssrn.2580050

Cited by 7 publications

(11 citation statements)

References 69 publications

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“…Based on our findings, one can build algorithmic trading systems around our text-based prediction methodology, which are capable of executing potentially profitable trading strategies [60,22]. In this regard, text mining in particular has recently received great traction and is propelling the automated interpretation of the linguistic content in corporate disclosures [61].…”

Section: Business Implications For Financial Decision-making and Decimentioning

confidence: 94%

“…These approaches are used to forecast various indicators of interest. These include, for instance, nominal returns [17], abnormal returns [8], optimal trading decisions [22], and market volatility [23]. A recent contribution by [24] applied an ontology-based web mining framework to improve the accuracy of unemployment rate predictions in the US.…”

Section: Decision Support From Financial Newsmentioning

confidence: 99%

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Long-term stock index forecasting based on text mining of regulatory disclosures

Feuerriegel

Gordon

2018

Decision Support Systems

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Share valuations are known to adjust to new information entering the market, such as regulatory disclosures. We study whether the language of such news items can improve short-term and especially long-term (24 months) forecasts of stock indices.For this purpose, this work utilizes predictive models suited to high-dimensional data and specifically compares techniques for data-driven and knowledge-driven dimensionality reduction in order to avoid overfitting. Our experiments, based on 75,927 ad hoc announcements from 1996-2016, reveal the following results: in the long run, text-based models succeed in reducing forecast errors below baseline predictions from historic lags at a statistically significant level. Our research provides implications to business applications of decision-support in financial markets, especially given the growing prevalence of index ETFs (exchange traded funds). reflect publicly-available information. Based on this premise, one can expect price changes whenever new information enters the market. In practice, regulations ensure that stock-relevant information is revealed primarily via regulatory disclosures in order to provide equal access for all market participants. Such materials disclose, for instance, quarterly earnings, but also management changes, legal risks and other events deemed important [2]. Accordingly, financial disclosures present an alluring and potentially financially-rewarding means of forecasting changes in stock valuations [3].In this respect, corporate news conveys a broad spectrum of information concerning the past performance and current challenges of the business [4], as well as frequently hinting at the future outlook. Research has followed this reasoning and empirically quantified the impact of the narrative content on the subsequent stock market responses [cf. 5, 6, 7]. Moreover, researchers have also demonstrated the prognostic capability of financial disclosures with respect to individual stock market returns in the short term [e. g. 8, 9, 10]. Accordingly, news-based forecasting has received considerable traction and, as a result, various publications have evaluated different news datasets, forecasted indicator/markets, preprocessing operations from the field of natural language processing and forecasting algorithms.Here we refer to the literature, which provides a thorough overview [3].Forecasting the development of stock indices is highly demanded by multiple stakeholders in financial markets. The underlying reason is that households are investing their money no only in individual stocks, government bonds or savings accounts; rather, they increasingly prefer exchange-traded funds (ETFs). These ETFs replicate the movements of marketable securities, with stock indices being the most prominent example. As part of their benefits, ETFs are traded on stock exchanges but often with higher liquidity and lower fees. Hence, private investors demand for decision support in better understanding the development of markets, as well as for obtaining prognostic support. For ...

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Section: Business Implications For Financial Decision-making and Decimentioning

confidence: 94%

Section: Decision Support From Financial Newsmentioning

confidence: 99%

Long-term stock index forecasting based on text mining of regulatory disclosures

Feuerriegel

Gordon

2018

Decision Support Systems

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“…[9]. Internet networks are rising and increasing such radio, online newspapers, online magazine and TV as a preferred platform for advertisement [40].…”

Section: Table 1 -Definitions Of Scientist About Social Media In Commmentioning

confidence: 99%

Social Media Networks Use in Communication Analyses of Arabic Countries

Davidavičienė¹,

Chalfoun²

2018

MDT

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“…Alternatively, one can rely upon perception as conveyed by professional reports, such as news or industry reports, or public materials from the firms themselves (i. e. regulatory filings, CEO speeches, etc.). These can help in improving the performance of investments [15,16,17]. Moreover, internal use of language (e. g. from emails) reflects the structure and processes of organizations.…”

Section: Introductionmentioning

confidence: 99%

Business analytics for strategic management: Identifying and assessing corporate challenges via topic modeling

Pröllochs

Feuerriegel

2020

Information & Management

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Strategic management requires an assessment of a firm's internal and external environment. Our work extends the body of management tools (e.g. SWOT analysis or growth-share matrix) by proposing an automated text mining framework. Here we draw upon narrative materials from firms (e.g. financial disclosures) and perform topic modeling in order to identify the key issues faced by an organization. We then quantify the use of language along two dimensions: risk and optimism. This reveals a firm's strengths and weaknesses by identifying business units, activities and processes subject to risk, while also comparing it to competitors or the market.

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News-Based Trading Strategies

Cited by 7 publications

References 69 publications

Long-term stock index forecasting based on text mining of regulatory disclosures

Long-term stock index forecasting based on text mining of regulatory disclosures

Social Media Networks Use in Communication Analyses of Arabic Countries

Business analytics for strategic management: Identifying and assessing corporate challenges via topic modeling

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