Market News Research Articles

Market news co-moments and currency returns

We propose three co-moments of the market returns’ cash-flow, and discount-rate shocks and examine empirically an intertemporal capital asset pricing model using the co-moments on currency returns as well as stock returns during Dec. 1983 to Dec. 2017. We find that our proposed model has explanatory power for both currency and stock portfolios. We find several common sources of market risk in currency and stock returns that are reflected in market news. Our findings show that the co-moments are related to currency risk premiums and outperform the well-known liquidity, dollar and HML risk factors.

A földrajzi diverzifikáció szerepe a globális tőkepiacokon

This study illustrates the effectiveness of geographical diversification using capital market data. The paper uses historical capital market prices to show how the neglect of geographical diversification results in a deterioration in investment decision-making. In addition, the correlations between the capital markets of the former socialist countries are presented, which in many cases can be explained by real economic processes and geopolitical events. Quantitative, real-time financial and statistical data provided by capital markets can also be used to justify the dependence systems between countries and groups of countries, but the method can also be used in many cases to show the economic and geopolitical changes between countries. The study shows how concentrated the world’s stock markets are, which means that smaller capital markets cannot separate themselves from economic events, money and capital market news, or events of the largest ones.

Spillovers from the Slowdown in China on Financial and Energy Markets: An Application of VAR–VECH–TARCH Models

The 2008 global financial crisis provides us with a wide range of study fields on cross-asset contagion mechanisms in the US financial markets. After a decade of the so-called subprime crisis, the impact of market news on asset volatilities increased significantly. Consequently, return and volatility spillovers became the most extensive channel for spreading out the news generated in one market to the other ones, which made the financial markets inherit international risk factors as their own local risks. Moreover, as a result of the Chinese economy becoming the main driver of the global economy in the last decade, Chinese markets became more interconnected with developed markets which were followed by a “digital cold war” era via Twitter. In this study, we investigate the relationship between the US stock market, Chinese stock markets, rare earth markets and industrial metals, and mining products via three different models by utilizing VAR–VECH–TARCH models. According to our findings, bilateral spillover exists between US and Chinese stock markets. Cross-market spillovers show that there is a risk transmission channel between the industrial metals, rare earth, and Chinese and US stock markets due to China’s strengthening position in the global economy.

A study on stock price prediction system based on text mining method using LSTM and stock market news

The stock price reflects people's psychology, and factors affecting the entire stock market include economic growth rate, economic rate, interest rate, trade balance, exchange rate, and currency. The domestic stock market is heavily influenced by the stock index of the United States and neighboring countries on the previous day, and the representative stock indexes are the Dow index, NASDAQ, and S & P500. Recently, research on stock price analysis using stock news has been actively conducted, and research is underway to predict the future based on past time series data through artificial intelligence-based analysis. However, even if the stock market is hit for a short period of time by the forecasting system, the market will no longer move according to the short-term strategy, and it will have to change anew. Therefore, this model monitored Samsung Electronics' stock data and news information through text mining, and presented a predictable model by showing the analyzed results.

John J. Kiernan: Business Journalism Pioneer, 1845–1893

ABSTRACT John J. Kiernan was a little-known but important transitional figure in business journalism in the nineteenth century, one who operated as business journalism began to form its early identity. Kiernan’s news bureau employed and trained Charles Dow, Edward Jones, and Charles Bergstresser before they launched Dow Jones & Company, Inc. and the Wall Street Journal. Beyond this, Kiernan has been overlooked in the academic literature, even though he provided a leading financial news service after the Civil War. His story is instructive for modern audiences since he operated as a new technology—the telegraph—transformed business journalism. Evidence suggests Kiernan’s foray into New York state politics distracted him from his core business as the market for business news grew dramatically. The evolutionary theory of a firm helps explain the demise of Kiernan’s business as he lacked the organizational capabilities to sustain innovation at a critical juncture in journalism history.

التعرض للقضایا الاقتصادیة عبر وسائل الإعلام الرقمی وعلاقته بمستوى الثقة فی الأداء الاقتصادی لدى الجمهور المصری

هدف البحث إلى التعرف على مدى تعرض الجمهور للقضايا الاقتصادية عبر وسائل الإعلام الرقمي وعلاقته بمستوى الثقة في الأداء الاقتصادي لديهم، وتنتمي هذه الدراسة إلى الدراسات الوصفية، وتعتمد الدراسة على منهج المسح، وطبقت الدراسة على عينة قوامها (400) مفردة من أربع محافظات مصرية: (القاهرة، والسويس، والأسکندرية، والمنيا)، وتم الاعتماد على استمارة الاستقصاء کأداة أساسية للدراسة، وکانت أهم النتائج ما يلى: جاءت أبرز الخدمات الاقتصادية التي تقدمها وسائل الإعلام الرقمي من وجهة نظر الجمهور ما يلي: ظهر بمقدمة تلک الخدمات أنهاتنشر إعلانات المناقصات، ثم تقدم ملفات ومعلومات اقتصادية متخصصة، تنشر أخبار قطاع البنوک، ثم تنشر أخبار قطاع شرکات التحويل العقاري، تقدم تغطية مستمرة للسلع والخدمات الرئيسة، ثم تقوم بتغطية المؤتمرات الاقتصادية، بنشر أخبار البورصة، وجاءت أهم مؤشرات الأداء الاقتصادي التي تعرف عليها الجمهور عينة الدراسة من خلال وسائل الإعلام الرقمي ما يلي: جاء تحرر سعر الصرف، انخفاض الواردات، ثم انخفاض معدل البطالة، ارتفاع الصادرات، ثم زيادة الاحتياطات الدولية من النقد الأجنبي، يليها تراجع معدل التضخم السنوي، ثم ارتفاع تدفقات النقد الأجنبي، وأخيرا جاء انخفاض أسعار الفائدة، کما لا يوجد فرق دال إحصائيا بين متوسطات درجات الذکور ومتوسطات درجات الإناث على مقياس تناول وسائل الإعلام الرقمي للأداء الاقتصادي. بينما توجد فروق ذات دلالة إحصائية بين متوسطات درجات المبحوثين على مقياس تناول وسائل الإعلام الرقمي للأداء الاقتصادي تبعا لاختلاف المحافظة (القاهرة- الأسکندرية- المنيا- السويس). Exposure to economic issues via digital media and its relationship The level of confidence of Egyptian public towards economic performance The research sought to determine public's exposure to economic issues through digital media and its relationship to level of confidence in their economic performance. This study belongs to descriptive studies, and study relies on survey methodology. The study was applied to a sample of (400) respondents from four Egyptian governorates (Cairo, Suez, Alexandria, and Minya). The survey form was used as an essential tool for study.The most important results conclude as following: -The most prominent economic services provided by digital media from public’s point of view, following came: introduction of those services appeared that it “publishes tender announcements”, then “provides specialized economic files and information” followed by “publishes news of banking sector” then “publishes news of real estate conversion companies sector It is followed by “continuous coverage of main goods and services” and then “it covers economic conferences” followed by “the exchange of stock market news”.-The most important indicators of economic performance that public became familiar with study sample came through digital media. The following came: “Liberalization of exchange rate” followed by “low imports” then “low unemployment rate” followed by “higher exports” and then “increased international reserves of foreign exchange” Followed by the decline in annual inflation rate and then the recent rise in foreign exchange flows and last one low interest rates. - There are no statistically significant differences between mean scores of males and mean scores of females on scale of digital media intake for economic performance. -There are statistically significant differences between mean scores of respondents on scale of digital media intake of economic performance according to difference in governorate (Cairo - Alexandria - Minya - Suez).

Targeted Sentiments and Hierarchical Events based Learning Model for Stock Market Forecasting from Multi-Source Data

Stock market price movement forecast from multi-source data has gained massive interest in recent years. Studies were focussed on extracting the events and sentiments from different source data and employ them in learning the stock price movement patterns. This approach provided accurate and highly reliable forecasting as it involves multiple stock price indicators. However, some aspects of sentiment analysis and event extraction increase the training time and computation complexity in big data stock analysis. To overcome these issues, the hierarchical event extraction and the target dependent sentiment analysis are performed in this paper to improve the learning rate stock price movement patterns. In this paper, the events are hierarchically extracted from news articles using Deep Restricted Boltzmann Machine (DRBM). The target based sentiments from the tweets are detected using Improved Extreme Learning machine (IELM) whose parameters are optimally selected using Spotted Hyena Optimizer (SHO). The stock indicators obtained from these two processes are used in the learning process performed using Tolerant Flexible Multi-Agent Deep Reinforcement Learning (TFMA-DRL) model for analysing the stock patterns and forecasting the future stock trends. The forecasting results obtained by using the TFMA-DRL model by combining the stock indicators of targeted sentiments and hierarchical events are trustworthy and reliable. Evaluations are performed using three datasets collected for 12 months period from three sources of Twitter, Market News and Stock exchange. Results highlighted that the proposed stock forecasting model achieved 90% accuracy with minimum training time.

Time scarcity and the market for news

We develop a theory of news coverage in environments of information abundance. Time-constrained consumers browse through news items across competing outlets. They choose which outlets to access and which stories to read or skip, thus indirectly deciding how much time to spend on a given outlet. Firms decide on rankings of news items that maximize their profits. We show that even when readers (or television viewers) and firms are rational and unbiased, they spend more time on the news than they would like and not necessarily on the topics they prefer. In particular, relevant news items may be crowded out. We then study how reader-efficient standards can be restored, and derive implications on diverse aspects of new and traditional media. These include tabloidization and polarization of the news, and other aspects relevant for the political economy of the media, including political knowledge gaps and voter turnout.

Online News and Advertising: What Role for Competition Law?

This paper examines the effects on competition, freedom of speech and democracy as a whole, of the use of behavioral targeting in the online news sector, and the institutional alternatives available to tackle them. It also relies on new empirical research on behavioral tracking in the online news sector. By revealing the network of parties involved in the process and the users’ data they share, this research demonstrates the central role of social platforms in shaping demand and the different levels of competition existing between ad networks, publishers and newspapers. Accordingly, the paper begins by mapping out the relationships between advertisers, publishers, data aggregators and other third parties. It then considers the different dimensions of competition in the collection and elaboration of the data needed to perform behavioral targeting, therefore also discussing whether competition law intervention would be justified. The paper also considers the effects of digital platforms and targeting on the quality of news reporting, on the diversity of information disseminated and on democracy as connected to the competitive dynamics established in the market. Targeted advertisement and tailored web-pages are part of a new type of behavioral targeting hinging on the elaboration of data obtained from the digital identities of the users. In the market for news, information (and ultimately ideas) the creation of a tailored digital environment may bring about not only economic effects but also distortions of the democratic process. In Part I, this paper presents the mechanisms through which behavioral targeting is made possible on the internet in particular through audience targeting. Part II describes the structure of this industry and examines the characteristics of ‘algorithmic curation’. It also reports the result of the empirical analysis performed by recording all tracking cookies on a selection of 100 different news websites and examines the (potential) competitive issues existing between publishers, ad networks and newspapers. Part III explores the different legal tools available to tackle unfair trading practices and anti-competitive conducts in this market. Part IV discusses whether competition law may expand its reach beyond the pricing mechanisms, promoting the protection of constitutional rights and public interest concerns, such as the one to correct information, and compares the application of competition laws to the other institutional alternatives.

Journalism Expands in Spite of the Crisis: Digital-Native News Media in Spain

Digital-native news organizations have grown steadily in Spain since the mid-1990s and they have become established as a major force in the media market. Paradoxically, their biggest expansion coincided with the Great Recession (2008–2014). In fact, their numbers increased most during 2012–2013, when traditional media were cutting staff in response to the economic crisis, and unemployment rates in the media sector as a whole hit their peak. However, these digital-native news startups have yet to prove their sustainability and stability. This study uses our own database of 3,862 native and non-native digital news outlets in Spain and the Reuters Institute Digital News Report to analyze a number of characteristics of these media, such as the percentage that have gone inactive, the relative popularity of legacy brands vs. digital natives, multi-platform synergies, content subject matter, geographical location, ownership, and funding sources. Based on these quantitative parameters, this study reviews the structural strengths and weaknesses of digital-native media in the Spanish news market. Taking into account these findings, we conclude that the surge in digital-native news media observed in Spain during the Great Recession followed the pattern of creative destruction described by several economists.

Globalizing the Thirty Years War: Early German Newspapers and their Geopolitical Perspective on the Atlantic World*

Abstract At the height of the Thirty Years War, news from South America, West Africa and the Caribbean was widespread and quickly distributed in the central European peripheries of the early modern Atlantic world. Despite the German retreat from sixteenth-century colonial experiments, overseas reports sometimes appeared in remote southern German towns before they were printed in Spain or the Low Countries. This article explains the vivid German interest in Atlantic news and examines how correspondents designed their overseas reports for a specifically German news market by connecting them to the European political and military situation, using a rhetorical frame of global conflict. While the domestic importance of American news was sometimes overstated by German newsmakers, its dissemination helps us understand how a sense of global connectedness emerged in a new print genre and created a discourse that supported the spatial and temporal integration of events around the globe.

Content Provision in the Media Market with Single-Homing and Multi-Homing Consumers

AbstractIn this paper, we analyze the effects on content provision in the news market of single-homing (i.e. when readers consume news from just one outlet) and multi-homing (i.e. when readers can choose to consume news from competing outlets). Media firms compete on content provision and on advertising revenues. Readers have an ideal variety of content and experience a disutility from consuming news that differs from their ideal variety. In addition, readers have a preference for single-homing and for multi-homing. In this set-up, we show that media firms only diversify content with single-homing, but not with multi-homing. The reason for this is that competition for readers and advertising is lower under multi-homing than under single-homing, since multi-homing readers consume from all media outlets. We derive the consequences of single-homing and multi-homing for profits, consumer surplus and social welfare. We also discuss the implications of our results for the current debate in the media market related with social media and echo chambers.

¿Puede un factor réplica del crecimiento económico futuro (PIB) explicar los rendimientos de los activos financieros cotizados en la bolsa española?

El objetivo de este trabajo es analizar si un factor con capacidad predictiva sobre el crecimiento económico futuro, captura los rendimientos de los activos cotizados en la bolsa española. A su vez, se analiza la posible interpretación racional económica de los factores de Fama y French y momentum, como variables con información sobre dicho crecimiento económico futuro. Se cuantifican estos efectos para las etapas de crisis (económica: 1993-1997 y financiera: 2008-2011) y de expansión económica (1998-2007). Los resultados subrayan la relevancia y capacidad explicativa de este factor predictivo pero se encuentra una interpretación económica débil de los factores tamaño y ratio book-to-market, a partir de este factor que recoge las noticias del mercado sobre el crecimiento futuro del PIB. El factor de negociación momentum aporta un impacto económico prácticamente nulo.

Stock Market Forecasting from Multi-Source Data using Tolerance Based Multi-Agent Deep Reinforcement Learning

Analyzing and forecasting the future trends in stock market is challenging due to the ever increasing size of stock data. Modern techniques extract the stock indicators from the web data to forecast the stock movements. However, most previous studies were based on single source of data for extracting these indicators. This might not be effective in obtaining all the possible diverse factors that influence the market movements. Multi-source data has been rarely applied for stock prediction and even those techniques have limitations in handling larger data. In an attempt to utilize multi-source data more effectively for extracting stock indicators and improve the forecasting accuracy of stock movements, this paper developed a stock market forecasting model using Tolerance based Multi-Agent Deep Reinforcement Learning (TMA-DRL) model. The TMA-DRL model effectively combines the quantitative stock data with the indicators i.e. the events extracted from news data and sentiments extracted from tweets. This forecasting model utilizes Random forests to extract the twitter opinions and Restricted Boltzmann Machine (RBM) for event extraction from news data. Combining these indicators, the TMA-DRL model leads to improved data learning and provides highly accurate prediction of future stock trends. Datasets for evaluation were collected from three sources namely Twitter, Market News and Stock exchange, for 12 months period. Evaluation results illustrate the effectiveness of the proposed TMA-DRL stock market forecasting model which makes predictions with high accuracy and less time complexity.

Sustainability ratings and corporate control: Debacle of shareholder over stakeholder theory

Corporate sustainability rating is frequently observed by different stakeholders, thereby finding interest in academic studies as well. Shareholders of sustainable-companies respond to different types of stock market news, be it financial or non-financial news. Announcements relating to ratings obtained by sustainability-compliant businesses appear to create anticipation in the mind of the investor. If these announcements are viewed by investors with interest, then it can have a greater implication for corporate governance and control and the corporate leaders can find a clear path to resolve the much debated “shareholder” versus “stakeholder” view in decision-making. This paper aims to explain whether or not the declaration of sustainability ratings contributes to the stock market reaction in emerging markets such as India. Short-run event analysis was carried out on a set of selected BSE listed companies following sustainable practice (2017-2019) and the entire data set was split into categories of the upgrade, downgrade, no change, and no ratings. The study results show that the announcement of sustainability ratings is not regarded by investors with a great deal of interest and there is inherent indifference to such news in the stock market. These findings are relevant for stock exchanges, investors, and corporate control as it raises a serious issue of rethinking stakeholder awareness levels, which in an emerging economy such as India currently seem to be in a nascent stage. In order to meet the stakeholders interested in the process of business becoming sustainable corporate leaders through proper governance should explore ways and means to approach sustainability in a more systematic way

Выделение глобального стохастического тренда из несинхронных наблюдений волатильности финансовых индексов

In this paper, the Kalman linear filter method is used to decompose non-synchronous observations of the realized volatility of financial indices (NIKKEI 225, FTSE 100, S&P 500) into unobservable global and local components. It is shown that the volatility of the New York S&P 500 index is a global component, while the Tokyo NIKKEI 225 index, on the contrary, is more sensible to the local news. It is shown that the largest contribution to the global component comes from the observation interval from the closing of the London Exchange to the closing of the exchange in New York (16:30 and 21:00 UTC, respectively). Starting from about 2012–2014, the contribution to the volatility of the global news market is growing from the interval from closing the exchange in New York to closing the exchange in Tokyo (from 21:00 to 6:00 UTC). This can be attributed to the recently increasing influence of the economies of Asian countries (China, Japan, Korea) on the world economy.

Book PR: do readers influence on the communication of publishing company?

The impact of readers as target audiences of publishing houses in Ukraine on PR communication is not clearly understood. The goal of this research is to examine the role of readers in the communication process between publishing houses and customers. The readers become an important source of information about the events of the book publishing market and book novelties. The article shows the results of the poll of visitors of the largest book festivals in Ukraine – Book Arsenal Festival in Kyiv and Book Forum in Lviv for 2017–2019. These respondents (200 interviews per event) are not only the main consumers of book products publishing houses, but also they are the source of information about new books and activities of Ukrainian publishing houses themselves. According to the results of the poll, visitors of book fairs pay attention to the advice of their colleagues and friends, which are an important source of information about the events of the book publishing market and book novelties. Almost 50% of respondents create and distribute user-generated content about the events of the book publishing market. This activity is explained by the lack of information about the book market news of more than half of visitors. The results of the research confirm that readers are important publishing communications subjects, consumers are active advocates of the publisher’s brand, friends and colleagues actively create the content about the events of the book publishing market in Ukraine.

All the News That’s Fit to Click: The Economics of Clickbait Media

The news media industry has changed as the internet and social media have matured and become integral to modern life. I describe these changes through a theoretical analysis of the economic structure of the industry and explore the implications for scholars of online media and politics. The crux of my argument is that social media simultaneously serves as a distribution platform and reputation builder, as social recommendations take the place of expensive investments in high-quality journalism. This development rendered crucial portions of previous models of the market for news inaccurate due to the declining importance of firm reputation. This mechanism interacts with the massive heterogeneity in digital literacy and growing animosity toward the news media among conservatives to create “credibility cascades,” which I argue are a necessary condition for Fake News to flourish.

Artificial intelligence, news sentiment, and property market liquidity

PurposeThe purpose of this paper is to use a text-based sentiment indicator to explain variations in direct property market liquidity in the USA.Design/methodology/approachBy means of an artificial neural network, market sentiment is extracted from 66,070 US real estate market news articles from the S&P Global Market Intelligence database. For training of the network, a distant supervision approach utilizing 17,822 labeled investment ideas from the crowd-sourced investment advisory platform Seeking Alpha is applied.FindingsAccording to the results of autoregressive distributed lag models including contemporary and lagged sentiment as independent variables, the derived textual sentiment indicator is not only significantly linked to the depth and resilience dimensions of market liquidity (proxied by Amihud’s (2002) price impact measure), but also to the breadth dimension (proxied by transaction volume).Practical implicationsThese results suggest an intertemporal effect of sentiment on liquidity for the direct property market. Market participants should account for this effect in terms of their investment decisions, and also when assessing and pricing liquidity risk.Originality/valueThis paper not only extends the literature on text-based sentiment indicators in real estate, but is also the first to apply artificial intelligence for sentiment extraction from news articles in a market liquidity setting.

Post-earnings announcement drift and parameter uncertainty: evidence from industry and market news

Post-earnings announcement drift (PEAD), one of the most prominent and robust return anomalies, is often attributed to investor naivete or irrationality. A competing explanation is parameter uncertainty, which posits that PEAD may occur as rational investors encounter parameter uncertainty and must learn about the true values of a firm’s pricing parameters over time. This study extends the parameter uncertainty explanation for PEAD and hypothesizes that industry or market news arriving during the drift period affects drift strength. Consistent with our hypothesis, we find that the prices of high surprise firms show stronger responses to industry/market news in the drift period. Hence, the drift becomes stronger (weaker or reversed) when drift-period industry/market news agrees (disagrees) with a firm’s prior earnings news. The evidence helps to distinguish the parameter uncertainty theory from competing behavioral explanations based on investor naivete or irrational biases, a task previous studies find difficult. Overall, our findings indicate that asset pricing anomalies need not imply investor irrationality—anomalies could arise from rational investors learning about pricing parameters over time.