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Stock market is a place, where shares of different companies are traded. It is a collection of buyers’ and sellers’ stocks. In this digital era, analysis and prediction in the stock market have gained an essential role in shaping today's economy. Stock market analysis can be either fundamental or technical. Technical analysis can be performed either with technical indicators or through machine learning techniques. In this paper, we report a system that uses a Reinforcement Learning (RL) network and market sentiments to make decisions about stock market trading. The system uses sentiment analysis on daily market news to spot trends in stock prices. The sentiment analysis module generates a unified score as a measure of the daily news about sentiments. This score is then fed into the RL module as one of its inputs. The RL section gives decisions in the form of three actions: buy, sell, or hold. The objective is to maximize long-term future profits. We have used stock data of Apple from 2006 to 2016 to interpret how sentiments affect trading. The stock price of any company rises, when significant positive news become available in the public domain. Our results reveal the influence of market sentiments on forecasting of stock prices.

The study relies on an extensive dataset (≈1.86 million news headlines) to investigate the heterogeneity and predictive power of explicit sentiment signals (TextBlob, VADER, and FinBERT) and implied sentiment (VIX) for stock market trends. We find that news content predominantly consists of objective or neutral information, with only a small portion carrying subjective or emotive weight. There is a structural market bias toward upswings (bullish market states). Market behavior appears anticipatory rather than reactive: forward-looking implied sentiment captures a substantial share (≈45–50%) of the variation in stock returns. By contrast, sentiment scores, even when disaggregated into firm- and non-firm-specific subscores, lack robust predictive power. However, weekend and holiday sentiment contains modest yet valuable market signals. Algorithm-wise, Gradient Boosting Machine (GBM) stands out in both classification (bullish vs. bearish) and regression tasks. Neither FinBERT news sentiment, historical returns, nor implied volatility offer a consistently exploitable edge over market efficiency. Thus, our findings lend empirical support to both the weak-form and semi-strong forms of the Efficient Market Hypothesis. In the realm of exploitable trading strategies, markets remain an enigma against systematic alpha.

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.

The political news media play an important role in the successful working of democratic societies. In order to fulfill this role, a sufficient level of journalistic quality is required. Most Western societies rely on the market as means to assure this level of quality. This implies regulation of the media sector by competition law, which may take different attitudes towards market power. While it is undisputed that some aspects of competition between political news media firms yield beneficial social outcomes, empirical findings regarding the impact of changes in market power are less straightforward. In the present analysis, I aim to understand whether an increase in market power may lead to an increase in journalistic quality. To this end,I formally model a demand function for media outlets based on the empirically justified assumption that preferences for journalistic quality systematically differ among consumers according to their education. I refer to this finding as consumption capital in a wide sense. Using a model of monopolistic competition, I find that, if consumption capital is sufficiently high, an increase in market power is associated with an increase in journalistic quality.

Future revenue streams for journalism are said not to lie in breaking news, but in specialist journalism that can engender income to sustain news production. A case study of the Norwegian TV 2 News Channel, however, shows that its profit-making features lie not in its content but in its mode of distribution. The added value of the channel to DTT subscription packages is as much due to TV 2’s market power and news brand value as to the news channel concept itself. This article analyses the function of the news channel in today’s competitive journalistic landscape from the perspective of news sociology and media economy, presenting a quantitative content analysis of the news output of TV 2 News Channel, qualitative interviews with TV 2 news editors, and analysis of key strategy documents of the organization.

This paper provides evidence on how stock market index reacts to releases of market-relevant information by five Middle-eastern and North African country budget and general election results. After estimating the ARMA (1, 2) estimator using daily stock returns over a recent five-year period, it was found that the market price effect over is a 20-day test window. The stock price adjustment to national annual budget announcement is significant, and the speed of adjustment is around two days to announcement. The national general election news attracts a faster adjustment time in all five countries tested. These findings of macro level market price effects from two key events are new to the literature.

Advertising imperfectly translates viewer preferences into demand for programming, and evaluating the quality of news products is difficult for consumers. Consequently the ability of market forces to supply high quality news is a subject of continuing debate. This paper offers new evidence on the supply of news by examining the investments by television stations in weather coverage. Weather forecasts meet the classic economic definition of a public good, yet television stations across the U.S. undertake extensive efforts to provide viewers with weather forecasts. Stations in markets with a higher incidence of severe weather, particularly a higher tornado rate, make significantly greater investments in their own Doppler weather radars and weathercasters certified by the American Meteorological Society. Since television weather can help save lives during severe weather, the supply of TV weather coverage is at least approximately efficient.

Los principales grupos de comunicación han creado empresas específicas para el mercado de Internet que, dentro de la organización, adoptan la forma de unidad de negocio, sumándose así a otras actividades, como la editorial o la audiovisual. El artículo propone la definición del modelo que adoptan estas empresas informativas, a partir del establecimiento de sus elementos diferenciales. La independencia en su organización, como una empresa más dentro del grupo, se contrarresta con su naturaleza dependiente del resto de medios. Esto obedece a la naturaleza convergente de Internet que, dentro del grupo de comunicación, viene a funcionar, no tanto como un medio más, sino como una nueva matriz digital en la que confluyen los distintos mercados informativos.

Sir, I am somewhat wary of taking issue with Terry Smith, chief executive of stockbrokers Collins Stewart, not least because of the way he is famously reported to have ended a past intellectual disagreement.

Germany's closely watched business climate Ifo index fell for a sixth consecutive month in November, confirming the fragility...