This dataset contains news headlines relevant to key forex pairs: AUDUSD, EURCHF, EURUSD, GBPUSD, and USDJPY. The data was extracted from reputable platforms Forex Live and FXstreet over a period of 86 days, from January to May 2023. The dataset comprises 2,291 unique news headlines. Each headline includes an associated forex pair, timestamp, source, author, URL, and the corresponding article text. Data was collected using web scraping techniques executed via a custom service on a virtual machine. This service periodically retrieves the latest news for a specified forex pair (ticker) from each platform, parsing all available information. The collected data is then processed to extract details such as the article's timestamp, author, and URL. The URL is further used to retrieve the full text of each article. This data acquisition process repeats approximately every 15 minutes.

To ensure the reliability of the dataset, we manually annotated each headline for sentiment. Instead of solely focusing on the textual content, we ascertained sentiment based on the potential short-term impact of the headline on its corresponding forex pair. This method recognizes the currency market's acute sensitivity to economic news, which significantly influences many trading strategies. As such, this dataset could serve as an invaluable resource for fine-tuning sentiment analysis models in the financial realm.

We used three categories for annotation: 'positive', 'negative', and 'neutral', which correspond to bullish, bearish, and hold sentiments, respectively, for the forex pair linked to each headline. The following Table provides examples of annotated headlines along with brief explanations of the assigned sentiment.

Examples of Annotated Headlines Forex Pair Headline Sentiment Explanation GBPUSD Diminishing bets for a move to 12400 Neutral Lack of strong sentiment in either direction GBPUSD No reasons to dislike Cable in the very near term as long as the Dollar momentum remains soft Positive Positive sentiment towards GBPUSD (Cable) in the near term GBPUSD When are the UK jobs and how could they affect GBPUSD Neutral Poses a question and does not express a clear sentiment JPYUSD Appropriate to continue monetary easing to achieve 2% inflation target with wage growth Positive Monetary easing from Bank of Japan (BoJ) could lead to a weaker JPY in the short term due to increased money supply USDJPY Dollar rebounds despite US data. Yen gains amid lower yields Neutral Since both the USD and JPY are gaining, the effects on the USDJPY forex pair might offset each other USDJPY USDJPY to reach 124 by Q4 as the likelihood of a BoJ policy shift should accelerate Yen gains Negative USDJPY is expected to reach a lower value, with the USD losing value against the JPY AUDUSD RBA Governor Lowe’s Testimony High inflation is damaging and corrosive

Positive Reserve Bank of Australia (RBA) expresses concerns about inflation. Typically, central banks combat high inflation with higher interest rates, which could strengthen AUD. Moreover, the dataset includes two columns with the predicted sentiment class and score as predicted by the FinBERT model. Specifically, the FinBERT model outputs a set of probabilities for each sentiment class (positive, negative, and neutral), representing the model's confidence in associating the input headline with each sentiment category. These probabilities are used to determine the predicted class and a sentiment score for each headline. The sentiment score is computed by subtracting the negative class probability from the positive one.

About this Dataset

Techcrunch news dataset in csv format.

Category

Economic

Keywords

news dataset,news data

Row Count

5246

Price

$67.00

China boasts the fastest growing GDP of all developed nations. Neighboring regions will have the largest middle class in history. China is building transport infrastructure to take advantage. Companies that capture market share in this region will be the largest and best performing over the next decade.

Macro Tailwinds

1) China GDP is the fastest growing of any major country with expected 5-6% over the next decade. If businesses (Alibaba, Tencent, etc..) maintain flat market share, that alone will drive 5-6% over the next decade. This is already higher than JP Morgans expectation (from their 13f filings) that the US market will perform between -5% and +5% over this coming decade.

2) The Southeast Asia Region contains about 5 billion people. China is constructing the One Best One Road which will be completed by 2030. This will grant their businesses access to the fastest and largest growing middle class in human history. Over the next 10+ years this region will be home to the largest middle class in history, potentially over 10x that of North America and Europe, based on stock price in Google Sheets.

Increasing average Chinese income.

Chinese average income has more than doubled over the last decade. Having sustained the least economic damage from the virus, this trend is expected to continue. At this pace the average Chinese citizen salary will be at 50% of the average US by 2030 (with stock price in Excel provided by Finsheet via Finnhub Stock Api), with the difference being there are 4x more Chinese. Thus a market potential of almost 2x the US over the next decade.

The Southeast Asia Region now contains the largest total number of billionaires, this number is expected to increase at an increasing rate as the region continues to develop. Over the next 10 years the largest trading route ever assembled will be completed, and China will be the primary provider of goods to 5b+ people

2013 North America was home to the largest number of billionaires. This reversed with Asia over the following 5 years. This separation is expected to continue at an increasing rate. Why does this matter? Over the next 10 years the largest trading route ever assembled will be completed, and China will be the primary provider of goods to 5b+ people

Companies that can easily access all customers in the world will perform best. This is good news for Apple, Microsoft, and Disney. Disney stock price in Excel right now is $70. But not for Amazon or Google which at first may sound contrary as the expectation is that Amazon "will take over the world". However one cannot do that without first conquering China. Firms like Alibaba and Tencent will have easy access to the global infrastructure being built by China in an attempt to speed up and ease trade in that region. The following guide shows how to get stock price in Excel.

We will explore companies using a:

1) Past

2) Present (including financial statements)

3) Future

4) Story/Tailwind

Method to find investing ideas in these regions. The tailwind is currently largest in the Asia region with 6%+ GDP growth according to the latest SEC form 4 from Edgar Company Search. This is relevant as investments in this region have a greater margin of safety; investing in a company that maintains flat market share should increase about 6% per year as the market growth size is so significant. The next article I will explore Alibaba (NYSE: BABA), and why I recently purchased a large position during the recent Ant Financial Crisis.

Techsalerator's News Events Data for Cambodia: A Comprehensive Overview

Techsalerator's News Events Data for Cambodia provides an essential resource for businesses, researchers, and media organizations. This dataset compiles information on key news events across Cambodia, drawing from a diverse array of media sources, including news outlets, online publications, and social media platforms. It offers valuable insights for those interested in tracking trends, analyzing public sentiment, or monitoring industry-specific developments.

Key Data Fields - Event Date: Records the precise date of the news event, crucial for trend analysis over time or for businesses reacting to market changes. - Event Title: A concise headline describing the event, enabling users to quickly gauge and categorize news content based on relevance. - Source: Identifies the news outlet or platform reporting the event, helping users track credible sources and evaluate the event's reach and influence. - Location: Provides geographic details about where the event occurred within Cambodia, valuable for regional analysis or targeted marketing. - Event Description: Offers a detailed summary of the event, including key developments, participants, and potential impact, aiding in understanding the context and implications.

Top 5 News Categories in Cambodia - Politics: Covers major news on government decisions, political movements, elections, and policy changes affecting the national landscape. - Economy: Focuses on Cambodia’s economic indicators, trade activities, inflation rates, and corporate news impacting business and finance sectors. - Social Issues: Highlights news on public health, education, social protests, and other societal concerns driving public discourse. - Sports: Features events in popular sports, such as football and martial arts, attracting considerable attention and engagement. - Technology and Innovation: Reports on tech advancements, startups, and innovations in Cambodia’s evolving tech sector.

Top 5 News Sources in Cambodia - The Phnom Penh Post: One of Cambodia's leading English-language newspapers, offering comprehensive coverage of politics, economy, and social issues. - Cambodia Daily: A well-regarded source for news related to national affairs, business, and cultural events. - Fresh News: A prominent online news platform providing real-time updates on breaking news, sports, and entertainment. - Koh Santepheap Daily: A major Khmer-language newspaper known for its extensive reporting on current affairs and local issues. - VOD (Voice of Democracy): An independent news outlet focusing on in-depth coverage of politics, social issues, and investigative journalism.

Accessing Techsalerator’s News Events Data for Cambodia To access Techsalerator’s News Events Data for Cambodia, please contact info@techsalerator.com with your specific needs. We will provide a customized quote based on the data fields and records you require, with delivery available within 24 hours. Ongoing access options can also be discussed.

Included Data Fields - Event Date - Event Title - Source - Location - Event Description - Event Category (Politics, Economy, Sports, etc.) - Participants (if applicable) - Event Impact (Social, Economic, etc.)

Techsalerator’s dataset is a valuable tool for tracking significant events in Cambodia. It supports informed decision-making, whether for business strategy, market analysis, or academic research, offering a comprehensive view of the country’s news landscape.

The Gross Domestic Product (GDP) in the United States was worth 29184.89 billion US dollars in 2024, according to official data from the World Bank. The GDP value of the United States represents 27.49 percent of the world economy. This dataset provides - United States GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

There is substantial evidence that voters’ choices are shaped by assessments of the state of the economy and that these assessments, in turn, are influenced by the news. But how does the economic news track the welfare of different income groups in an era of rising inequality? Whose economy does the news cover? Drawing on a large new dataset of U.S. news content, we demonstrate that the tone of the economic news strongly and disproportionately tracks the fortunes of the richest households, with little sensitivity to income changes among the non-rich. Further, we present evidence that this pro-rich bias emerges not from pro-rich journalistic preferences but, rather, from the interaction of the media’s focus on economic aggregates with structural features of the relationship between economic growth and distribution. The findings yield a novel explanation of distributionally perverse electoral patterns and demonstrate how distributional biases in the economy condition economic accountability.

The economics news website Boursorama.com topped the ranking as the most visited online economics and legal newspaper as of July 2024 in France, with a total number of visits exceeding 41.62 million visits. The websites LesEchos.fr and Capital.fr came in second and third positions, with around 26 and 25 million visits respectively in France in July 2024.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

MSCI World: Reflecting Global Economic Trends or Inflated Valuations?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

This dataset is part of the Monash, UEA & UCR time series regression repository. http://tseregression.org/

The goal of this dataset is to predict sentiment score for news title. This dataset contains 83164 time series obtained from the News Popularity in Multiple Social Media Platforms dataset from the UCI repository. This is a large data set of news items and their respective social feedback on multiple platforms: Facebook, Google+ and LinkedIn. The collected data relates to a period of 8 months, between November 2015 and July 2016, accounting for about 100,000 news items on four different topics: economy, microsoft, obama and palestine. This data set is tailored for evaluative comparisons in predictive analytics tasks, although allowing for tasks in other research areas such as topic detection and tracking, sentiment analysis in short text, first story detection or news recommendation. The time series has 3 dimensions.

Please refer to https://archive.ics.uci.edu/ml/datasets/News+Popularity+in+Multiple+Social+Media+Platforms for more details

Citation request
Nuno Moniz and Luis Torgo (2018), Multi-Source Social Feedback of Online News Feeds, CoRR

The news: The present dataset consists of 1789 news articles from the British daily newspaper The Guardian extracted using the content endpoint of The Guardian Open Platform. The news articles were, at the time, all the news corresponding to the sections: business, politics, society and world news for the entire month of January of 2013 (for a total of 1689 news) and an extra set of news articles randomly selected from the period Febrary of 2013 to December of 2015 (100 news articles). The first set of 1689 news articles was used for training and the second set of 100 news articles was used for testing in two publications: * Maisonnave, M., Delbianco, F., Tohmé, F.A. and Maguitman, A.G., 2018, November. A Supervised Term-Weighting Method and its Application to Variable Extraction from Digital Media. In XIX Simposio Argentino de Inteligencia Artificial (ASAI)-JAIIO 47 (CABA, 2018). * Maisonnave, M., Delbianco, F., Tohmé, F.A. and Maguitman, A.G., 2019. A Flexible Supervised Term-Weighting Technique and its Application to Variable Extraction and Information Retrieval. Inteligencia Artificial, 22(63), pp.61-80. The labels: The entire dataset was manually classified into two possible categories: economically relevant and irrelevant. The labelling process was carried out by two experts in Economy working in collaboration. For each news article, the full text of the article was analyzed to determine the category. The format: There are two different versions for this dataset: the reduced and the full versions. The former consists of a CSV and a readme file. The CSV file has five columns: "Instance No.", "Title", "Web Publication Date", "web URL" and "Economically Relevant". This version is reduced in columns as it does not include the full article texts; however, it does include all the 1789 instances. Requesting the full dataset: To gain access to the full version of the dataset (which includes the body of the news articles), please send an email to mariano.maisonnave@cs.uns.edu.ar with a copy to openplatform@theguardian.com requesting authorization and making it clear that the data set will not be used for commercial purposes.

This data file contains news intensity measures for the UK and US, based on semantic fingerprints of the news articles from New York Times and the respective country. News articles in the following categories are used: Business Day, New York, U.S., World, Technology, Travel, Health, Real Estate, Science, Education, Automobiles, Your Money, Washington, Climate.

This dataset is about news. It has 1 row and is filtered where the keywords includes Education-Economic aspects-China. It features 10 columns including source, publication date, section, and news link.

Graph and download economic data for Equity Market Volatility Tracker: Macroeconomic News and Outlook: Business Investment And Sentiment (EMVMACROBUS) from Jan 1985 to May 2025 about volatility, uncertainty, equity, investment, business, and USA.

This dataset is about news. It has 1 row and is filtered where the keywords includes Economic assistance-Ghana. It features one column called news link.

Do files and simulated data for tables and figures in "Political Polarization in Financial News"

Dataset - Economic risks of climate change : an American prospectus in the news

News of topics of Econom & Finance, published by the Press Office of the Bilbao City Council.

This poll, conducted December 8-10, 2006, is part of a continuing series of monthly surveys that solicit public opinion on the presidency and on a range of other political and social issues. Respondents were asked whether they approved of the way President George W. Bush was handling the presidency and issues such as foreign policy and the economy. Respondents voiced their concerns about the most important problem facing the country, the condition of the national economy, their own household's financial security, and whether the country was moving in the right direction. A series of questions addressed respondents' feelings about the newly elected United States Congress, and whether the United States should intervene in other countries' affairs. Views were sought on the war with Iraq, whether the Iraqi government was strong enough to withstand pressure from the insurgents, and whether the United States government should solicit the help of neighboring countries in the Middle East in its efforts to create stability in Iraq. Other questions addressed the recommendations made by the Iraq Study Group commissioned by Congress, and whether the United States had a responsibility to make sure Iraq had a stable government before withdrawing its troops. Respondents were also asked about their own opportunities to succeed compared to those of their parents' generation, whether they expected their children to have better opportunities than they did, how often they experienced stress in their daily life, and how often this stress was caused by financial difficulties. Additional topics addressed holiday spending, retirement savings and investments, the real estate and stock markets, and whether respondents rented or owned their home. Demographic information includes sex, age, race, education level, household income, marital status, religious preference, type of residential area (e.g., urban or rural), political party affiliation, political philosophy, voter registration status and participation history, the presence of household members between the ages of 18 and 24, whether respondents had children under 18, and whether they considered themselves to be born-again Christians.

Dataset

This dataset was created by Himalaya Ashish

Contents

Leading Economic Index Guatemala increased 3.80 percent in April of 2025 over the same month in the previous year. This dataset provides - Guatemala Leading Economic Index- actual values, historical data, forecast, chart, statistics, economic calendar and news.