FinFeedAPI provides equity market data covering over 11,000 symbols, featuring historical T+1 data with an unlimited loopback period. We deliver everything from detailed trade records and multiple levels of order book depth (Level 1-3) to crucial regulatory and system messages.

Our data is engineered for performance, featuring nano-second precision timestamps. This ensures a competitive edge for high-frequency trading by enabling fair, accurate, and auditable transaction sequencing, critical for regulatory compliance. Access comprehensive equity market intelligence directly through our robust API offerings.

Why FinFeedAPI?

Market Coverage & Data Depth: - Historical Data: T+1 data on 11K+ symbols with unlimited historical lookback. - Trade Feeds: Detailed trade records including timestamps, sizes, prices, and conditions (e.g., odd lot, intermarket sweep, extended hours). - Level 1 Quotes: Best bid/ask prices, sizes, and timestamps. - Level 2 Price Book: Market depth with multiple bid/ask prices and aggregate order sizes. - Level 3 Order Book: The complete order book detailing individual orders.

Essential Messages: - Admin Messages: Trading status, official open/close prices, auction states, short sale restrictions, retail liquidity indicators, security directory. - System Events: Exchange-level notifications for key trading session phases.

Precision & Reliability: - Nano-second Timestamps: Ensuring fair, accurate, and auditable transaction sequencing for HFT and compliance. - Institutional Trust: Relied upon by financial institutions for dependable equity market information.

Financial institutions and trading firms rely on FinFeedAPI for mission-critical equity market intelligence. We are committed to delivering clean, precise, and comprehensive data when it matters most. If you require dependable and granular stock market data, FinFeedAPI provides the actionable insights you need.

In 2024, 62 percent of adults in the United States invested in the stock market. This figure has remained steady over the last few years, and is still below the levels before the Great Recession, when it peaked in 2007 at 65 percent. What is the stock market? The stock market can be defined as a group of stock exchanges, where investors can buy shares in a publicly traded company. In more recent years, it is estimated an increasing number of Americans are using neobrokers, making stock trading more accessible to investors. Other investments A significant number of people think stocks and bonds are the safest investments, while others point to real estate, gold, bonds, or a savings account. Since witnessing the significant one-day losses in the stock market during the Financial Crisis, many investors were turning towards these alternatives in hopes for more stability, particularly for investments with longer maturities. This could explain the decrease in this statistic since 2007. Nevertheless, some speculators enjoy chasing the short-run fluctuations, and others see value in choosing particular stocks.

TagX is your trusted partner for stock market and financial data solutions. We specialize in delivering real-time and end-of-day data feeds that power software, trading algorithms, and risk management systems globally. Whether you're a financial institution, hedge fund, or individual investor, our reliable datasets provide essential insights into market trends, historical pricing, and key financial metrics.

TagX is committed to precision and reliability in stock market data. Our comprehensive datasets include critical information such as date, open/close/high/low prices, trading volume, EPS, P/E ratio, dividend yield, and more. Tailor your dataset to match your specific requirements, choosing from a wide range of parameters and coverage options across primary listings on NASDAQ, AMEX, NYSE, and ARCA exchanges.

Key Features of TagX Stock Market Data:

Custom Dataset Requests: Customize your data feed to focus on specific metrics and parameters crucial to your trading strategy.

Extensive Coverage: Access data from reputable exchanges and market participants, ensuring accuracy and completeness in your analyses.

Flexible Pricing Models: Choose pricing structures based on your selected parameters, offering cost-effective solutions tailored to your needs.

Why Choose TagX? Partner with TagX for precise, dependable, and customizable stock market data solutions. Whether you require real-time updates or end-of-day valuations, our datasets are designed to support informed decision-making and enhance your competitive edge in the financial markets. Trust TagX to deliver the data integrity and accuracy essential for maximizing your trading potential.

China's main stock market index, the SHANGHAI, rose to 3385 points on June 6, 2025, gaining 0.04% from the previous session. Over the past month, the index has climbed 1.28% and is up 10.95% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from China. China Shanghai Composite Stock Market Index - values, historical data, forecasts and news - updated on June of 2025.

Online Calendar Apps Market Outlook

The online calendar apps market size is witnessing substantial growth, with the global market valued at approximately USD 1.5 billion in 2023 and projected to reach USD 4.2 billion by 2032, reflecting a robust CAGR of 12.1% during the forecast period. This remarkable growth is driven by the increasing reliance on digital tools for personal and professional time management, along with the rising penetration of smartphones and internet connectivity worldwide.

One of the primary growth factors for the online calendar apps market is the accelerated digital transformation across various sectors. The shift towards remote work and virtual collaboration tools has significantly boosted the demand for efficient time management solutions. Online calendar apps serve as an essential tool for both individuals and enterprises to streamline schedules, set reminders, and coordinate tasks seamlessly. Moreover, the integration of artificial intelligence and machine learning capabilities into these apps to offer personalized suggestions and automate routine tasks is further enhancing their appeal and functionality.

Another significant growth factor is the increasing adoption of mobile devices and the rapid proliferation of internet access. With smartphones becoming ubiquitous and internet services more affordable, a larger segment of the global population is now able to utilize online calendar apps. This trend is particularly pronounced in emerging markets where mobile-first strategies are prevalent. Additionally, the growing focus on productivity and time management in both personal and professional spheres is driving the adoption of these applications.

The rise of hybrid work models, combining remote and on-site work, is also contributing to the market's growth. As organizations embrace flexible working arrangements, the need for efficient scheduling and coordination tools has become paramount. Online calendar apps facilitate smooth communication and collaboration among team members, regardless of their physical location. The trend towards digitization of traditional office tools and the increasing emphasis on work-life balance are further propelling the market.

From a regional perspective, North America holds a significant share of the online calendar apps market due to the high adoption rate of digital tools and the presence of major technology companies. The Asia Pacific region is expected to witness the highest growth rate, driven by the large population base, increasing smartphone penetration, and rising digital literacy. Europe also represents a substantial market share, supported by the widespread use of technology in personal and professional domains. The Latin America and Middle East & Africa regions are also experiencing gradual growth, motivated by improving internet infrastructure and growing awareness of digital productivity tools.

Type Analysis

The online calendar apps market can be segmented by type into personal and professional categories. Personal calendar apps cater to individual needs, helping users manage their daily schedules, appointments, and personal events. These apps are designed with user-friendly interfaces and features like reminders, to-do lists, and integration with other personal productivity tools. The demand for personal calendar apps is driven by the increasing need for efficient time management in daily life, as individuals seek to balance work, personal activities, and social commitments. The growing awareness of mental health and the importance of maintaining a balanced lifestyle also play a crucial role in this segment's growth.

Professional calendar apps, on the other hand, are tailored for business and corporate users. These applications offer advanced features such as team collaboration, project management, resource allocation, and integration with enterprise software like CRM and ERP systems. The professional segment is experiencing significant growth due to the rising adoption of remote and hybrid work models, which necessitate efficient scheduling and coordination tools. Enterprises are increasingly investing in professional calendar apps to enhance productivity, streamline workflows, and ensure effective communication among team members. The integration of AI-driven functionalities that offer predictive insights and automated scheduling is further boosting the appeal of professional calendar apps.

The personal and professional segments are both evolving with technological advancements. For instance, many personal calendar apps are now incorporat

While the global coronavirus (COVID-19) pandemic caused all major stock market indices to fall sharply in March 2020, both the extent of the decline at this time, and the shape of the subsequent recovery, have varied greatly. For example, on March 15, 2020, major European markets and traditional stocks in the United States had shed around 40 percent of their value compared to January 5, 2020. However, Asian markets and the NASDAQ Composite Index only shed around 20 to 25 percent of their value. A similar story can be seen with the post-coronavirus recovery. As of November 14, 2021 the NASDAQ composite index value was around 65 percent higher than in January 2020, while most other markets were only between 20 and 40 percent higher.

Why did the NASDAQ recover the quickest?

Based in New York City, the NASDAQ is famously considered a proxy for the technology industry as many of the world’s largest technology industries choose to list there. And it just so happens that technology was the sector to perform the best during the coronavirus pandemic. Accordingly, many of the largest companies who benefitted the most from the pandemic such as Amazon, PayPal and Netflix, are listed on the NADSAQ, helping it to recover the fastest of the major stock exchanges worldwide.

Which markets suffered the most?

The energy sector was the worst hit by the global COVID-19 pandemic. In particular, oil companies share prices suffered large declines over 2020 as demand for oil plummeted while workers found themselves no longer needing to commute, and the tourism industry ground to a halt. In addition, overall share prices in two major stock exchanges – the London Stock Exchange (as represented by the FTSE 100 index) and Hong Kong (as represented by the Hang Seng index) – have notably recovered slower than other major exchanges. However, in both these, the underlying issue behind the slower recovery likely has more to do with political events unrelated to the coronavirus than it does with the pandemic – namely Brexit and general political unrest, respectively.

Major Developments deliver immediate summaries and classifications of vital, market-moving corporate events – a news analysis and filtering tool designed to streamline your workflow. Leverage Major Developments (MajDev) data to conduct thorough research on particular subjects such as mergers, earnings reports, executive changes, and new products. Since 2000, we have gathered over 4 million developments, expanding by 3500 each week. Each event is tagged with the topic, relevance, significance, and the date/time of the announcement.

1. Overview

This dataset provides monthly stock price data for the MAG7 over the past 20 years (2004–2024). The data includes key financial metrics such as opening price, closing price, highest and lowest prices, trading volume, and percentage change. The dataset is valuable for financial analysis, stock trend forecasting, and portfolio optimization.

2. What is MAG7 ?

MAG7 refers to the seven largest and most influential technology companies in the U.S. stock market : - Microsoft (MSFT) - Apple (AAPL) - Google (Alphabet, GOOGL) - Amazon (AMZN) - Nvidia (NVDA) - Meta (META) - Tesla (TSLA)

These companies are known for their market dominance, technological innovation, and significant impact on global stock indices such as the S&P 500 and Nasdaq-100.

3. Dataset Details

The dataset consists of historical monthly stock prices of MAG7, retrieved from Investing.com. It provides an overview of how these stocks have performed over two decades, reflecting market trends, economic cycles, and technological shifts.

4. Columns Descriptions

• Date The recorded month and year (DD-MM-YYYY)
• Price The closing price of the stock at the end of the month
• Open The price at which the stock opened at the beginning of the month
• High The highest stock price recorded in the month
• Low The lowest stock price recorded in the month
• Vol. The total trading volume for the month
• Change % The percentage change in stock price compared to the previous month # 5. Data Source & Format The dataset was obtained from Investing.com and downloaded in CSV format. The data has been processed to ensure consistency and accuracy, with date formats standardized for time-series analysis. # 6. Potential Use Cases This dataset can be used for :
• 📈 Stock price trend analysis over 20 years
• 📊 Building financial models for long-term investing
• 🔎 Machine learning applications in stock market prediction
• 📉 Evaluating market volatility and economic impact on MAG7 stocks

7. Limitations & Considerations

• ⚠️ The dataset is limited to monthly data, meaning short-term price fluctuations are not captured.
• ⚠️ Trading volume (Vol.) may vary in availability due to differences in reporting.
• ⚠️ External factors such as stock splits, dividends, and market crashes are not explicitly noted but may impact historical trends.

This dataset includes various economic indicators such as stock market performance, inflation rates, GDP, interest rates, employment data, and housing index, all of which are crucial for understanding the state of the economy. By analysing this dataset, one can gain insights into the causes and effects of past recessions in the US, which can inform investment decisions and policy-making.

There are 20 columns and 343 rows spanning 1990-04 to 2022-10

The columns are:

1. Price: Price column refers to the S&P 500 lot price over the years. The S&P 500 is a stock market index that measures the performance of 500 large companies listed on stock exchanges in the United States. This variable represents the value of the S&P 500 index from 1980 to present. Industrial Production: This variable measures the output of industrial establishments in the manufacturing, mining, and utilities sectors. It reflects the overall health of the manufacturing industry, which is a key component of the US economy.

2. INDPRO: Industrial production measures the output of the manufacturing, mining, and utility sectors of the economy. It provides insights into the overall health of the economy, as a decline in industrial production can indicate a slowdown in economic activity. This data can be used by policymakers and investors to assess the state of the economy and make informed decisions.

3. CPI: CPI stands for Consumer Price Index, which measures the change in the prices of a basket of goods and services that consumers purchase. CPI inflation represents the rate at which the prices of goods and services in the economy are increasing.

4. Treasure Bill rate (3 month to 30 Years): Treasury bills (T-bills) are short-term debt securities issued by the US government. This variable represents the interest rates on T-bills with maturities ranging from 3 months to 30 years. It reflects the cost of borrowing money for the government and provides an indication of the overall level of interest rates in the economy.

5. GDP: GDP stands for Gross Domestic Product, which is the value of all goods and services produced in a country. This dataset is taking into account only the Nominal GDP values. Nominal GDP represents the total value of goods and services produced in the US economy without accounting for inflation.

6. Rate: The Federal Funds Rate is the interest rate at which depository institutions lend reserve balances to other depository institutions overnight. It is set by the Federal Reserve and is used as a tool to regulate the money supply in the economy.

7. BBK_Index: The BBKI are maintained and produced by the Indiana Business Research Center at the Kelley School of Business at Indiana University. The BBK Coincident and Leading Indexes and Monthly GDP Growth for the U.S. are constructed from a collapsed dynamic factor analysis of a panel of 490 monthly measures of real economic activity and quarterly real GDP growth. The BBK Leading Index is the leading subcomponent of the cycle measured in standard deviation units from trend real GDP growth.

8. Housing Index: This variable represents the value of the housing market in the US. It is calculated based on the prices of homes sold in the market and provides an indication of the overall health of the housing market.

9. Recession binary column: This variable is a binary indicator that takes a value of 1 when the US economy is in a recession and 0 otherwise. It is based on the official business cycle dates provided by the National Bureau of Economic Research.

The India B2B events market is experiencing robust growth, projected to reach $534.70 million in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 11.72% from 2025 to 2033. This expansion is driven by several key factors. Firstly, the increasing adoption of digital technologies is transforming the events landscape, with virtual and hybrid events gaining traction, complementing traditional physical events. Secondly, a burgeoning number of businesses across diverse sectors—including Food and Beverage, Public Sector Units (PSUs), Luxury, Banking, Financial Services and Insurance (BFSI), Fast-Moving Consumer Goods (FMCG), Retail, Healthcare, and Automotive—are recognizing the value of B2B events for networking, lead generation, and brand building. The rising disposable incomes and economic growth in India further fuel this market expansion. Furthermore, strategic partnerships and collaborations between event organizers and technology providers are enhancing event experiences, creating more engaging and efficient platforms for attendees. However, the market also faces certain challenges. Competition amongst numerous event management companies necessitates continuous innovation and differentiation. Economic downturns or unforeseen events (like pandemics) can significantly impact event participation and spending. Therefore, successful players must adapt swiftly to changing market conditions, embrace technological advancements, and offer highly targeted and valuable experiences to maintain market share. The market segmentation across platforms (physical and virtual) and end-user verticals allows for focused strategies, maximizing returns in specific niches and minimizing susceptibility to wider market fluctuations. Major players like Sapphire Connect, Mantra, Seventy EMG, and others are actively shaping the market through innovative offerings and strategic acquisitions. This report provides an in-depth analysis of the burgeoning India B2B events market, offering invaluable insights for businesses looking to capitalize on its immense growth potential. With a study period spanning 2019-2033, a base year of 2025, and a forecast period from 2025-2033, this report utilizes data from the historical period (2019-2024) to project future trends and market size in the millions. The report segments the market by platform (physical and virtual events), end-user verticals (Food and Beverage, PSU, Luxury, BFSI, FMCG, Retail, Healthcare, Automotive, and Others), and key players, providing a granular understanding of this dynamic sector. Recent developments include: In March 2024, by bringing together 3,500 exhibitors from across the entire value chain under one roof for the first time, the theme of Bharat Tex 2024 emphasized India’s capability to provide end-to-end textile solutions. Spread across nearly two million square feet and attracting 100,000 visitors, this huge event, staged in New Delhi, was organized by a consortium of 11 textile export promotion councils and sponsored by the country’s Ministry of Textile., In November 2023, a mega B2B food event was organized in Delhi. The mega food festival generated significant interest from foreign and Indian stakeholders, organized in collaboration with ten ministries of government, six commodities commissions, and 25 states. A total of 1208 exhibitors, 14 country pavilions, and significant participation by 715 foreign buyers, 218 domestic buyers, and 97 corporate executives were present at this event. The event brought together a broad range of platforms for highlighting the most recent developments in the food processing industry, covering an area of over 50,000 m2 across seven spaces. The event was attended by 14 delegations from the member states, seven of which were ministers. The distinguished participation of the Netherlands as a partner country and Japan as the focal country further enhanced the global appeal of this event.. Key drivers for this market are: Mobile e-commerce to be the fastest-growing retailing channel due to proliferation of mobile apps and convenience, Retailers develop mobile-friendly strategies to attract young and tech-savvy consumers. Potential restraints include: , Lack of Awareness Among Government Organizations About New Technologies. Notable trends are: Retail Sector to be the Largest End User.

Dhaka Stock Exchange Historical Data Overview This dataset contains historical technical data from the Dhaka Stock Exchange (DSE), primarily collected from the official DSE website and supplemented with other publicly available online sources. It is intended solely for informational and research purposes. While every effort has been made to ensure the accuracy and completeness of the data, some inconsistencies or errors may still exist. Users are advised to independently verify any critical information before use. Data Summary: This dataset provides historical trading data for over 700 listed companies on the Dhaka Stock Exchange (DSE), covering the period from January 1999 to April 2025. The dataset consists of 1,684,249 rows and 7 columns, including the following fields: Trading Code: Ticker symbol of the company Date: Trading date Open: Opening price High: Highest price during the day Low: Lowest price during the day Close: Closing price Volume: Total shares traded on that day Notable Findings: The dataset reflects significant market cycles, including bullish and bearish trends, over two decades. Includes major economic events, such as: 2008 global financial crisis impact on DSE The 2010–11 market crash in Bangladesh The effects of COVID-19 (2020–21) on trading volume and volatility Historical price trajectories of major companies like BEXIMCO, SQUARE, GP, BATBC, etc., are well captured. Value of the Data: Offers a comprehensive, time-rich view of Bangladesh’s capital market over 25+ years. Useful for quantitative finance, econometrics, and machine learning applications in time series forecasting. Enables comparative studies across sectors like banking, pharmaceuticals, telecom, textiles, etc. Suitable for academic research, policy analysis, and investment strategy development. Acts as a benchmark dataset for algorithm testing, especially in emerging market scenarios. Potential Use Cases: Financial modeling and stock price forecasting using machine learning Volatility and risk analysis across different timeframes Impact studies of global/regional events on stock performance Development of automated trading systems for the Bangladesh market Training data for university courses in finance, statistics, or data science Backtesting investment strategies and portfolio simulations Data visualization projects to explore long-term market trends

According to Cognitive Market Research, the global Date Palm market will be USD 11512.2 million in 2024 and will expand at a compound annual growth rate (CAGR) of 5.60% from 2024 to 2031.

North America held the major market share of more than 40% of the global revenue, with a market size of USD 4604.88 million in 2024. The market will grow at a compound annual growth rate (CAGR) of 3.8% from 2024 to 2031.
Europe accounted for a share of over 30% of the global market size of USD 3453.66 million.
Asia Pacific held a market share of around 23% of global revenue, with a market size of USD 2647.81 million in 2024, and will grow at a compound annual growth rate (CAGR) of 7.6% from 2024 to 2031.
Latin America's Market will have more than 5% of the global revenue with a market size of USD 575.61 million in 2024 and will grow at a compound annual growth rate (CAGR) of 5.0% from 2024 to 2031.
The Middle East and Africa held the major market share of around 2% of the global revenue, with a market size of USD 230.24 million in 2024. The market will grow at a compound annual growth rate (CAGR) of 5.3% from 2024 to 2031.
Whole date product held the highest Date Palm market revenue share in 2024.

Market Dynamics of Date Palm Market

Key Drivers of Date Palm Market

Increase in International Trade to Provide Viable Market Output

The increase in international trade is creating a significant increase in global demand. Firstly, globalization has facilitated easier access to markets worldwide, allowing date producers to reach a broader customer base. Additionally, advancements in transportation and logistics have made it more cost-effective to export date products across borders. Furthermore, rising consumer awareness of the nutritional benefits and versatility of dates has spurred demand in new regions. Moreover, governmental initiatives and trade agreements promoting agricultural exports have further boosted the international trade of date palms. Overall, this trend indicates a promising outlook for the global date palm market, with sustained growth expected in the foreseeable future.

For instance, in June 2023, The Food and Agriculture Organization (FAO) Council approved Saudi Arabia's proposal to declare 2027 the International Year of the Date Palm.

(Source: https://www.fao.org/3/nd767en/nd767en.pdf)

Increasing Demand for Organic Products Propels Market Growth

The increasing demand for organic products aims to provide growth in the Market. Consumers are becoming health-conscious and environmentally aware, leading to a preference for organically grown produce, including dates. Organic dates are cultivated without synthetic pesticides or fertilizers, aligning with the growing trend toward sustainable agriculture. Moreover, organic farming practices promote soil health and biodiversity conservation. As consumers get healthier and more sustainable food options, the demand for organic dates continues to rise. This trend presents opportunities for date palm growers to cater to a niche market segment focused on natural, chemical-free products, driving growth in the date palm market.

For instance, In the U.S., organic foods are certified by the National Organic Program. Almost 40% of people consider organic food as one of their leading food priorities. The sale of organic food stood at around US$ 57.5 Bn in the U.S. in 2021.

(Source: https://www.ers.usda.gov/topics/natural-resources-environment/organic-agriculture/)

Restraint Factors Of Date Palm Market

Water Scarcity to Restrict Market Growth

The Date Palm market faces challenges due to the scarcity of water. Date palms require ample water for growth and fruit production, making them highly vulnerable to water shortages. As water resources become scarce due to factors such as climate change and over-exploitation, the cultivation of date palms becomes challenging and economically unviable in certain regions. Inefficiencies in water management exacerbate this issue, leading to decreased yields and lower-quality produce. Additionally, competition for water resources from other sectors further strains the availability of water for date palm cultivation. Consequently, water scarcity acts as a significant constraint on the expansion and sustainability of the Date Palm market, impacting both production levels and market dynamics.

Impact of COVID-19 on the Date Palm Market

The market for...

The Long Depression was, by a large margin, the longest-lasting recession in U.S. history. It began in the U.S. with the Panic of 1873, and lasted for over five years. This depression was the largest in a series of recessions at the turn of the 20th century, which proved to be a period of overall stagnation as the U.S. financial markets failed to keep pace with industrialization and changes in monetary policy. Great Depression The Great Depression, however, is widely considered to have been the most severe recession in U.S. history. Following the Wall Street Crash in 1929, the country's economy collapsed, wages fell and a quarter of the workforce was unemployed. It would take almost four years for recovery to begin. Additionally, U.S. expansion and integration in international markets allowed the depression to become a global event, which became a major catalyst in the build up to the Second World War. Decreasing severity When comparing recessions before and after the Great Depression, they have generally become shorter and less frequent over time. Only three recessions in the latter period have lasted more than one year. Additionally, while there were 12 recessions between 1880 and 1920, there were only six recessions between 1980 and 2020. The most severe recession in recent years was the financial crisis of 2007 (known as the Great Recession), where irresponsible lending policies and lack of government regulation allowed for a property bubble to develop and become detached from the economy over time, this eventually became untenable and the bubble burst. Although the causes of both the Great Depression and Great Recession were similar in many aspects, economists have been able to use historical evidence to try and predict, prevent, or limit the impact of future recessions.

We investigate the relationship between long-term US stock market risks and the macroeconomic environment using a two-component GARCH-MIDAS model. Our results show that macroeconomic variables are important determinants of the secular component of stock market volatility. Among the various macro variables in our dataset the term spread, housing starts, corporate profits and the unemployment rate have the highest predictive ability for long-term stock market volatility. While the term spread and housing starts are leading variables with respect to stock market volatility, for industrial production and the unemployment rate expectations data from the Survey of Professional Forecasters regarding the future development are most informative.

KeyCorp stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

ZENPULSAR’s data centric AI platform “PUMP” monitors in real time multiple social media networks to track activities related to financial and crypto assets and then analyse them. It detects emerging viral narratives likely to form trends and impact financial assets. PUMP clears out the noise of social media with unmatched speed and accuracy. It identifies viral narratives related to the assets you track, early signals we can spot and act on before the crowds and everyone else. ZENPULSAR’s technology is also leveraged by a variety of clients to manage critical events such as product launches, policy platform developments, reputation crisis management, and disinformation campaigns. We are providing time series social media data relevant to selected assets. The data is extracted from Twitter, Reddit, Seeking Alpha, Telegram, LinkedIn, Facebook, and Weibo.

The data provided can be split into 4 categories: 1. Data describing sentiment of social media posts a. Number of social media posts with bullish/bearish sentiment towards a target asset per period b. Number of upvotes/downvotes, likes, replies, comments, cross-posts of the posts with bullish/bearish sentiment towards target asset per period 2. Data describing activity of social media accounts a. Number of social media posts per period 3. Data describing engagement of social media accounts a. Number of likes and upvotes/downvotes per period b. Number of replies and comments to the posts per period c. Number of retweets and cross-posts per period 4. Data describing credibility of social media accounts a. Number of Social media posts done by accounts identified as bots/not bots per period b. Number of Upvotes/downvotes, likes, replies, comments, cross-posts of the posts done by accounts identified as bots/non-bots per period c. Number of social media posts done by accounts identified as influencers/market analysts per period d. Number of upvotes/downvotes, likes, replies, comments, cross-posts of the posts done by accounts influencers/market analysts per period

Data analytics methodology

Selection of asset-relevant social media posts: This task is done via iterative usage of information retrieval methods such as keyword extraction and topic modelling (LDA, BERTopic, etc.). We extract the keywords for each asset that are commonly used by people. Because a person who wants to influence public opinion on an asset must provide a specific name for the target asset, such as relevant codes or common names, the keywords they choose will help us to identify them. Also, there are fine-tuned models to help us to determine the truth about the financial topics. By combining these methods and models, we can focus on the data to seek the alpha or identify critical events from different influencers.

Financial-related classification: To filter the key samples from large amounts of posts and news, we employ one of the state-of-art NLP models (Roberta-XLM) to achieve the best performance. There were already some pre-trained models focused on the news containing traditional assets such as bonds, FX, and stocks. By using weak-supervision learning and the additional internal data related to less traditional assets like crypto (added via such techniques as pseudo-labelling), our fine-tuned classifier can achieve great accuracy and precision. This is a binary classification to predict whether the post is related to finance or not.

Account classification: To classify an account as a bot or as an authentic user, we apply a combination of the following techniques: ● NLP-based content analysis - we employ transformer models like google MT5 or XLM-Roberta trained on bot post datasets. ● Heuristics-based features (speed of posting, statistical characteristics based on NER analysis results, etc). Those features are fed to the Support Vector machine classifier. ● The format of recent posts from the same user. Many bots have templates for different posts by putting the text together and transforming it. The model can extract features from the format to improve the model. ● Analysis of network topology (bots have a different one from human accounts), specifically betweenness centrality characteristics of an account within an account network (Katz centrality, Pagerank). To classify an account as an influencer or a market analyst, or an abnormal user we apply a combination of the following techniques: ● NLP-based content analysis - transformer models like google MT5 or XLM-Roberta trained on influencer post datasets. ● Analysis of the account following network characteristics of an account, specifically betweenness centrality, within the account network (Katz centrality, Pagerank, Eigenvector centrality). ● Number of followers/reddit karma thresholds.

Sentiment detection: We utilise transformer-based models (FinBert, CryptoBert and CryptoRoberta) finetuned on our internal datasets. The model was trained on cryptocurrency and stock data collected fr...

Explore Stock exchange automation through data • Key facts: author, publication date, book publisher, book series, book subjects • Real-time news, visualizations and datasets

The global calendar app market is projected to grow from USD 1.8 billion in 2023 to USD 4.0 billion by 2033, exhibiting a CAGR of 9.5% during the forecast period. The increasing adoption of cloud-based calendar solutions, rising demand for automated scheduling, and the growing trend of remote working are key drivers of market growth. Additionally, the integration of AI and machine learning in calendar apps is expected to enhance their functionality and user experience, further fueling market expansion. The cloud-based segment is anticipated to dominate the market due to its scalability, affordability, and ease of deployment. Furthermore, the increasing popularity of mobile devices and the rise of BYOD policies are contributing to the growth of this segment. The SME segment is expected to witness significant growth owing to the increasing adoption of calendar apps for managing appointments, scheduling meetings, and coordinating tasks. North America is expected to hold the largest market share, followed by Europe and Asia Pacific. The presence of leading players such as Google, Microsoft, and Apple, as well as the early adoption of technology in these regions, are key factors contributing to their dominance.

Abstract Purpose: The objective of this study is to analyze the impact of changes in credit ratings on the long-term return of Brazilian firms. Design/methodology/approach: We conducted an event study to measure how stock prices in the Brazilian stock exchange (B3) react to rating upgrades and downgrades by Moody’s and S&P. Findings: Our sample presents positive and significant returns measured by the BHAR for ratings downgrades and non-significant ones for upgrades. Our data also show the important role of the previous rating in explaining these results in a non-linear fashion. Originality/value: Our research makes an important contribution to the theory of market efficiency, analyzing the degree of information present in the announcements of credit ratings changes. We also present results for Brazilian companies, correcting gaps pointed out in previous methodologies.

Coated Face Stock Label Paper Market Outlook

The global coated face stock label paper market size was valued at approximately USD 12.5 billion in 2023 and is projected to reach USD 18.9 billion by 2032, growing at a compound annual growth rate (CAGR) of 4.5% during the forecast period. This robust growth trajectory is driven by various factors including the rising demand for labeled products in the food & beverages and pharmaceutical sectors. Increasing consumer awareness about product authenticity and safety further augments the need for high-quality coated face stock label paper, thus fueling market expansion.

A key growth factor for the coated face stock label paper market is the burgeoning food & beverages industry. The need for efficient labeling solutions in this sector is paramount for ensuring product information, brand identity, and regulatory compliance. Consumers are increasingly scrutinizing product labels for nutritional information and ingredient lists, thus necessitating the use of high-quality, durable labels that can withstand various environmental conditions. The rise in packaged food consumption globally has significantly contributed to this demand, thereby propelling the market for coated face stock label paper.

Another significant growth driver is the pharmaceutical industry, which mandates stringent labeling standards to ensure patient safety and regulatory compliance. Coated face stock label paper is extensively used to provide critical information such as dosage instructions, warnings, and expiration dates. The increasing prevalence of chronic diseases and the consequent rise in pharmaceutical product consumption have led to a surge in the demand for high-quality labeling solutions. Additionally, the adoption of advanced printing technologies further enhances the quality and functionality of these labels, thus boosting market growth.

The personal care and cosmetic industry also play a pivotal role in the market's growth. The aesthetic appeal and durability of coated face stock label paper make it an ideal choice for labeling premium personal care products. These labels not only enhance brand visibility but also provide vital product information to consumers. The growing trend of premiumization in the personal care sector has led to an increased demand for high-quality, visually appealing labels, thereby driving market growth.

Paper Coating Materials play a crucial role in the production of high-quality coated face stock label paper. These materials are essential for enhancing the surface properties of paper, providing a smooth and uniform finish that is ideal for printing. The choice of coating materials can significantly impact the printability, durability, and aesthetic appeal of the labels. With advancements in coating technologies, manufacturers are now able to produce labels that not only meet the functional requirements but also offer superior visual appeal. The development of eco-friendly and sustainable coating materials is also gaining traction, aligning with the growing demand for environmentally conscious labeling solutions.

Regionally, Asia Pacific is anticipated to exhibit significant growth during the forecast period. The rapid industrialization and urbanization in countries such as China and India have spurred the demand for labeled products. Additionally, the rising disposable income and changing consumption patterns in these regions are contributing to the increased demand for packaged goods, thereby fueling the growth of the coated face stock label paper market. The presence of a large number of manufacturing units and the availability of raw materials at competitive prices further augment market expansion in this region.

Product Type Analysis

The coated face stock label paper market can be segmented by product type into gloss coated, matte coated, and semi-gloss coated. Gloss coated label paper is highly sought after for its shiny finish and superior print quality, making it ideal for applications where visual appeal is critical. This type of label paper is extensively used in the food & beverages and personal care industries to enhance product presentation and brand visibility. The growing demand for premium packaging solutions is likely to drive the segment's growth during the forecast period.

Matte coated label paper, on the other hand, offers a non-reflecti