27 datasets found
  1. Inside the Supermarket Showdown: The Story Behind Supermarket Competition...

    • ibisworld.com
    Updated Mar 22, 2024
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    IBISWorld (2024). Inside the Supermarket Showdown: The Story Behind Supermarket Competition and Profits [Dataset]. https://www.ibisworld.com/blog/supermarket-competition-and-profits/99/1126/
    Explore at:
    Dataset updated
    Mar 22, 2024
    Dataset authored and provided by
    IBISWorld
    Time period covered
    Mar 22, 2024
    Description

    Coles and Woolworths’ high market share has raised the risk of exploitative business practices. AU profit compared with UK and US data paints the most accurate picture.

  2. Canadians believing grocery chains' fault for food price increases 2023, by...

    • statista.com
    Updated Mar 18, 2025
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    Statista (2025). Canadians believing grocery chains' fault for food price increases 2023, by province [Dataset]. https://www.statista.com/statistics/1441346/canada-grocery-chain-price-gouging-as-main-reason-for-increased-food-prices-by-province/
    Explore at:
    Dataset updated
    Mar 18, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Mar 2023
    Area covered
    Canada
    Description

    According to a survey conducted in Canada in 2023, close to 52 percent of respondents from Nova Scotia believed grocery chain price gouging to be the main reason food prices have been rising in Canada. Conversely, close to 22 percent of those from Quebec believed the same.

  3. Paramount Coffee Company Faces Price Hike Due to U.S. Tariffs - News and...

    • indexbox.io
    doc, docx, pdf, xls +1
    Updated Jun 1, 2025
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    IndexBox Inc. (2025). Paramount Coffee Company Faces Price Hike Due to U.S. Tariffs - News and Statistics - IndexBox [Dataset]. https://www.indexbox.io/blog/paramount-coffee-company-announces-price-increase-amid-tariff-challenges/
    Explore at:
    doc, pdf, xls, docx, xlsxAvailable download formats
    Dataset updated
    Jun 1, 2025
    Dataset provided by
    IndexBox
    Authors
    IndexBox Inc.
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2012 - Jun 1, 2025
    Area covered
    United States
    Variables measured
    Market Size, Market Share, Tariff Rates, Average Price, Export Volume, Import Volume, Demand Elasticity, Market Growth Rate, Market Segmentation, Volume of Production, and 4 more
    Description

    Paramount Coffee Company is increasing prices as U.S. tariffs on imported coffee beans strain the Midwest coffee market.

  4. f

    Analysis of difference between newsvending and price gouging choices.

    • plos.figshare.com
    bin
    Updated Jun 16, 2023
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    Zuzana Brokesova; Cary Deck; Jana Peliova (2023). Analysis of difference between newsvending and price gouging choices. [Dataset]. http://doi.org/10.1371/journal.pone.0264183.t004
    Explore at:
    binAvailable download formats
    Dataset updated
    Jun 16, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Zuzana Brokesova; Cary Deck; Jana Peliova
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Analysis of difference between newsvending and price gouging choices.

  5. How Chipotle Keeps Prices Stable Amid U.S. Tariff Concerns - News and...

    • indexbox.io
    doc, docx, pdf, xls +1
    Updated Jul 4, 2025
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    IndexBox Inc. (2025). How Chipotle Keeps Prices Stable Amid U.S. Tariff Concerns - News and Statistics - IndexBox [Dataset]. https://www.indexbox.io/blog/chipotle-navigates-tariffs-without-raising-prices/
    Explore at:
    xlsx, pdf, doc, docx, xlsAvailable download formats
    Dataset updated
    Jul 4, 2025
    Dataset provided by
    IndexBox
    Authors
    IndexBox Inc.
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2012 - Jul 1, 2025
    Area covered
    Mexico
    Variables measured
    Market Size, Market Share, Tariff Rates, Average Price, Export Volume, Import Volume, Demand Elasticity, Market Growth Rate, Market Segmentation, Volume of Production, and 4 more
    Description

    Chipotle CEO Scott Boatwright reveals the company's plan to absorb costs from Trump's tariffs, avoiding price hikes, with efficient sourcing and innovative operations.

  6. Monthly inflation rate and Federal Reserve interest rate in the U.S....

    • statista.com
    • ai-chatbox.pro
    Updated Jun 23, 2025
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    Statista (2025). Monthly inflation rate and Federal Reserve interest rate in the U.S. 2018-2025 [Dataset]. https://www.statista.com/statistics/1312060/us-inflation-rate-federal-reserve-interest-rate-monthly/
    Explore at:
    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2018 - Mar 2024
    Area covered
    United States
    Description

    The inflation rate in the United States declined significantly between June 2022 and May 2025, despite rising inflationary pressures towards the end of 2024. The peak inflation rate was recorded in June 2022, at *** percent. In August 2023, the Federal Reserve's interest rate hit its highest level during the observed period, at **** percent, and remained unchanged until September 2024, when the Federal Reserve implemented its first rate cut since September 2021. By January 2025, the rate dropped to **** percent, signalling a shift in monetary policy. What is the Federal Reserve interest rate? The Federal Reserve interest rate, or the federal funds rate, is the rate at which banks and credit unions lend to and borrow from each other. It is one of the Federal Reserve's key tools for maintaining strong employment rates, stable prices, and reasonable interest rates. The rate is determined by the Federal Reserve and adjusted eight times a year, though it can be changed through emergency meetings during times of crisis. The Fed doesn't directly control the interest rate but sets a target rate. It then uses open market operations to influence rates toward this target. Ways of measuring inflation Inflation is typically measured using several methods, with the most common being the Consumer Price Index (CPI). The CPI tracks the price of a fixed basket of goods and services over time, providing a measure of the price changes consumers face. At the end of 2023, the CPI in the United States was ****** percent, up from ****** a year earlier. A more business-focused measure is the producer price index (PPI), which represents the costs of firms.

  7. f

    Descriptive statistics of inventory and price choices.

    • plos.figshare.com
    bin
    Updated Jun 16, 2023
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    Zuzana Brokesova; Cary Deck; Jana Peliova (2023). Descriptive statistics of inventory and price choices. [Dataset]. http://doi.org/10.1371/journal.pone.0264183.t002
    Explore at:
    binAvailable download formats
    Dataset updated
    Jun 16, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Zuzana Brokesova; Cary Deck; Jana Peliova
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Descriptive statistics of inventory and price choices.

  8. US Steelmakers Increase Rebar Prices by $60 Per Ton - News and Statistics -...

    • indexbox.io
    doc, docx, pdf, xls +1
    Updated Jun 1, 2025
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    IndexBox Inc. (2025). US Steelmakers Increase Rebar Prices by $60 Per Ton - News and Statistics - IndexBox [Dataset]. https://www.indexbox.io/blog/us-steel-companies-announce-rebar-price-hike/
    Explore at:
    xlsx, docx, xls, doc, pdfAvailable download formats
    Dataset updated
    Jun 1, 2025
    Dataset provided by
    IndexBox
    Authors
    IndexBox Inc.
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2012 - Jun 9, 2025
    Area covered
    United States
    Variables measured
    Market Size, Market Share, Tariff Rates, Average Price, Export Volume, Import Volume, Demand Elasticity, Market Growth Rate, Market Segmentation, Volume of Production, and 4 more
    Description

    Major US steelmakers hike rebar prices by $60 per ton amid market fluctuations and demand changes.

  9. Nucor's Fourth Price Hike in 2025 for Hot-Rolled Coils - News and Statistics...

    • indexbox.io
    doc, docx, pdf, xls +1
    Updated Jul 1, 2025
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    IndexBox Inc. (2025). Nucor's Fourth Price Hike in 2025 for Hot-Rolled Coils - News and Statistics - IndexBox [Dataset]. https://www.indexbox.io/blog/nucor-announces-price-increase-for-hot-rolled-coils/
    Explore at:
    docx, doc, xls, xlsx, pdfAvailable download formats
    Dataset updated
    Jul 1, 2025
    Dataset provided by
    IndexBox
    Authors
    IndexBox Inc.
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2012 - Jul 1, 2025
    Area covered
    United States
    Variables measured
    Market Size, Market Share, Tariff Rates, Average Price, Export Volume, Import Volume, Demand Elasticity, Market Growth Rate, Market Segmentation, Volume of Production, and 4 more
    Description

    Nucor Corporation raises hot-rolled coil prices for the fourth time in 2025, setting the new base at $820 per short tonne, reflecting dynamic market trends and trade policy influences.

  10. Volcker Shock: federal funds, unemployment and inflation rates 1979-1987

    • statista.com
    Updated Sep 2, 2024
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    Statista (2024). Volcker Shock: federal funds, unemployment and inflation rates 1979-1987 [Dataset]. https://www.statista.com/statistics/1338105/volcker-shock-interest-rates-unemployment-inflation/
    Explore at:
    Dataset updated
    Sep 2, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    1979 - 1987
    Area covered
    United States
    Description

    The Volcker Shock was a period of historically high interest rates precipitated by Federal Reserve Chairperson Paul Volcker's decision to raise the central bank's key interest rate, the Fed funds effective rate, during the first three years of his term. Volcker was appointed chairperson of the Fed in August 1979 by President Jimmy Carter, as replacement for William Miller, who Carter had made his treasury secretary. Volcker was one of the most hawkish (supportive of tighter monetary policy to stem inflation) members of the Federal Reserve's committee, and quickly set about changing the course of monetary policy in the U.S. in order to quell inflation. The Volcker Shock is remembered for bringing an end to over a decade of high inflation in the United States, prompting a deep recession and high unemployment, and for spurring on debt defaults among developing countries in Latin America who had borrowed in U.S. dollars.

    Monetary tightening and the recessions of the early '80s

    Beginning in October 1979, Volcker's Fed tightened monetary policy by raising interest rates. This decision had the effect of depressing demand and slowing down the U.S. economy, as credit became more expensive for households and businesses. The Fed funds rate, the key overnight rate at which banks lend their excess reserves to each other, rose as high as 17.6 percent in early 1980. The rate was allowed to fall back below 10 percent following this first peak, however, due to worries that inflation was not falling fast enough, a second cycle of monetary tightening was embarked upon starting in August of 1980. The rate would reach its all-time peak in June of 1981, at 19.1 percent. The second recession sparked by these hikes was far deeper than the 1980 recession, with unemployment peaking at 10.8 percent in December 1980, the highest level since The Great Depression. This recession would drive inflation to a low point during Volcker's terms of 2.5 percent in August 1983.

    The legacy of the Volcker Shock

    By the end of Volcker's terms as Fed Chair, inflation was at a manageable rate of around four percent, while unemployment had fallen under six percent, as the economy grew and business confidence returned. While supporters of Volcker's actions point to these numbers as proof of the efficacy of his actions, critics have claimed that there were less harmful ways that inflation could have been brought under control. The recessions of the early 1980s are cited as accelerating deindustrialization in the U.S., as manufacturing jobs lost in 'rust belt' states such as Michigan, Ohio, and Pennsylvania never returned during the years of recovery. The Volcker Shock was also a driving factor behind the Latin American debt crises of the 1980s, as governments in the region defaulted on debts which they had incurred in U.S. dollars. Debates about the validity of using interest rate hikes to get inflation under control have recently re-emerged due to the inflationary pressures facing the U.S. following the Coronavirus pandemic and the Federal Reserve's subsequent decision to embark on a course of monetary tightening.

  11. f

    Regression analysis of individual characteristics on average choice.

    • figshare.com
    bin
    Updated Jun 16, 2023
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    Zuzana Brokesova; Cary Deck; Jana Peliova (2023). Regression analysis of individual characteristics on average choice. [Dataset]. http://doi.org/10.1371/journal.pone.0264183.t003
    Explore at:
    binAvailable download formats
    Dataset updated
    Jun 16, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Zuzana Brokesova; Cary Deck; Jana Peliova
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Regression analysis of individual characteristics on average choice.

  12. Probit analysis of chasing behavior.

    • plos.figshare.com
    bin
    Updated May 30, 2023
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    Zuzana Brokesova; Cary Deck; Jana Peliova (2023). Probit analysis of chasing behavior. [Dataset]. http://doi.org/10.1371/journal.pone.0264183.t007
    Explore at:
    binAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Zuzana Brokesova; Cary Deck; Jana Peliova
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Probit analysis of chasing behavior.

  13. Grocery retail sales value of supermarkets Australia 2014-2023

    • statista.com
    • ai-chatbox.pro
    Updated Jun 12, 2025
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    Statista (2025). Grocery retail sales value of supermarkets Australia 2014-2023 [Dataset]. https://www.statista.com/statistics/972669/grocery-retail-sales-value-supermarkets-australia/
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    Dataset updated
    Jun 12, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Australia
    Description

    In 2023, the value of grocery retail sales from supermarkets in Australia exceeded *** billion Australian dollars. This marked an increase from the previous year, in which grocery retail sales were valued at just shy of *** billion Australian dollars. Which supermarkets dominate Australia’s grocery landscape? Australia’s supermarket and grocery sector is highly concentrated, with the top four companies, Woolworths, Coles, German company Aldi, and IGA (Metcash) holding over ** percent of the country’s grocery retailer market share. The top two supermarkets, Woolworths and Coles, have extensive retail networks across the country, with around ***** stores in the Woolworths network as of May 2025, including Woolworths Supermarkets, Ampol Woolworths, and EG Ampol locations. Inquiry into Australia’s grocery sector Going into 2024, the price of groceries was one of the most pressing financial issues for many Australian households, with almost ** percent of consumers surveyed in April 2024 saying they felt grocery prices had increased compared to the previous year. Only ** percent of Australian consumers indicated in the same survey that, in their view, grocery products were priced fairly by supermarkets. Following price gouging allegations against major supermarket chains in the country, including Australia’s supermarket duopoly, Woolworths and Coles, the Australian Consumer Competition Commission (ACCC) launched its inquiry into the country’s grocery retail sector in January 2024. The inquiry endeavors to highlight key issues across the supermarket sector and introduce improved regulatory framework and pricing mechanisms, enabling better market access for smaller grocery retailers and discounters, as well as improving customer, supply chain contributor, and farmer satisfaction.

  14. f

    Analysis of asymmetric pull-to-center effect.

    • plos.figshare.com
    bin
    Updated Jun 16, 2023
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    Zuzana Brokesova; Cary Deck; Jana Peliova (2023). Analysis of asymmetric pull-to-center effect. [Dataset]. http://doi.org/10.1371/journal.pone.0264183.t005
    Explore at:
    binAvailable download formats
    Dataset updated
    Jun 16, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Zuzana Brokesova; Cary Deck; Jana Peliova
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Analysis of asymmetric pull-to-center effect.

  15. f

    Analysis of the within subject variation of choices.

    • plos.figshare.com
    bin
    Updated Jun 5, 2023
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    Zuzana Brokesova; Cary Deck; Jana Peliova (2023). Analysis of the within subject variation of choices. [Dataset]. http://doi.org/10.1371/journal.pone.0264183.t006
    Explore at:
    binAvailable download formats
    Dataset updated
    Jun 5, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Zuzana Brokesova; Cary Deck; Jana Peliova
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Analysis of the within subject variation of choices.

  16. d

    Inflation Rates Master Data: Year- and Month-wise Consumer Price Index of...

    • dataful.in
    Updated Jul 1, 2025
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    Dataful (Factly) (2025). Inflation Rates Master Data: Year- and Month-wise Consumer Price Index of Industrial Workers and Agricultural and Rural Labourers (from base year 1960) [Dataset]. https://dataful.in/datasets/17508
    Explore at:
    csv, xlsx, application/x-parquetAvailable download formats
    Dataset updated
    Jul 1, 2025
    Dataset authored and provided by
    Dataful (Factly)
    License

    https://dataful.in/terms-and-conditionshttps://dataful.in/terms-and-conditions

    Area covered
    India
    Variables measured
    Consumer Price Index
    Description

    The dataset contains year- and month-wise historically compiled from the year 1960 to till date on the consumer price index, along with linking factor, of industrial workers, agricultural and rural labourers

    Note: Data for the latest two months are provisional.

  17. f

    Participant characteristics by treatment.

    • figshare.com
    bin
    Updated Jun 16, 2023
    + more versions
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    Zuzana Brokesova; Cary Deck; Jana Peliova (2023). Participant characteristics by treatment. [Dataset]. http://doi.org/10.1371/journal.pone.0264183.t001
    Explore at:
    binAvailable download formats
    Dataset updated
    Jun 16, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Zuzana Brokesova; Cary Deck; Jana Peliova
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Participant characteristics by treatment.

  18. P

    ##Do flight prices change the more you search? Dataset

    • paperswithcode.com
    Updated Jun 28, 2025
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    (2025). ##Do flight prices change the more you search? Dataset [Dataset]. https://paperswithcode.com/dataset/do-flight-prices-change-the-more-you-search
    Explore at:
    Dataset updated
    Jun 28, 2025
    Description

    Flight prices can vary dramatically depending on a range of factors. In fact, prices can change up to 100 times a day for the same route. ☎️+1 (855) 217-1878 While it might seem like the more you search, the higher the prices climb, this perception isn't always due to actual price changes. ☎️+1 (855) 217-1878 Instead, it's often driven by how airline algorithms work, using cookies and user behavior to personalize pricing or trigger urgency.

    Airlines use dynamic pricing algorithms that take into account your search history, location, time of day, and even the device you're using. ☎️+1 (855) 217-1878 These algorithms are designed to maximize revenue, which can lead to the illusion that repeatedly searching raises the price. ☎️+1 (855) 217-1878 In some cases, this may be true if the site uses your activity to suggest urgency or simulate demand. But it's not always a hard rule.

    For example, when you search multiple times for a flight to New York from Los Angeles within a short period, you may notice the fare jump slightly. ☎️+1 (855) 217-1878 This doesn’t necessarily mean the system is punishing you; rather, it may reflect changing inventory, competitor pricing, or new bookings. ☎️+1 (855) 217-1878 Airlines operate with a tiered pricing model, so as cheaper seats sell out, more expensive ones take their place, which also explains rising fares.

    Browser cookies may play a small role. Some travel booking websites use cookies to track your behavior. ☎️+1 (855) 217-1878 While many deny price manipulation, clearing your cookies or browsing in incognito mode can sometimes help you see different fares. ☎️+1 (855) 217-1878 However, experts argue that inventory and timing are far bigger factors than user behavior.

    Another element is the time and day you search. Studies show that flight prices are often lower midweek and higher on weekends. ☎️+1 (855) 217-1878 Searching Tuesday or Wednesday morning may yield better deals than browsing on a Saturday evening. ☎️+1 (855) 217-1878 Timing plays a big role not only in pricing but also in seat availability and routing options.

    Using price tracking tools like Google Flights, Skyscanner, or Hopper can help monitor price trends over time. ☎️+1 (855) 217-1878 These tools analyze historical data and notify users when it's the best time to book based on trends. ☎️+1 (855) 217-1878 This strategy helps you avoid impulsive purchases based on artificially inflated fares or perceived scarcity.

    Airlines also increase fares based on seasonal demand. For example, flights during the December holiday season or summer breaks tend to rise steeply. ☎️+1 (855) 217-1878 If your repeated searches coincide with high-demand periods, you’re more likely to see fare increases regardless of your search behavior. ☎️+1 (855) 217-1878 This is due to genuine supply and demand dynamics, not necessarily algorithmic manipulation.

    In reality, flight prices do change frequently—but not always because of your search behavior. ☎️+1 (855) 217-1878 They change due to availability, demand, competitor actions, and many external economic factors. ☎️+1 (855) 217-1878 Airlines aim to sell each seat at the highest price someone is willing to pay, using powerful tools to make that happen.

    In short, it’s wise to compare prices across multiple platforms, use incognito mode, and track fares before booking. ☎️+1 (855) 217-1878 By understanding the logic behind price fluctuations, you can better time your purchase and avoid overpaying. ☎️+1 (855) 217-1878 Strategic planning is your best ally when navigating airfare volatility.

  19. m

    Data from: The Economic Bomb: A Strategic Financial Warfare Tactic

    • data.mendeley.com
    Updated Feb 21, 2025
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    Nicolin Decker (2025). The Economic Bomb: A Strategic Financial Warfare Tactic [Dataset]. http://doi.org/10.17632/xn9ws8x6j7.2
    Explore at:
    Dataset updated
    Feb 21, 2025
    Authors
    Nicolin Decker
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset provides evidence supporting the hypothesis that institutional shorting, ETF outflows, whale wallet movements, and media sentiment drive Bitcoin’s volatility and price manipulation. Central to this dataset is the Decker Sentiment-Short Interest Model (DSSIM)—an original equation developed by Nicolin Decker to quantify the relationship between market sentiment and institutional short interest. By combining sentiment scores from Natural Language Processing (NLP) and short positioning data, DSSIM offers a flexible framework for analyzing volatility in Bitcoin and other assets.

    The dataset spans January 2021 to December 2024, capturing daily market activity and key price events. Each file aligns with DSSIM’s variables, enabling replication and further analysis of the findings in the doctoral-level thesis The Economic Bomb: A Strategic Financial Warfare Tactic.

    Key Components: BTC_Price_Data.csv: Daily BTC/USD closing prices from Binance, Coinbase, and Bitstamp, serving as the baseline for volatility and return calculations.

    ETF_Holdings_Over_Time_Thesis.csv: Daily BTC holdings of ETFs (Grayscale, BlackRock, and Fidelity), illustrating cumulative outflows and their liquidity impact.

    ETF_Outflows_Price_Impact_Data.csv: Correlates ETF outflows with BTC volatility, highlighting timing and magnitude.

    Institutional_Shorting_Data.csv: Daily BTC short positions from Binance, BitMEX, Bybit, and OKX, serving as input for DSSIM’s short interest variable.

    Whale_Wallet_Movements.csv: Tracks large BTC wallet movements, revealing sell-offs preceding price crashes and influencing DSSIM’s residual noise component.

    Market_Liquidity_Data.csv: Daily BTC trading volume, order book depth, and liquidity ratios, validating DSSIM’s predictive capabilities.

    Media_Sentiment_Scores.csv: Daily sentiment from Twitter, Reddit, Google News, and YouTube, forming DSSIM’s sentiment variable.

    Monte_Carlo_Simulation_Results.csv: Simulates 1,000 BTC price paths to assess potential volatility under market stress.

    VAR_Model_Data.csv: Analyzes ETF outflows’ delayed impact on BTC returns using vector autoregression.

    Volatility_Clustering_Data.csv: Tracks daily BTC returns and 30-day rolling volatility, confirming persistent volatility after institutional actions.

    GARCH_Model_Data.csv: Models BTC volatility using GARCH, validating volatility clustering during market shocks.

    The dataset includes adjustments for major market events, such as the May 2021 Flash Crash, June 2022 Liquidation Crisis, and March 2023 Banking Crisis, ensuring realistic volatility patterns aligned with DSSIM’s modeling of sentiment shifts and institutional shorting.

    Researchers can use DSSIM’s structure and data to explore similar dynamics in other cryptocurrencies, equities, commodities, and forex markets, advancing financial analysis and predictive modeling.

    Access the full dataset: https://drive.google.com/drive/folders/1pnwqBTMF_QSJoC5QcNAPSQpVtOST2n8c?usp=drive_link

  20. Monthly electricity price for industries in the United States 2020-2024

    • statista.com
    Updated Jun 27, 2025
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    Monthly electricity price for industries in the United States 2020-2024 [Dataset]. https://www.statista.com/statistics/1395805/monthly-electricity-price-industrial-sector-united-states/
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    Dataset updated
    Jun 27, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2020 - May 2024
    Area covered
    United States
    Description

    Electricity prices for industries in the United States increased over the past few years, peaking in summer 2022. Industrial electricity prices amounted to **** U.S. cents per kilowatt-hour in May 2024, up from **** U.S. dollar cents per kilowatt-hour the previous month. The average retail electricity price for industrial consumers in the United States stood at **** U.S. dollar cents per kilowatt-hour in 2023.

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IBISWorld (2024). Inside the Supermarket Showdown: The Story Behind Supermarket Competition and Profits [Dataset]. https://www.ibisworld.com/blog/supermarket-competition-and-profits/99/1126/
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Inside the Supermarket Showdown: The Story Behind Supermarket Competition and Profits

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Dataset updated
Mar 22, 2024
Dataset authored and provided by
IBISWorld
Time period covered
Mar 22, 2024
Description

Coles and Woolworths’ high market share has raised the risk of exploitative business practices. AU profit compared with UK and US data paints the most accurate picture.

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