3 datasets found
  1. k

    Asia Dragon Stock Forecast: Get Ready to Ride the Dragon's Tailwind (DGN)...

    • kappasignal.com
    Updated Jun 26, 2024
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    KappaSignal (2024). Asia Dragon Stock Forecast: Get Ready to Ride the Dragon's Tailwind (DGN) (Forecast) [Dataset]. https://www.kappasignal.com/2024/06/asia-dragon-stock-forecast-get-ready-to.html
    Explore at:
    Dataset updated
    Jun 26, 2024
    Dataset authored and provided by
    KappaSignal
    License

    https://www.kappasignal.com/p/legal-disclaimer.htmlhttps://www.kappasignal.com/p/legal-disclaimer.html

    Description

    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.

    Asia Dragon Stock Forecast: Get Ready to Ride the Dragon's Tailwind (DGN)

    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

  2. Indonesia CPI: 2022=100: Weights: Food, Beverage and Tobacco: Food: Dragon...

    • ceicdata.com
    Updated Feb 15, 2025
    + more versions
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    CEICdata.com (2025). Indonesia CPI: 2022=100: Weights: Food, Beverage and Tobacco: Food: Dragon Fruit [Dataset]. https://www.ceicdata.com/en/indonesia/consumer-price-index-2022100-weights/cpi-2022100-weights-food-beverage-and-tobacco-food-dragon-fruit
    Explore at:
    Dataset updated
    Feb 15, 2025
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Feb 1, 2024 - Jan 1, 2025
    Area covered
    Indonesia
    Description

    Indonesia Consumer Price Index (CPI): 2022=100: Weights: Food, Beverage and Tobacco: Food: Dragon Fruit data was reported at 0.034 % in Mar 2025. This stayed constant from the previous number of 0.034 % for Feb 2025. Indonesia Consumer Price Index (CPI): 2022=100: Weights: Food, Beverage and Tobacco: Food: Dragon Fruit data is updated monthly, averaging 0.034 % from Jan 2022 (Median) to Mar 2025, with 39 observations. The data reached an all-time high of 0.034 % in Mar 2025 and a record low of 0.034 % in Mar 2025. Indonesia Consumer Price Index (CPI): 2022=100: Weights: Food, Beverage and Tobacco: Food: Dragon Fruit data remains active status in CEIC and is reported by Statistics Indonesia. The data is categorized under Indonesia Premium Database’s Inflation – Table ID.IA010: Consumer Price Index: 2022=100: Weights.

  3. f

    Data from: A pneumatic soft gripper with pre-deformed stiffener inspired by...

    • figshare.com
    docx
    Updated May 29, 2025
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    Yingli Li; Jiajia Ding; Song Yao; Chong Shi (2025). A pneumatic soft gripper with pre-deformed stiffener inspired by blowing dragon toys [Dataset]. http://doi.org/10.6084/m9.figshare.29183787.v1
    Explore at:
    docxAvailable download formats
    Dataset updated
    May 29, 2025
    Dataset provided by
    Taylor & Francis
    Authors
    Yingli Li; Jiajia Ding; Song Yao; Chong Shi
    License

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

    Description

    The movement of toys not only captures attention of children but also informs the design of soft robotics. Pneumatic actuators are a key area of research in soft robotics due to their lightweight and easily controllable characteristic. This study presents the design of a novel pneumatic soft gripper that integrates a soft, minimally stretchable inflatable tube with a pre-deformed stiffener. The motion of the gripper is inspired by the inflation and deflation process of the blowing dragon toys. The gripper’s bending performance and load capacity are analyzed through theoretical force analysis and finite element simulations. Its grasping performance and versatility were evaluated across a range of applications in experiments. Results indicate a consistent trend between theoretical force analysis, finite element simulations, and experimental outcomes. The proposed soft gripper is capable of grasping objects weighing up to 23.32 g and with a diameter of up to 50 mm, achieving a weight-to-grip ratio of approximately 28.38 times its own weight (0.82 g). Compared with conventional lightweight pneumatic soft grippers, the proposed design exhibits superior load capacity. Furthermore, it demonstrates practical applications in tasks such as catching thumbtacks, collecting items, and cleaning pipes due to its excellent bending performance.

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Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
KappaSignal (2024). Asia Dragon Stock Forecast: Get Ready to Ride the Dragon's Tailwind (DGN) (Forecast) [Dataset]. https://www.kappasignal.com/2024/06/asia-dragon-stock-forecast-get-ready-to.html

Asia Dragon Stock Forecast: Get Ready to Ride the Dragon's Tailwind (DGN) (Forecast)

Explore at:
Dataset updated
Jun 26, 2024
Dataset authored and provided by
KappaSignal
License

https://www.kappasignal.com/p/legal-disclaimer.htmlhttps://www.kappasignal.com/p/legal-disclaimer.html

Description

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.

Asia Dragon Stock Forecast: Get Ready to Ride the Dragon's Tailwind (DGN)

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

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