The yield on US 10 Year Note Bond Yield rose to 4.12% on December 2, 2025, marking a 0.02 percentage points increase from the previous session. Over the past month, the yield has remained flat, and it is 0.11 points lower than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. US 10 Year Treasury Bond Note Yield - values, historical data, forecasts and news - updated on December of 2025.

The yield on India 10Y Bond Yield eased to 6.52% on December 2, 2025, marking a 0.06 percentage points decrease from the previous session. Over the past month, the yield has fallen by 0.03 points and is 0.24 points lower than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. India 10-Year Government Bond Yield - values, historical data, forecasts and news - updated on December of 2025.

** Overview** This dataset contains stock price data for 5 different stocks along with major market indices (Dow Jones, NASDAQ, and S&P 500). The data has been enhanced with various technical indicators and features commonly used in financial analysis and algorithmic trading.

Dataset Statistics

• Number of rows: 2569
• Number of columns: 221
• Date range: 2015-01-05 to 2025-03-21
• Number of stocks: 5
• Number of market indices: 3

Feature Naming Conventions

• Features ending with numbers (e.g., return_1, close_2) refer to specific stocks (1-5)
• Features with X_Y format (e.g., ma10_3, beta_2_nasdaq_20) have the following pattern:
  • First number/name refers to the parameter or stock
  • Second number/name refers to the stock or index
  • Third number (if present) refers to the time window
• Correlation features (e.g., corr_1_2) show correlation between two stocks (stock 1 and stock 2)

Feature Categories

Basic Price Data

• Date: Trading date in YYYY-MM-DD format
• return_X: Daily return (percentage price change) for stock X (where X is 1-5)
• open_X: Opening price for stock X
• high_X: Highest price during the trading day for stock X
• low_X: Lowest price during the trading day for stock X
• close_X: Closing price for stock X
• adjusted_X: Adjusted closing price for stock X (accounts for dividends and splits)
• volume_X: Trading volume (number of shares traded) for stock X

Market Index Data

• returns_dj: Daily return for Dow Jones Industrial Average
• close_dj: Closing price for Dow Jones Industrial Average
• returns_nasdaq: Daily return for NASDAQ Composite Index
• close_nasdaq: Closing price for NASDAQ Composite Index
• returns_SP500: Daily return for S&P 500 Index
• close_SP500: Closing price for S&P 500 Index

Moving Averages and Trend Indicators

• maX_Y: X-day simple moving average of closing price for stock Y
• emaX_Y: X-day exponential moving average of closing price for stock Y
• envelope_upper_X: Upper price envelope (5% above MA10) for stock X
• envelope_lower_X: Lower price envelope (5% below MA10) for stock X

Momentum and Volatility Indicators

• rocX_Y: X-day Rate of Change (percentage) for stock Y
• volatility_X: 20-day rolling standard deviation of returns for stock X
• rsi_X: 14-day Relative Strength Index for stock X (momentum indicator, 0-100)
• macd_X: Moving Average Convergence Divergence for stock X (ema12 - ema26)
• macd_signal_X: 9-day EMA of MACD for stock X
• macd_hist_X: MACD histogram for stock X (macd - macd_signal)

Volume Indicators

• volume_ma10_X: 10-day moving average of trading volume for stock X
• volume_ratio_X: Ratio of current volume to 10-day volume MA for stock X

Price Ratio Indicators

• high_low_ratio_X: Ratio of high price to low price for stock X (daily range)
• close_open_ratio_X: Ratio of close price to open price for stock X (intraday movement)

Correlation and Beta Indicators

• beta_X_Y_Z: Z-day rolling beta of stock X to index Y (measure of volatility relative to market)
• corr_X_Y: 20-day rolling correlation between returns of stock X and stock Y (ranges from -1 to 1)

Example Usage

import pandas as pd
import matplotlib.pyplot as plt

# Load the dataset
df = pd.read_csv('enhanced_stock_dataset.csv')
df['Date'] = pd.to_datetime(df['Date'])

# Plot closing prices for all stocks
plt.figure(figsize=(12, 6))
for i in range(1, 6):
  plt.plot(df['Date'], df[f'close_{i}'], label=f'Stock {i}')
plt.title('Stock Closing Prices')
plt.xlabel('Date')
plt.ylabel('Price')
plt.legend()
plt.grid(True)
plt.show()

Notes

• This dataset contains engineered features that can be directly used for machine learning models
• All NaN values have been filled using forward and backward filling methods
• The correlation features (corr_X_Y) show the relationship between different stocks
• Beta values show the relationship between each stock and the market indices

View data of the S&P 500, an index of the stocks of 500 leading companies in the US economy, which provides a gauge of the U.S. equity market.

Dividend-Yield Time Series for IG Group Holdings PLC. IG Group Holdings plc, a fintech company, engages in the online trading business in the United Kingdom, Ireland, the Asia-Pacific, the Middle East, the United States, Europe, and institutional and emerging markets. The company offers retail over the counter derivatives, including contracts for difference, OTC FX and options; and exchange-traded derivatives options and futures under the tastytrade. It also provides stock trading and investment services, such as share trading, smart portfolios, and ISA and SIPPs, as well as equities, exchange traded funds, and fixed income products, which include fractional shares, mutual funds, UK treasury bills, UK tax wrappers, securities lending, and proxy voting services; and cash crypto trading. In addition, the company offers content and education solutions, such as daily live programming, news and original content, and webinars and tutorials, as well as content, education, and support tools, including signals, analytics, charting applications, and proprietary insights through the Trade Live with IG and tastylive channels. Further, it engages in CFD trading, foreign exchange, and market risk management; spread betting; data distribution; software development and support services; turbo warrants issuing; financing; market maker; network and content provision; and brokerage activities. The company serves investors, customers, communities, colleagues, regulators, and suppliers. IG Group Holdings plc was founded in 1974 and is headquartered in London, the United Kingdom.

Techsalerator offers an extensive dataset of End-of-Day Pricing Data for all 408 companies listed on the Guayaquil Stock Exchange (XGUA) in Ecuador. This dataset includes the closing prices of equities (stocks), bonds, and indices at the end of each trading session. End-of-day prices are vital pieces of market data that are widely used by investors, traders, and financial institutions to monitor the performance and value of these assets over time.

‍

Top 5 used data fields in the End-of-Day Pricing Dataset for Ecuador:

1. Equity Closing Price :The closing price of individual company stocks at the end of the trading day.This field provides insights into the final price at which market participants were willing to buy or sell shares of a specific company.

2. Bond Closing Price: The closing price of various fixed-income securities, including government bonds, corporate bonds, and municipal bonds. Bond investors use this field to assess the current market value of their bond holdings.

3. Index Closing Price: The closing value of market indices, such as the Botswana stock market index, at the end of the trading day. These indices track the overall market performance and direction.

4. Equity Ticker Symbol: The unique symbol used to identify individual company stocks. Ticker symbols facilitate efficient trading and data retrieval.

5. Date of Closing Price: The specific trading day for which the closing price is provided. This date is essential for historical analysis and trend monitoring.

‍

Top 5 financial instruments with End-of-Day Pricing Data in Ecuador:

Bolsa de Valores de Quito (BVQ) General Index: The BVQ General Index is a benchmark index that tracks the performance of domestic companies listed on the Bolsa de Valores de Quito (BVQ), the main stock exchange in Ecuador. It provides an overview of the overall market performance in the country.

Bolsa de Valores de Guayaquil (BVG) Index: The BVG Index is another key index in Ecuador, tracking the performance of companies listed on the Bolsa de Valores de Guayaquil (BVG), one of the major stock exchanges in the country.

Corporación Favorita C.A.: Corporación Favorita is a prominent Ecuadorian retail company that operates supermarkets and hypermarkets under various brand names. It is one of the largest companies in Ecuador's retail sector.

Petroamazonas EP (Ecuadorian state oil company): Petroamazonas is a state-owned oil company in Ecuador engaged in the exploration, production, and development of oil and gas resources. It plays a significant role in Ecuador's energy sector.

Banco Pichincha: Banco Pichincha is one of the largest banks in Ecuador, providing a wide range of banking and financial services to individuals and businesses. It is an important player in the country's financial industry.

‍

If you're interested in accessing Techsalerator's End-of-Day Pricing Data for Ecuador, please contact info@techsalerator.com with your specific requirements. Techsalerator will provide you with a customized quote based on the number of data fields and records you need. The dataset can be delivered within 24 hours, and ongoing access options can be discussed if needed.

‍

Data fields included:

Equity Ticker Symbol Equity Closing Price Bond Ticker Symbol Bond Closing Price Index Ticker Symbol Index Closing Price Date of Closing Price Equity Name Equity Volume Equity High Price Equity Low Price Equity Open Price Bond Name Bond Coupon Rate Bond Maturity Index Name Index Change Index Percent Change Exchange Currency Total Market Capitalization Dividend Yield Price-to-Earnings Ratio (P/E) ‍

Q&A:

1. How much does the End-of-Day Pricing Data cost in Ecuador ?

The cost of this dataset may vary depending on factors such as the number of data fields, the frequency of updates, and the total records count. For precise pricing details, it is recommended to directly consult with a Techsalerator Data specialist.

1. How complete is the End-of-Day Pricing Data coverage in Ecuador?

Techsalerator provides comprehensive coverage of End-of-Day Pricing Data for various financial instruments, including equities, bonds, and indices. Thedataset encompasses major companies and securities traded on Ecuador exchanges.

1. How does Techsalerator collect this data?

Techsalerator collects End-of-Day Pricing Data from reliable sources, including stock exchanges, financial news outlets, and other market data providers. Data is carefully curated to ensure accuracy and reliability.

1. Can I select specific financial instruments or multiple countries with Techsalerator's End-of-Day Pricing Data?

Techsalerator offers the flexibility to select specific financial instruments, such as equities, bonds, or indices, depending on your needs. While the dataset focuses on Botswana, Techsalerator also provides data for other countries and international markets....

Disclaimer!!! Data uploaded here are collected from the internet. The sole purposes of uploading these data are to provide this Kaggle community with a good source of data for analysis and research. I don't own these datasets and am also not responsible for them legally by any means. I am not charging anything (either monetary or any favor) for this dataset.

Overview

This dataset contains historical daily prices for indices currently trading on the Indian Stock Market. The historical data are retrieved from the NSE India website. Daily gold price from 1979 to 2022 in INR is uploaded here.

• Premier
  • PE, P/B, Div Yield Data.
  • Gold price to INR Data.

Content

This data contains daily OHLC data for all indices in NSE from 1990 to 2022. Along with Indices OHLC data, there are PE(Price to Earning ratio), P/B (Price to book value), and Dividend Yield data also available for all indices. Lastly, Volatility Index (VIX) data is also available from 1990 to 2022.

For Example - - "Nifty 50 data" contains the below columns: 1. Date - Date of observation 2. Open - Open price of the index on a particular day 3. High - High price of the index on a particular day 4. Low - Low price of the index on a particular day 5. Close - Close price of the index on a particular day - "NIFTY 50 - HistoricalPE_PBDIV_Data" contains the below columns: 1. Date - Date of observation 2. P/E - Price to Earnings Ratio 3. P/B - Price-to-book value 4. Div Yield % - Dividend Yield = Cash Dividend per share / Market Price per share * 100

• "Gold price INR.csv" contains Date and Gold price (INR per troy ounce). Where 1 Troy ounce = 31.1035 gram

The list of indices is: 1. NIFTY 50
2. NIFTY 100
3. NIFTY BANK
4. NIFTY COMMODITIES 5. NIFTY ENERGY
6. NIFTY FMCG 7. NIFTY HOUSING
8. NIFTY INDIA MANUFACTURING 9. NIFTY INFRASTRUCTURE
10. NIFTY IT 11. NIFTY MEDIA
12. NIFTY METAL 13. NIFTY MIDCAP 100
14. NIFTY NEXT 50 15. NIFTY OIL & GAS
16. NIFTY PHARMA 17. NIFTY PRIVATE BANK 18. NIFTY PSU BANK 19. NIFTY AUTO 20. VIX History

Inspiration

• Data is uploaded for Research and Educational purposes.
• The data scientists and researchers can download any index OHLC data, along with P/B, PE, and Dividend Yield values and VIX data.
• Even Gold prices can help researchers to get more insight into their investment decisions.
• A time series forecasting for future index price, based on multiple features along with OHLC data and P/B, P/E, and Div Yield percentage, VIX.

Data Source

For the gold price - https://gold.org For stock indices - https://www.niftyindices.com/reports/historical-data

The main stock market index of United States, the US500, rose to 6818 points on December 2, 2025, gaining 0.08% from the previous session. Over the past month, the index has declined 0.50%, though it remains 12.70% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on December of 2025.

We compile all return and macroeconomic data from Kenneth French's website and the OECD statistical data warehouse, respectively, for the period from January 1990 to December 2018. All return and macroeconomic data include the following countries: Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Netherlands, Norway, Portugal, Spain, Sweden, Switzerland and United Kingdom.The dataset comprises the following series:

1. Fama-French factors, 3-factor model, as provided by Kenneth French (Europe_3_Factors.txt).
2. Fama-French factors, 5-factor model, as provided by Kenneth French (Europe_5_Factors.txt).
3. Returns for 25 size-BE/ME portfolios, as provided by Kenneth French (Europe_25_Portfolios_ME_BE-ME.txt).
4. Returns for 25 size-momentum, as provided by Kenneth French (Europe_25_Portfolios_ME_Prior_12_2.txt).
5. Weighted average per capita consumption growth. We first collect quarterly chained volume estimates for consumption in nondurables and services, non-seasonally adjusted, in national currency, for the 16 countries under consideration (‘Non-durable goods’ and ‘Services’ series, LNBQR measure). Second, we use the population series provided by the OECD to determine per capita consumption growth series for each country. Finally, we estimate the average consumption growth for the economies under consideration, weighting by population (Europe_Consumption_Q.txt).
6. Weighted average consumer confidence index (CCI). We collect monthly CCI data as provided by the OECD (‘OECD Standardised CCI, Amplitude adjusted, sa’ series, dataset ‘Composite Leading Indicators’, MEI). We determine the average CCI for the economies under consideration, weighting by population (Europe_Indicators_Q.txt).

Ireland ISEQ Bonds: Irish Stock Exchange: Return Index: Under 5 Years data was reported at 168.400 30Jun2004=100 in Oct 2018. This records an increase from the previous number of 168.260 30Jun2004=100 for Sep 2018. Ireland ISEQ Bonds: Irish Stock Exchange: Return Index: Under 5 Years data is updated monthly, averaging 125.470 30Jun2004=100 from Mar 2003 (Median) to Oct 2018, with 188 observations. The data reached an all-time high of 169.420 30Jun2004=100 in Dec 2016 and a record low of 96.360 30Jun2004=100 in Mar 2003. Ireland ISEQ Bonds: Irish Stock Exchange: Return Index: Under 5 Years data remains active status in CEIC and is reported by Irish Stock Exchange. The data is categorized under Global Database’s Ireland – Table IE.Z001: Irish Stock Exchange: Index.

The yield on 10 Year TIPS Yield rose to 1.83% on December 1, 2025, marking a 0.07 percentage points increase from the previous session. Over the past month, the yield has edged up by 0.03 points, though it remains 0.10 points lower than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. This dataset includes a chart with historical data for the United States 10 Year TIPS Yield.

This release presents the main results from an analysis of the profitability and resilience of farms in England using data from the Farm Business Survey. Six measures have been examined; liabilities, net worth, gearing ratios, liquidity, net interest payments as a proportion of Farm Business Income and Return on Capital Employed (ROCE). Link to main notice: https://www.gov.uk/government/collections/farm-business-survey#documents Survey details The Farm Business Survey (FBS) is an annual survey providing information on the financial position and physical and economic performance of farm businesses in England. The sample of around 1,900 farm businesses covers all regions of England and all types of farming with the data being collected by face to face interview with the farmer. Results are weighted to represent the whole population of farm businesses that have at least 25 thousand Euros of standard output as recorded in the annual June Survey of Agriculture and Horticulture. In 2012 there were just over 56 thousand farm businesses meeting this criteria. The data used for this analysis is from only those farms present in the Farm Business Survey (FBS) for 2010/11 to 2012/13. Those entering or leaving the survey in this period have been excluded. The sub sample consists of around 1490 farms. For further information about the Farm Business Survey please see: https://www.gov.uk/government/organisations/department-for-environment-food-rural-affairs/series/farm-business-survey Data analysis The results from the FBS relate to farms which have a standard output of at least 25,000 Euros. Initial weights are applied to the FBS records based on the inverse sampling fraction for each design stratum (farm type by farm size). These weights are then adjusted (calibration weighting) so that they can produce unbiased estimators of a number of different target variables. All data in this release is based on farms present in the FBS for 2010/11 to 2012/13 and that have complete returns on their assets and liabilities. Those entering or leaving the survey in this period have been excluded. This sub sample consists of around 1490 farms. The results for this subsample have been reweighted using a method that preserves marginal totals for populations according to farm type and farm size groups. As such, farm population totals for other classifications (e.g. regions) will not be in-line with results using the main FBS weights, nor will any results produced for variables derived from the rest of the FBS (e.g. farm business income). Measures represent a three year average from 2010-2013, presented in 2012/2013 prices (uprated according to RPI inflation). This helps to stabilise the fluctuations in income that can significantly change the financial position of a farm from year to year. ? Accuracy and reliability of the results We show 95% confidence intervals against the results. These show the range of values that may apply to the figures. They mean that we are 95% confident that this range contains the true value. They are calculated as the standard errors (se) multiplied by 1.96 to give the 95% confidence interval (95% CI). The standard errors only give an indication of the sampling error. They do not reflect any other sources of survey errors, such as non-response bias. For the Farm Business Survey, the confidence limits shown are appropriate for comparing groups within the same year only; they should not be used for comparing with previous years since they do not allow for the fact that many of the same farms will have contributed to the Farm Business Survey in both years. We have also shown error bars on the figures in this notice. These error bars represent the 95% confidence intervals (as defined above). For the FBS, where figures are based on less than 5 observations these have been suppressed to prevent disclosure and where they are based on less than 15 observations these have been highlighted in the tables. Availability of results Defra statistical notices can be viewed on the Food and Farming Statistics pages on the Defra website at https://www.gov.uk/government/organisations/department-for-environment-food-rural-affairs/about/statistics. This site also shows details of future publications, with pre-announced dates. Definitions Mean The mean (average) is found by adding up the weighted variable of interest (e.g. liabilities or net worth) for each individual farm in the population for analysis and dividing the result by the corresponding weighted number of farms. In this report average is usually taken to refer to the mean. Percentiles These are the values which divide the population for analysis, when ranked by an output variable (e.g. ROCE or net worth), into 100 equal-sized groups. For example, twenty five per cent of the population would have incomes below the 25th percentile. Median The median divides the population, when ranked by an output variable, into two equal sized groups. The median of the whole population is the same as the 50th percentile. Farm Type Where reference is made to the type of farm in this document, this refers to the ‘robust type’, which is a standardised farm classification system. Farm Sizes Farm sizes are based on the estimated labour requirements for the business, rather than its land area. The farm size bands used within the detailed results tables which accompany this publication are shown in the table below. Standard Labour Requirement (SLR) is defined as the theoretical number of workers required each year to run a business, based on its cropping and livestock activities. Farm size Definition Spare & Part time Less than 1 SLR Small 1 to less than 2 SLR Medium 2 to less than 3 SLR Large 3 to less than 5 SLR Very Large 5 or more SLR Assets Assets include milk and livestock quotas, as well as land, buildings (including the farm house), breeding livestock, and machinery and equipment. For tenanted farmers, assets can include farm buildings, cottages, quotas, etc., where these are owned by the occupier. Personal possessions (e.g. jewellery, furniture, and possibly private cash) are not included. Net worth Net worth represents the residual claim or interest of the owner in the business. It is the balance sheet value of assets available to the owner of the business after all other claims against these assets have been met. Net worth takes total liabilities from total assets, including tenant type capital and land. This describes the wealth of a farm if all of their liabilities were called in.? Liabilities Liabilities are the total debt (short and long term) of the farm business including monies owed. It includes mortgages, long term loans and monies owed for hire purchase, leasing and overdrafts. Tenant type capital Tenant type capital comprises assets normally provided by tenants and includes livestock, machinery, crops and produce in store, stocks of bought and home-grown feeding stuffs and fodder, seeds, fertilisers, pesticides, medicines, fuel and other purchased materials, work in progress (tillages or cultivations), cash and other assets needed to run the business. Orchards, other permanent crops, such as soft fruit and hop gardens and glasshouses, are also generally considered to be tenant-type capital. Return on capital employed (ROCE) Return on capital employed (ROCE) is a measure of the return that a business makes from the available capital. ROCE provides a more holistic view than profit margins, focusing on efficient use of capital and low costs and allowing an equal comparison across farms of differing sizes. It is calculated as economic profit divided by capital employed. Liquidity ratio The liquidity ratio shows the ability of a farm to finance its immediate financial demands from its current assets, such as cash, savings or stock. It is calculated as current assets divided by the current liabilities of the farms. Gearing ratio The gearing ratio gives a farm’s liabilities as a proportion of its assets Farm business income (FBI) Farm Business Income (FBI) for sole traders and partnerships represents the financial return to all unpaid labour (farmers and spouses, non-principal partners and directors and their spouses and family workers) and on all their capital invested in the farm business, including land and buildings. For corporate businesses it represents the financial return on the shareholders capital invested in the farm business. Note that prior to 2008/09 directors remuneration was not deducted in the calculation of farm business income. It is used when assessing the impact of new policies or regulations on the individual farm business. Although Farm Business Income is equivalent to financial Net Profit, in practice they are likely to differ because Net Profit is derived from financial accounting principles whereas Farm Business Income is derived from management accounting principles. For example in financial accounting output stocks are usually valued at cost of production, whereas in management accounting they are usually valued at market price. In financial accounting depreciation is usually calculated at historic cost whereas in management accounting it is often calculated at replacement cost. Net Farm Income (NFI) Net Farm Income (NFI) is intended as a consistent measure of the profitability of tenant-type farming which allows farms of different business organisation, tenure and indebtedness to be compared. It represents the return to the farmer and spouse alone for their manual and managerial labour and on the tenant-type capital invested in the farm business. To represent the return to farmer and spouse alone, a notional deduction is made for any unpaid labour provided by non-principal partners and directors, their spouses and by others; this unpaid labour is valued at average local market rates for manual agricultural work. To confine the measure to the tenant-type activities and assets of the business, an imputed rent is deducted for owner-occupied land and

About this dataset

India's National Stock Exchange (NSE) has a total market capitalization of more than US$3.4 trillion, making it the world's 10th-largest stock exchange as of August 2021, with a trading volume of ₹8,998,811 crore (US$1.2 trillion) and more 2000 total listings.

NSE's flagship index, the NIFTY 50, is a 50 stock index is used extensively by investors in India and around the world as a barometer of the Indian capital market.

This dataset contains data of all company stocks listed in the NSE, allowing anyone to analyze and make educated choices about their investments, while also contributing to their countries economy.

How to use this dataset

• Create a time series regression model to predict NIFTY-50 value and/or stock prices.
• Explore the most the returns, components and volatility of the stocks.
• Identify high and low performance stocks among the list.

Highlighted Notebooks

• Your kernel can be featured here!
• Related Dataset: S&P 500 Stocks - daily updated
• More datasets

Acknowledgements

License

CC0: Public Domain

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Stonks by unknown memer.

Indo Gangetic plains of India. Hence, we evaluated long-term (10 years) effect of conservation agriculture (CA) practices on soil quality improvement under six different cropping scenarios (Sc), i.e. Sc1-represented by transplanted puddled rice (TPR) followed by conventional tilled broadcasted wheat (CT-wheat) with residue removal, Sc2-TPR rice followed by zero tillage (ZT) wheat and ZT-mung bean with partial residue retention, Sc3- direct seeded rice (DSR) followed by ZT-wheat and ZT-mung bean with full residue retention, Sc4-DSR is replaced by ZT-maize followed by ZT-wheat and ZT-mung bean, Sc5 and Sc6 were – Sc3 integrated with sub surface drip irrigation (SDI) and Sc4 + SDI, respectively. Soil samples were collected from 0 to 5, 5–15 and 15–30 cm soil depth from each scenario after harvesting of wheat in 2019. Results showed that, reduction in bulk density (BD), soil penetration resistance (SPR) and enhancement of water holding capacity and infiltration were associated with CA based scenarios (Sc3–Sc6). Scenario 3 recorded lowest BD of 1.39 and 1.58 g cm􀀀 3 at 0–5 and 5–15 cm soil depth, respectively. CA based Sc6 recorded highest infiltration rate (1.48 cm hr􀀀 1) and lowest was associated with Sc1 (0.5 cm hr􀀀 1). The enrichment of soil organic carbon (SOC) content, stock, available nitrogen and potassium was mainly confined to upper surface soil layer (0–5 cm). The SOC content and stock in CA based scenarios (average of Sc3 to Sc6) was 41–57 and 69–94% higher than Sc1 at 0–5 cm soil layer. Available nitrogen was increased by 23–50 and 64–98% and available potassium increased by 13–28 and 42–71% in 0–5 and 5–15 cm soil depth, respectively in CA based scenarios over Sc1. Similarly, microbial biomass carbon (MBC) and dehydrogenase (DHA) activity in top soil layer under CA based scenarios was increased by 177–195 and 67–107% over Sc1, respectively. The maximum SQI was registered with Sc6 (0.91) followed by Sc4 (0.89) and least was recorded in Sc1 (0.65) at 0–5 cm soil depth. Maize-wheat based cropping system recorded higher SQI over rice–wheat based cropping system. Sustainable yield index was strongly related with key soil quality indicators and also positively correlated with SQI. Thus our study suggests that CA based maize-wheat-mung bean cropping system should be recommended for better soil quality and yield sustainability in North West India.

A table that shows in detail by CUSIP, the interest rate, the STRIP CUSIP, maturity date, and amounts outstanding for securities held in unstripped form, stripped form and amount that have been reconstituted. STRIP stands for Separate Trading of Registered Interest and Principal of Securities. This is a security that has been stripped down into separate securities representing the principal and each interest payment. Each payment has its own identification number and can be traded individually. These securities are also known as zero-coupon bonds.

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The Coca-Cola Company is an North American multinational beverage corporation incorporated under Delaware's General Corporation Law[a] and headquartered in Atlanta, Georgia. The Coca-Cola Company has interests in the manufacturing, retailing, and marketing of non-alcoholic beverage concentrates and syrups, and alcoholic beverages. The company produces Coca-Cola, the sugary drink for which it is best known for, invented in 1886 by pharmacist John Stith Pemberton. At the time, the product was made with coca leaves, which added an amount of cocaine to the drink, and with kola nuts, which added caffeine, so that the coca and the kola together provided a stimulative effect. This stimulative effect is the reason the drink was sold to the public as a healthy "tonic", and the coca and the kola are also the source of the name of the product and of the company.In 1889, the formula and brand were sold for $2,300 (roughly $68,000 in 2021) to Asa Griggs Candler, who incorporated The Coca-Cola Company in Atlanta in 1892.

Since 1919, Coca-Cola has been a publicly traded company. Its stock is listed on the New York Stock Exchange under the ticker symbol "KO". One share of stock purchased in 1919 for $40, with all dividends reinvested, would have been worth $9.8 million in 2012, a 10.7% annual increase adjusted for inflation. A predecessor bank of SunTrust received $100,000 for underwriting Coca-Cola's 1919 public offering; the bank sold that stock for over $2 billion in 2012. In 1987, Coca-Cola once again became one of the 30 stocks which makes up the Dow Jones Industrial Average, which is commonly referenced as a proxy for stock market performance; it had previously been a Dow stock from 1932 to 1935. Coca-Cola has paid a dividend since 1920 and, as of 2019, had increased it each year for 57 years straight.

The yield on US 2 Year Note Bond Yield eased to 3.54% on December 2, 2025, marking a 0.01 percentage points decrease from the previous session. Over the past month, the yield has fallen by 0.08 points and is 0.65 points lower than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. US 2 Year Treasury Bond Note Yield - values, historical data, forecasts and news - updated on December of 2025.

The yield on China 10Y Bond Yield held steady at 1.83% on December 2, 2025. Over the past month, the yield has edged up by 0.07 points, though it remains 0.16 points lower than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. China 10-Year Government Bond Yield - values, historical data, forecasts and news - updated on December of 2025.

Japan's main stock market index, the JP225, rose to 49553 points on December 2, 2025, gaining 0.51% from the previous session. Over the past month, the index has declined 3.78%, though it remains 26.25% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Japan. Japan Stock Market Index (JP225) - values, historical data, forecasts and news - updated on December of 2025.

The yield on Singapore 10Y Bond Yield eased to 2.15% on December 2, 2025, marking a 0.01 percentage points decrease from the previous session. Over the past month, the yield has edged up by 0.21 points, though it remains 0.54 points lower than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. Singapore 10Y Bond Yield - values, historical data, forecasts and news - updated on December of 2025.