The yield on US 30 Year Bond Yield rose to 4.71% on September 30, 2025, marking a 0 percentage point increase from the previous session. Over the past month, the yield has fallen by 0.25 points, though it remains 0.64 points higher than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. United States 30 Year Bond Yield - values, historical data, forecasts and news - updated on September of 2025.

The benchmark interest rate In the Euro Area was last recorded at 2.15 percent. This dataset provides - Euro Area Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The benchmark interest rate in Sweden was last recorded at 1.75 percent. This dataset provides the latest reported value for - Sweden Interest Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This data set contains the U.S. Treasury yield curve rates on a daily basis for a variety of maturities ranging from 1-month bills to 30-year bonds. Panel-formatted, it can be used for analyses of term structures of interest rates, forecasting of monetary policy, and time-series analysis of sovereign risk-free standards. It is especially appropriate for empirical applications of finance including bond pricing, cost of borrowing by municipalities, and macro-financial risk measurement.

The yield on US 10 Year Note Bond Yield rose to 4.16% on October 1, 2025, marking a 0.01 percentage points increase from the previous session. Over the past month, the yield has fallen by 0.11 points, though it remains 0.37 points higher 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 October of 2025.

This table contains 71 series, with data starting from 1934 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Rates (71 items: Bank rate; last Tuesday or last Thursday; Bank rate; Chartered bank administered interest rates - prime business; Chartered bank - consumer loan rate ...).

The dataset used in the paper is a set of synthetic financial data, including option prices, underlying asset prices, strike prices, expiration times, risk-free interest rates, and volatility.

The yield on Japan 10Y Bond Yield held steady at 1.65% on September 30, 2025. Over the past month, the yield has edged up by 0.03 points and is 0.80 points higher than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. Japan 10 Year Government Bond Yield - values, historical data, forecasts and news - updated on September of 2025.

The benchmark interest rate in Japan was last recorded at 0.50 percent. This dataset provides - Japan Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Monthly t​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​echnical information relating to risk-free interest rate (RFR) term structures is used for the calculation of the technical provisions for (re)insurance obligations across Europe and contributes to higher supervisory convergence for the benefit of the European insurance policyholders.

1. Data Source

This dataset is a synthetic version inspired by the original Credit Risk dataset on Kaggle and enriched with additional variables based on Financial Risk for Loan Approval data. SMOTENC was used to simulate new data points to enlarge the instances. The dataset is structured for both categorical and continuous features.

2. Metadata

The dataset contains 45,000 records and 14 variables, each described below:

3. Data Usage

The dataset can be used for multiple purposes:

• Exploratory Data Analysis (EDA): Analyze key features, distribution patterns, and relationships to understand credit risk factors.
• Classification: Build predictive models to classify the loan_status variable (approved/not approved) for potential applicants.
• Regression: Develop regression models to predict the credit_score variable based on individual and loan-related attributes.

Mind the data issue from the original data, such as the instance > 100-year-old as age.

This dataset provides a rich basis for understanding financial risk factors and simulating predictive modeling processes for loan approval and credit scoring.

Feel free to leave comments on the discussion. I'd appreciate your upvote if you find my dataset useful! 😀

Dataset Description: 34-year Daily Stock Data (1990-2024)

Context and Inspiration

This dataset captures historical financial market data and macroeconomic indicators spanning over three decades, from 1990 onwards. It is designed for financial analysis, time series forecasting, and exploring relationships between market volatility, stock indices, and macroeconomic factors. This dataset is particularly relevant for researchers, data scientists, and enthusiasts interested in studying: - Volatility forecasting (VIX) - Stock market trends (S&P 500, DJIA, HSI) - Macroeconomic influences on markets (joblessness, interest rates, etc.) - The effect of geopolitical and economic uncertainty (EPU, GPRD)

Sources

The data has been aggregated from a mix of historical financial records and publicly available macroeconomic datasets: - VIX (Volatility Index): Chicago Board Options Exchange (CBOE). - Stock Indices (S&P 500, DJIA, HSI): Yahoo Finance and historical financial databases. - Volume Data: Extracted from official exchange reports. - Macroeconomic Indicators: Bureau of Economic Analysis (BEA), Federal Reserve, and other public records. - Uncertainty Metrics (EPU, GPRD): Economic Policy Uncertainty Index and Global Policy Uncertainty Database.

Columns

1. dt: Date of observation in YYYY-MM-DD format.
2. vix: VIX (Volatility Index), a measure of expected market volatility.
3. sp500: S&P 500 index value, a benchmark of the U.S. stock market.
4. sp500_volume: Daily trading volume for the S&P 500.
5. djia: Dow Jones Industrial Average (DJIA), another key U.S. market index.
6. djia_volume: Daily trading volume for the DJIA.
7. hsi: Hang Seng Index, representing the Hong Kong stock market.
8. ads: Aruoba-Diebold-Scotti (ADS) Business Conditions Index, reflecting U.S. economic activity.
9. us3m: U.S. Treasury 3-month bond yield, a short-term interest rate proxy.
10. joblessness: U.S. unemployment rate, reported as quartiles (1 represents lowest quartile and so on).
11. epu: Economic Policy Uncertainty Index, quantifying policy-related economic uncertainty.
12. GPRD: Geopolitical Risk Index (Daily), measuring geopolitical risk levels.
13. prev_day: Previous day’s S&P 500 closing value, added for lag-based time series analysis.

Key Features

• Cross-Market Analysis: Compare U.S. markets (S&P 500, DJIA) with international benchmarks like HSI.
• Macroeconomic Insights: Assess how external factors like joblessness, interest rates, and economic uncertainty affect markets.
• Temporal Scope: Longitudinal data facilitates trend analysis and machine learning model training.

Potential Use Cases

• Forecasting market indices using machine learning or statistical models.
• Building volatility trading strategies with VIX Futures.
• Economic research on relationships between policy uncertainty and market behavior.
• Educational material for financial data visualization and analysis tutorials.

Feel free to use this dataset for academic, research, or personal projects.

This table contains 39 series, with data for starting from 1991 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada); Financial market statistics (39 items: Government of Canada Treasury Bills, 1-month (composite rates); Government of Canada Treasury Bills, 2-month (composite rates); Government of Canada Treasury Bills, 3-month (composite rates);Government of Canada Treasury Bills, 6-month (composite rates); ...).

The yield on Germany 10Y Bond Yield eased to 2.75% on September 26, 2025, marking a 0.03 percentage point decrease from the previous session. Over the past month, the yield has edged up by 0.05 points and is 0.61 points higher than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. Germany 10-Year Bond Yield - values, historical data, forecasts and news - updated on September of 2025.

China Bond Yield: Treasury Bond: 10 Year data was reported at 1.679 % pa in 16 May 2025. This records a decrease from the previous number of 1.680 % pa for 15 May 2025. China Bond Yield: Treasury Bond: 10 Year data is updated daily, averaging 3.254 % pa from Mar 2006 (Median) to 16 May 2025, with 4806 observations. The data reached an all-time high of 4.722 % pa in 20 Nov 2013 and a record low of 1.596 % pa in 06 Feb 2025. China Bond Yield: Treasury Bond: 10 Year data remains active status in CEIC and is reported by China Central Depository & Clearing Co., Ltd. The data is categorized under China Premium Database’s Money Market, Interest Rate, Yield and Exchange Rate – Table CN.MF: PBC & CCDC: Treasury Bond and Other Bond Yield: Daily.

The benchmark interest rate in Taiwan was last recorded at 2 percent. This dataset provides the latest reported value for - Taiwan Interest Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Projekt 1: The study conducts an online experiment employing a 2x2+1 between-subjects design. Participants assume the role of investors and have to invest a budget in two firms. For this purpose, the participants receive 1,000 coins they have to invest in two firms in steps of 1 coin. Before ending the experiment, participants answer follow-up questions. Participants are recruited from the crowdsourcing platform Prolific. Projekt 2: The study uses intraday stock returns in 5-minute intervals taken from kibot.com. Daily and monthly returns are taken from CRSP and data on company fundamentals from Compustat. Risk-free rates, the market factor, as well as the Fama-French factors are taken from the data library of Kenneth French. In addition, the study uses options data provided by Historical Option Data. Projekt 3: Monthly returns are taken from CRSP. Risk-free rates and the market factor are obtained from Kenneth French's data library. The study uses options data, which are sourced from Historical Option Data. In addition, the study employs firm characteristics, which can be downloaded from openassetpricing.com.

Free-Cash-Flow-To-The-Firm Time Series for Bank of Montreal. Bank of Montreal provides diversified financial services primarily in North America. It operates through Canadian P&C, U.S P&C, BMO Wealth Management, and BMO Capital Markets segments. The company's personal banking products and services include deposits, mortgages, home lending, consumer credit, small business lending, credit cards, cash management, financial and investment advice, and other banking services; and commercial banking products and services comprise various of financing options and treasury and payment solutions, as well as risk management products. It also offers investing, banking, and wealth management advisory; digital investing services; financial solutions for individuals, families, and businesses; provides investment management services to institutional, retail, and high net worth investors; and diversified insurance, and wealth and pension de-risking solutions. In addition, the company provides individual life, critical illness and annuity products, as well as segregated funds, and group creditor and travel insurance to customers; debt and equity capital-raising, loan origination and syndication, balance sheet management, treasury management, mergers and acquisitions advice, restructurings and recapitalizations, trade finance, and risk mitigation services, as well as a range of banking and other operating services. Further, the company offers research and access to financial markets for institutional, corporate and retail clients through an integrated suite of sales and trading solutions related to debt, foreign exchange, interest rates, credit, equities, securitization, and commodities; provides new product development and origination services, as well as risk management and advisory services for hedging strategies, including in interest rates, foreign exchange rates and commodities prices; and funding and liquidity management services. Bank of Montreal was founded in 1817 and is headquartered in Montreal, Canada.

The benchmark interest rate in Indonesia was last recorded at 4.75 percent. This dataset provides - Indonesia Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The benchmark interest rate in Mexico was last recorded at 7.50 percent. This dataset provides - Mexico Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.