Graph and download economic data for from Jan 1948 to Jan 1967 about bonds, yield, interest rate, interest, rate, and USA.

Graph and download economic data for Index of Yields of High Grade Municipal Bonds for United States (M13023USM156NNBR) from Jan 1900 to Apr 1967 about grades, bonds, yield, interest rate, interest, rate, indexes, and USA.

The yield on US 30 Year Bond Yield eased to 4.89% on August 22, 2025, marking a 0.03 percentage point decrease from the previous session. Over the past month, the yield has fallen by 0.05 points, though it remains 0.80 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 August of 2025.

This dataset compiles national-level municipal bond issuance and pricing statistics for the United States, sourced from the Securities Industry and Financial Markets Association (SIFMA). It includes time-series data on municipal bond issuance volumes, average yields, interest rates, and maturity structures, aggregated on a monthly and annual basis. The dataset provides critical macro-financial context for evaluating subnational debt trends, especially in the context of climate adaptation investments and fiscal resilience. In particular, it supports comparative analysis between local climate-related borrowing (e.g., FEMA-backed projects) and national municipal debt trends, serving as a benchmark for assessing changes in risk premiums, cost of capital, and investor behavior. This file was used to calibrate yield spreads in empirical models evaluating the market response to federally co-funded nature-based infrastructure.

The SIFMA Municipal Swap Index, formerly the Bond Market Association Index, is a market index composed of tax-exempt variable rate demand obligations (VRDOs). VRDOs are municipal bonds with floating interest rates. The SIFMA index is issued weekly.

The SIFMA rate for each interest payment period is equal to the weighted average of the SIFMA index value. Both SIFMA and LIBOR are popular floating rate index. The SIFMA rate represents the average interest rate payable on tax-exempt variable rate demand obligations, while the LIBOR rate represents the interest rate payable on non-tax exempt demand obligations. In general, the SIFMA rate trades as a proportion of LIBOR rate.

The coupon rates of many floating rate bonds or floating rate callable bonds refer to SIFMA index. The change of index has quite impact on the bond values. Thus, the SIFMA curve is major used to price various bonds, such as municipal bonds, municipal debts, bond purchase agreements, etc.

Graph and download economic data for Bond Buyer Go 20-Bond Municipal Bond Index (DISCONTINUED) (WSLB20) from 1953-01-01 to 2016-10-06 about municipal, state & local, bonds, government, indexes, and USA.

Both climate risk and race are factors that may affect municipal bond yields, yet each has received relatively limited empirical research attention. We analyzed > 712,000 municipal bonds representing nearly 2 trillion USD in par outstanding, focusing on credit spread or the difference between a debt issuer’s interest cost to borrow and a benchmark “risk-free” municipal rate. The relationship between credit spread and physical climate risk is significant and slightly positive, yet the coefficient indicates no meaningful spread penalty for increased physical climate risk. We also find that racial composition (the percent of a community that is Black) explains a statistically significant and meaningful portion of municipal credit spreads, even after controlling for a variety of variables in domains such as geographic location of issuer, bond structure (e.g., bond maturity), credit rating, and non-race economic variables (e.g., per capita income). Assuming 4 trillion USD in annual outstanding par across the entire municipal market, and weighting each issuer by its percent Black, an estimated 19 basis point (bp) penalty for Black Americans sums to approximately 900 million USD annually in aggregate. Our combined findings indicate a systemic mispricing of risk in the municipal bond market, where race impacts the cost of capital, and climate does not.

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.

BBN BlackRock Taxable Municipal Bond Trust Common Shares of Beneficial Interest

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

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.

Invesco Trust (VGM) Municipal Bonds: A Safe Haven in Uncertain Times

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

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.

Will MFS (CXH) Municipal Bonds Recover?

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

This is a dataset of General Obligation, Dormitory Authority of the State of New York, and the New York City Municipal Water Finance Authority Interest Rate Exchange Agreements. This data set provides information on interest rate exchange agreements. Note: Mark-to-Market Values are calculated by a third-party swap adviser.

Fixed Income Asset Management Market Outlook

The global fixed income asset management market size was valued at approximately USD 5.7 trillion in 2023 and is projected to grow to USD 9.3 trillion by 2032, expanding at a compound annual growth rate (CAGR) of 5.5% over the forecast period. The growth of this market is primarily driven by the increasing demand for stable and predictable returns in an uncertain economic environment.

One of the significant growth factors for the fixed income asset management market is the aging global population. As more individuals approach retirement age, the demand for fixed income investments that offer stable returns and lower risk compared to equities is increasing. Retirees and near-retirees often prioritize capital preservation and income generation, which fixed income products are well-suited to provide. This demographic trend is particularly prominent in developed countries but is also becoming more relevant in emerging markets as their populations age and accumulate wealth.

Another crucial growth driver is the rising interest rate environment. As central banks around the world shift towards tightening monetary policies to combat inflation, interest rates are gradually increasing. Higher interest rates make newly issued bonds more attractive to investors due to their higher yields. This situation creates opportunities for fixed income asset managers to attract new investments and cater to clients looking for better returns in a higher interest rate environment. Additionally, higher yields can enhance the overall performance of fixed income portfolios, making them more appealing to both institutional and retail investors.

The increasing complexity and diversity of fixed income products is also contributing to market growth. The fixed income market has evolved to include a wide range of instruments beyond traditional government and corporate bonds. Products such as mortgage-backed securities, municipal bonds, and various structured financial instruments offer different risk-return profiles and investment opportunities. This diversification allows asset managers to tailor portfolios to meet specific client needs and preferences, thereby attracting a broader investor base. The development of innovative fixed income products continues to drive growth in this market by expanding the range of investment options available.

In the realm of private equity, the PE Fund Management Fee plays a crucial role in shaping the investment landscape. These fees are typically charged by fund managers to cover the operational costs of managing the fund, including research, administration, and portfolio management. The structure of these fees can vary, often comprising a management fee based on the committed capital and a performance fee tied to the fund's returns. Understanding the intricacies of these fees is essential for investors, as they can significantly impact the net returns on their investments. As private equity continues to grow as an asset class, the transparency and justification of management fees are becoming increasingly important to investors seeking to maximize their returns while ensuring alignment of interests with fund managers.

From a regional perspective, North America remains the largest market for fixed income asset management, driven by the presence of a well-established financial industry, a large pool of institutional investors, and a high level of individual wealth. However, the Asia Pacific region is expected to exhibit the highest growth rate during the forecast period. Rapid economic growth, increasing financial literacy, and a burgeoning middle class are driving demand for fixed income investments in countries such as China and India. Additionally, regulatory reforms aimed at developing local bond markets and attracting foreign investment are further propelling the market in this region.

Asset Type Analysis

The fixed income asset management market can be categorized by asset type into government bonds, corporate bonds, municipal bonds, mortgage-backed securities, and others. Each of these asset types offers unique characteristics and appeals to different segments of investors, contributing to the overall growth and diversification of the market.

Government bonds are one of the most significant segments in the fixed income market. Issued by national governments, these bonds are considered low-risk investments due to the backing of the issuing g

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Fixed Income Assets Management Market Size 2025-2029

The fixed income assets management market size is forecast to increase by USD 9.16 tr at a CAGR of 6.3% between 2024 and 2029.

The market is experiencing significant growth, driven by increasing investor interest in fixed income securities as a hedge against market volatility. A key trend in this market is the expansion of bond Exchange-Traded Funds (ETFs), which offer investors liquidity, diversification, and cost savings. However, this market is not without risks. Transactions in fixed income assets involve complexities such as credit risk, interest rate risk, and liquidity risk, which require sophisticated risk management strategies. As global investors seek to capitalize on market opportunities and navigate these challenges effectively, they must stay informed of regulatory changes, market trends, and technological advancements. Companies that can provide innovative solutions for managing fixed income risks and optimizing returns will be well-positioned to succeed in this dynamic market.

What will be the Size of the Fixed Income Assets Management Market during the forecast period?

Request Free SampleThe fixed income assets market in the United States continues to be an essential component of investment portfolios for various official institutions and individual investors. With an expansive market size and growth, fixed income securities encompass various debt instruments, including corporate bonds and government treasuries. Interest rate fluctuations significantly impact this market, influencing investment decisions and affecting the returns from interest payments on these securities. Fixed income Exchange-Traded Funds (ETFs) and index managers have gained popularity due to their cost-effective and diversified investment options. However, the credit market volatility and associated default risk pose challenges for investors. In pursuit of financial goals, investors often choose fixed income funds over equities for their stable dividend income and tax savings benefits. Market risk and investors' risk tolerance are crucial factors in managing fixed income assets. Economic uncertainty and interest rate fluctuations necessitate active management by asset managers, hedge funds, and mutual funds. The fund maturity and investors' financial goals influence the choice between various fixed income securities, such as treasuries and loans. Despite the challenges, the market's direction remains positive, driven by the continuous demand for income-generating investments.

How is this Fixed Income Assets Management Industry segmented?

The fixed income assets management industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD tr' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. TypeCoreAlternativeEnd-userEnterprisesIndividualsGeographyNorth AmericaUSCanadaEuropeFranceGermanyItalyUKAPACChinaIndiaJapanSouth KoreaSouth AmericaMiddle East and Africa

By Type Insights

The core segment is estimated to witness significant growth during the forecast period.The fixed income asset management market encompasses a diverse range of investment vehicles, including index investing, pension funds, official institutions, mutual funds, investment advisory services, and hedge funds. This asset class caters to income holders with varying risk tolerances, offering securities such as municipal bonds, government bonds, and high yield bonds through asset management firms. Institutional investors, insurance companies, and corporations also play significant roles in this sector. Fixed income securities, including Treasuries, municipal bonds, corporate bonds, and debt securities, provide regular interest payments and can offer tax savings, making them attractive for investors with financial goals. However, liquidity issues and credit market volatility can pose challenges. The Federal Reserve's interest rate decisions and economic uncertainty also impact the fixed income market. Asset management firms employ various strategies, such as the core fixed income (CFI) strategy, which invests in a mix of investment-grade fixed-income securities. CFI strategies aim to deliver consistent performance by carefully managing portfolios, considering issuer creditworthiness, maturity, and jurisdiction. Fixed income funds, including government bonds and corporate bonds, offer lower market risk compared to equities. Investors can choose from various investment vehicles, including mutual funds, ETFs, and index funds managed by active managers or index managers. Fixed income ETFs, in particular, provide investors with the benefits of ETFs, such as liquidity and transparency, while offering exposure to the fixed income market. Despite market risks and liquidity issues, the fixed income asset management market continues to be

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.

MFS Investment Grade Municipal Trust (CXH): Steadiness in Municipal Bonds?

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

Techsalerator offers an extensive dataset of End-of-Day Pricing Data for all 14 companies listed on the Dominican Republic Stock Exchange (XBVR) in Dominican Republic. 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.

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

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.

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

Dow Jones Dominican Republic Index: The Dow Jones Dominican Republic Index represents the performance of companies listed on the Dominican Republic Stock Exchange (Bolsa de Valores de la República Dominicana). It serves as a benchmark for tracking the overall market performance in the country.

Banco Popular Dominicano: Banco Popular Dominicano is one of the largest banks in the Dominican Republic, offering a range of banking and financial services to individuals and businesses. The securities of Banco Popular Dominicano are actively traded on the Dominican Republic Stock Exchange.

Grupo Financiero BHD León: Grupo Financiero BHD León is a financial group that operates in the Dominican Republic, providing banking, insurance, and financial services. The securities of Grupo Financiero BHD León are listed and traded on the Dominican Republic Stock Exchange.

Banco de Reservas de la República Dominicana: Banco de Reservas, also known as Banreservas, is the state-owned bank of the Dominican Republic. It offers a wide range of banking and financial services to customers. The securities of Banreservas are listed on the Dominican Republic Stock Exchange.

Altice Dominicana: Altice Dominicana is a subsidiary of Altice Group, a multinational telecommunications company. Altice Dominicana provides telecommunication services in the Dominican Republic. The securities of Altice Dominicana are listed and traded on the Dominican Republic Stock Exchange.

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If you're interested in accessing Techsalerator's End-of-Day Pricing Data for Dominican Republic, 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.

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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 Dominican Republic ?

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 Dominican Republic?

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 Dominican Republic 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...

Techsalerator offers an extensive dataset of End-of-Day Pricing Data for all 1000 companies listed on the Cayman Islands Stock Exchange (XCAY) in Cayman Islands. 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 Cayman Islands :

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.

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

Cayman Islands Stock Exchange (CSX) Domestic Company Index: The main index that tracks the performance of domestic companies listed on the Cayman Islands Stock Exchange. This index provides insights into the overall market performance of companies based in the Cayman Islands.

Cayman Islands Stock Exchange (CSX) Foreign Company Index: The index that tracks the performance of foreign companies listed on the Cayman Islands Stock Exchange. This index reflects the performance of international companies that are listed and traded on the CSX.

Financial Services Corporation Cayman Trust Bank: A major financial institution based in the Cayman Islands, offering banking, investment, and wealth management services. This company's securities are listed and traded on the CSX.

Real Estate Development Group Cayman Properties: A prominent real estate development company operating in the Cayman Islands, involved in the construction of residential and commercial properties. This company's securities are listed on the CSX.

Offshore Investment Fund Cayman Capital: An offshore investment fund registered in the Cayman Islands, offering investment opportunities to both local and international investors. Units of this fund are traded on the CSX.

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If you're interested in accessing Techsalerator's End-of-Day Pricing Data for Cayman Islands, 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 Cayman Islands ?

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 Cayman Islands?

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 Cayman Islands 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 Botsw...

The U.S. dollar was the currency most commonly used for deals on the international debt capital market in the fourth quarter of 2024. At that time, the value of deals in that currency was 639 billion U.S. dollars. What is debt capital market? The debt market is the part of the capital market on which fixed-interest securities are traded. These securities include, for example, government, municipal, corporate or mortgage bonds. It allows the companies and governments to raise capital through issuance of debt securities. In case a company or a government decides to collect additional money on debt capital market, it issues debt securities and sells them to investors. Depending on financial situation of the company issued bonds can obtain different ratings. The better the company is perceived in the market, the lower interest rates it has to pay for raised capital. Other ways of raising capital Some companies can access money via venture capital or private equity funding, where money comes from high net worth individuals, investment funds, banks or other financial institutions. For larger and well-established companies going public can be an option and raising money among investors. This process is called initial public offering (IPO).

SPDR Nuveen Bloomberg Municipal Bond ETF PE ratio as of July 06, 2025 is 0.00. Current and historical p/e ratio for SPDR Nuveen Bloomberg Municipal Bond ETF (TFI) from 1970 to 1969. The price to earnings ratio is calculated by taking the latest closing price and dividing it by the most recent earnings per share (EPS) number. The PE ratio is a simple way to assess whether a stock is over or under valued and is the most widely used valuation measure. Please refer to the Stock Price Adjustment Guide for more information on our historical prices.

Techsalerator offers an extensive dataset of End-of-Day Pricing Data for all 214 companies listed on the Panama Stock Exchange (XPTY) in Panama. 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 Panama:

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 Panama:

Panamanian Stock Exchange Domestic Company Index: The main index that tracks the performance of domestic companies listed on the Panamanian Stock Exchange (Bolsa de Valores de Panamá). This index provides an overview of the overall market performance in Panama.

Panamanian Stock Exchange Foreign Company Index: The index that tracks the performance of foreign companies listed on the Panamanian Stock Exchange. This index reflects the performance of international companies operating in Panama.

Company A: A prominent Panamanian company with diversified operations across various sectors, such as shipping, logistics, or finance. This company's stock is widely traded on the Panamanian Stock Exchange.

Company B: A leading financial institution in Panama, offering banking, insurance, or investment services. This company's stock is actively traded on the Panamanian Stock Exchange.

Company C: A major player in the Panamanian energy or real estate sector, involved in the production and distribution of related products. This company's stock is listed and actively traded on the Panamanian Stock Exchange.

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If you're interested in accessing Techsalerator's End-of-Day Pricing Data for Panama, 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 Panama ?

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 Panama?

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 Panama 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.

1. How do I pay for this dataset?

Techsalerator accepts various payment methods, including credit cards, direc...

Analysis of ‘NYC Quarterly Bond Update: General Obligation, DASNY, and the NYCMW Rate Exchange Agreements’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/e2ddd773-6ac7-42d9-bfd0-2c06bc1b57d0 on 27 January 2022.

--- Dataset description provided by original source is as follows ---

This is a dataset of General Obligation, Dormitory Authority of the State of New York, and the New York City Municipal Water Finance Authority Interest Rate Exchange Agreements.

This data set provides information on outstanding New York city bonds, interest rate exchange agreements, and projected debt service on those bonds.

Note: In the Table "General Obligation, Dormitory Authority of the State of New York, and the New York City Municipal Water Finance Authority Interest Rate Exchange Agreements",*Mark-to-Market Values are calculated by a third party swap adviser, Mohanty Gargiulo LLC.

--- Original source retains full ownership of the source dataset ---