From January 2020 through January 2025, the value of money market funds under management in the United Kingdom (UK) remained relatively stable aside from one notable spike in value in October 2022, by January 2023, however, the spike had subsided, and fund levels had fallen below ** million British pounds.

How are money market yields linked to inflation? The money market yields are influenced by inflation expectations. When inflation expectations rise, investors typically demand higher nominal yields to offset the anticipated decline in purchasing power. Market sentiment regarding inflation is reflected in these yields, which act as indicators for both investors and policymakers. The inflation rate for the Consumer Price Index (CPI) in the United Kingdom went from under *** percent in March 2021 to a high of **** percent in October 2022. Although inflation declined to *** percent in October 2023, it remained well above the levels seen before 2021. Consequently, a significant increase in money market yields was observed. Beginning in 2022, the monthly average yields from the British government bonds continued to rise until they reached their peak in mid-2023, indicating higher inflation expectations.

What is LIBOR? The London Interbank Offered Rate, or LIBOR, is a benchmark interest rate that reflects the average interest rate at which major global banks lend to each other in the interbank market. It is used to establish interest rates for financial instruments such as adjustable-rate mortgages, business loans, and derivatives. The six-month overnight London Interbank Offered Rate based on the British pound increased month by month from 2022 onwards, reaching its peak in March 2023 at **** percent. This increase in borrowing costs has a ripple effect throughout the financial system, which means higher interest rates for businesses and consumers overall.

Context

The Federal Reserve sets interest rates to promote conditions that achieve the mandate set by the Congress — high employment, low and stable inflation, sustainable economic growth, and moderate long-term interest rates. Interest rates set by the Fed directly influence the cost of borrowing money. Lower interest rates encourage more people to obtain a mortgage for a new home or to borrow money for an automobile or for home improvement. Lower rates encourage businesses to borrow funds to invest in expansion such as purchasing new equipment, updating plants, or hiring more workers. Higher interest rates restrain such borrowing by consumers and businesses.

Content

This dataset includes data on the economic conditions in the United States on a monthly basis since 1954. The federal funds rate is the interest rate at which depository institutions trade federal funds (balances held at Federal Reserve Banks) with each other overnight. The rate that the borrowing institution pays to the lending institution is determined between the two banks; the weighted average rate for all of these types of negotiations is called the effective federal funds rate. The effective federal funds rate is determined by the market but is influenced by the Federal Reserve through open market operations to reach the federal funds rate target. The Federal Open Market Committee (FOMC) meets eight times a year to determine the federal funds target rate; the target rate transitioned to a target range with an upper and lower limit in December 2008. The real gross domestic product is calculated as the seasonally adjusted quarterly rate of change in the gross domestic product based on chained 2009 dollars. The unemployment rate represents the number of unemployed as a seasonally adjusted percentage of the labor force. The inflation rate reflects the monthly change in the Consumer Price Index of products excluding food and energy.

Acknowledgements

The interest rate data was published by the Federal Reserve Bank of St. Louis' economic data portal. The gross domestic product data was provided by the US Bureau of Economic Analysis; the unemployment and consumer price index data was provided by the US Bureau of Labor Statistics.

Inspiration

How does economic growth, unemployment, and inflation impact the Federal Reserve's interest rates decisions? How has the interest rate policy changed over time? Can you predict the Federal Reserve's next decision? Will the target range set in March 2017 be increased, decreased, or remain the same?

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

U.S. Economic and Financial Dataset

Dataset Description

This dataset combines historical U.S. economic and financial indicators, spanning the last 50 years, to facilitate time series analysis and uncover patterns in macroeconomic trends. It is designed for exploring relationships between interest rates, inflation, economic growth, stock market performance, and industrial production.

Key Features

• Frequency: Monthly
• Time Period: Last 50 years from Nov-24
• Sources:
  • Federal Reserve Economic Data (FRED)
  • Yahoo Finance

Dataset Feature Description

1. Interest Rate (Interest_Rate):

   • The effective federal funds rate, representing the interest rate at which depository institutions trade federal funds overnight.

2. Inflation (Inflation):

   • The Consumer Price Index for All Urban Consumers, an indicator of inflation trends.

3. GDP (GDP):

   • Real GDP measures the inflation-adjusted value of goods and services produced in the U.S.

4. Unemployment Rate (Unemployment):

   • The percentage of the labor force that is unemployed and actively seeking work.

5. Stock Market Performance (S&P500):

   • Monthly average of the adjusted close price, representing stock market trends.

6. Industrial Production (Ind_Prod):

   • A measure of real output in the industrial sector, including manufacturing, mining, and utilities.

Dataset Statistics

1. Total Entries: 599
2. Columns: 6
3. Memory usage: 37.54 kB
4. Data types: float64

Feature Overview

• Columns:
  • Interest_Rate: Monthly Federal Funds Rate (%)
  • Inflation: CPI (All Urban Consumers, Index)
  • GDP: Real GDP (Billions of Chained 2012 Dollars)
  • Unemployment: Unemployment Rate (%)
  • Ind_Prod: Industrial Production Index (2017=100)
  • S&P500: Monthly Average of S&P 500 Adjusted Close Prices

Executive Summary

This project explores the interconnected dynamics of key macroeconomic indicators and financial market trends over the past 50 years, leveraging data from the Federal Reserve Economic Data (FRED) and Yahoo Finance. The dataset integrates critical variables such as the Federal Funds Rate, Inflation (CPI), Real GDP, Unemployment Rate, Industrial Production, and the S&P 500 Index, providing a holistic view of the U.S. economy and financial markets.

The analysis focuses on uncovering relationships between these variables through time-series visualization, correlation analysis, and trend decomposition. Key findings are included in the Insights section. This project serves as a robust resource for understanding long-term economic trends, policy impacts, and market behavior. It is particularly valuable for students, researchers, policymakers, and financial analysts seeking to connect macroeconomic theory with real-world data.

Potential Use Cases

• Economic Analysis: Examine relationships between interest rates, inflation, GDP, and unemployment.
• Stock Market Prediction: Study how macroeconomic indicators influence stock market trends.
• Time Series Modeling: Perform ARIMA, VAR, or other models to forecast economic trends.
• Cyclic Pattern Analysis: Identify how economic shocks and recoveries impact key indicators.

Snap of Power Analysis

https://github.com/user-attachments/assets/1b40e0ca-7d2e-4fbc-8cfd-df3f09e4fdb8">

To ensure sufficient power, the dataset covers last 50 years of monthly data i.e., around 600 entries.

Key Insights derived through EDA, time-series visualization, correlation analysis, and trend decomposition

• Interest Rate and Inflation Dynamics: The interest Rate and inflation exhibit an inverse relationship, especially during periods of aggressive monetary tightening by the Federal Reserve.
• Economic Growth and Market Performance: GDP growth and the S&P 500 Index show a positive correlation, reflecting how market performance often aligns with overall economic health.
• Labor Market and Industrial Output: Unemployment and industrial production demonstrate a strong inverse relationship. Higher industrial output is typically associated with lower unemployment
• Market Behavior During Economic Shocks: The S&P 500 experienced sharp declines during significant crises, such as the 2008 financial crash and the COVID-19 pandemic in 2020. These events also triggered increased unemployment and contractions in GDP, highlighting the interplay between markets and the broader economy.
• Correlation Highlights: S&P 500 and GDP have a strong positive correlation. Interest rates negatively correlate with GDP and inflation, reflecting monetary policy impacts. Unemployment is negatively correlated with industrial production but positively correlated with interest rates.

Link to GitHub Repo

https:/...

The interest rate set by the Federal Reserve is a crucial tool for promoting economic conditions that meet the mandate established by the United States Congress, which includes high employment, low and stable inflation, sustainable economic growth, and the moderation of long-term interest rates. The interest rates determined by the Fed directly influence the cost of credit, making financing either more accessible or more restrictive. When interest rates are low, there is a greater incentive for consumers to purchase homes through mortgages, finance automobiles, or undertake home renovations. Additionally, businesses are encouraged to invest in expanding their operations, whether by purchasing new equipment, modernizing facilities, or hiring more workers. Conversely, higher interest rates tend to curb such activity, discouraging borrowing and slowing economic expansion.

The dataset analyzed contains information on the economic conditions in the United States on a monthly basis since 1954, including the federal funds rate, which represents the percentage at which financial institutions trade reserves held at the Federal Reserve with each other in the interbank market overnight. This rate is determined by the market but is directly influenced by the Federal Reserve through open market operations to reach the established target. The Federal Open Market Committee (FOMC) meets eight times a year to determine the federal funds rate target, which has been defined within a range with upper and lower limits since December 2008.

Furthermore, real Gross Domestic Product (GDP) is calculated based on the seasonally adjusted quarterly rate of change in the economy, using chained 2009 dollars as a reference. The unemployment rate represents the seasonally adjusted percentage of the labor force that is unemployed. Meanwhile, the inflation rate is determined by the monthly change in the Consumer Price Index, excluding food and energy prices for a more stable analysis of core inflation.

The interest rate data was sourced from the Federal Reserve Bank of St. Louis' economic data portal, while GDP information was provided by the U.S. Bureau of Economic Analysis, and unemployment and inflation data were made available by the U.S. Bureau of Labor Statistics.

The analysis of this data helps to understand how economic growth, the unemployment rate, and inflation influence the Federal Reserve’s monetary policy decisions. Additionally, it allows for a study of the evolution of interest rate policies over time and raises the question of how predictable the Fed’s future decisions may be. Based on observed trends, it is possible to speculate whether the target range set in March 2017 will be maintained, lowered, or increased, considering the prevailing economic context and the challenges faced in conducting U.S. monetary policy.

The benchmark interest rate in the United States was last recorded at 4 percent. This dataset provides the latest reported value for - United States Fed Funds Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

In 2025, ** percent of adults in the United States invested in the stock market. This figure has remained steady over the last few years and is still below the levels before the Great Recession, when it peaked in 2007 at ** percent. What is the stock market? The stock market can be defined as a group of stock exchanges where investors can buy shares in a publicly traded company. In more recent years, it is estimated an increasing number of Americans are using neobrokers, making stock trading more accessible to investors. Other investments A significant number of people think stocks and bonds are the safest investments, while others point to real estate, gold, bonds, or a savings account. Since witnessing the significant one-day losses in the stock market during the financial crisis, many investors were turning towards these alternatives in hopes for more stability, particularly for investments with longer maturities. This could explain the decrease in this statistic since 2007. Nevertheless, some speculators enjoy chasing the short-run fluctuations, and others see value in choosing particular stocks.

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.

An index that can be used to gauge broad financial conditions and assess how these conditions are related to future economic growth. The index is broadly consistent with how the FRB/US model generally relates key financial variables to economic activity. The index aggregates changes in seven financial variables: the federal funds rate, the 10-year Treasury yield, the 30-year fixed mortgage rate, the triple-B corporate bond yield, the Dow Jones total stock market index, the Zillow house price index, and the nominal broad dollar index using weights implied by the FRB/US model and other models in use at the Federal Reserve Board. These models relate households' spending and businesses' investment decisions to changes in short- and long-term interest rates, house and equity prices, and the exchange value of the dollar, among other factors. These financial variables are weighted using impulse response coefficients (dynamic multipliers) that quantify the cumulative effects of unanticipated permanent changes in each financial variable on real gross domestic product (GDP) growth over the subsequent year. The resulting index is named Financial Conditions Impulse on Growth (FCI-G). One appealing feature of the FCI-G is that its movements can be used to measure whether financial conditions have tightened or loosened, to summarize how changes in financial conditions are associated with real GDP growth over the following year, or both.

The benchmark interest rate in Argentina was last recorded at 29 percent. This dataset provides the latest reported value for - Argentina Money Market Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The study’s subject The author’s aim is to describe the functional changes of German capital markets and stock exchanges. First he describes characteristics of German capital markets as a place of balancing supply and demand. Then, further submarkets are analyzed in their function (for example the meaning of credit transactions and interest rates for investment activities of the economy, or by means of fixed interest securities and equity securities documented capital procurement). Starting point of the investigation is the period until 1924, a period without regulation activities of the state on the capital trade. This period was followed by increased requirements on capital due to the first World War and the inflation. The description closed with the consequences of political influence on processes of capital markets.The author tries to show the rise of the German capital market, it’s functionality and the restriction as an effect of the first World War (the state’s extremely high need for money), and the following hyperinflation using long time series data. The data deals with following subjects: Datatables in HISTAT (Topic: Money and Currency = Geld): A.01 Average Price Level of Fixed Rated Bond Issues (Durchschnittlicher Kursstand festverzinslicher Anleihen) A.02 German Financial Assets from 1893 to 1913 (Das deutsche Geldvermögen zwischen 1893 und 1913) A.03 Foundation of Stock Corporations between 1870 and 1928 (Gründung von Aktiengesellschaften zwischen 1870 und 1928) A.04 Branches of German Major Banks between 1900 and 1918 (Niederlassungen der deutschen Großbanken in Deutschland zwischen 1900 und 1918) A.05 Deposits stock of German Banks in Mill. Mark between 1872 and 1910 (Depositenbestand der D-Banken in Mill. Mark zwischen 1872 und 1910) A.06 Importance of the Banks for financing investments: by capital issue raised capital sum between 1889 and 1904 (Bedeutung der Banken für die Investitionsfinanzierung: durch Emissionen aufgebrachte Kapitalsummen von 1889 bis 1904) A.07 Bank rate of the German Reichsbank between 1924 and 1930 (Der Diskontsatz der Deutschen Reichsbank (Jahresdurchschnitt) zwischen 1924 und 1930) A.08 Capital Market Interest for Fixed Rate Issues in Germany, United States, Switzerland and The Netherlands in 1925 and between 1928 and 1930 (Der Kapitalmarktzins für festverzinsliche Wertpapiere in Deutschland, USA, Schweiz und Holland für 1925, 1928 und 1930) A.09 Development of Savings and Deposits of German Savings Banks in Mill. Mark between 1924 and 1933 (Entwicklung der Spar- und Geldeinlagen der deutschen Sparkassen in Mill. Mark zwischen 1924 und 1933) A.10 Development of Savings and Deposits in German Savings Banks between 1933 and 1937(Entwicklung der Spareinlagen bei den deutschen Sparkassen zwischen 1933 bis 1937) A.11 Depts of Communities and associations of local authorities, 1928 – 1930 (Die Schulden der Gemeinden und der Gemeinde-Verbände, 1928-1930) A.12 Capital Assets of Insurances in Mill. Reichsmark between 1932 and 1936 (Die Kapitalanlage der Versicherungen in Mill. Reichsmark zwischen 1932 und 1936) A.13 Number of dealt Papers on the Berlin Stock Market and the Papers‘ Prices between 1931 and 1935 (Zahl der an der Berliner Börse gehandelten Papiere, Kurse und Dividenden der gehandelten Papiere zwischen 1931 und 1935)

This dataset includes various economic indicators such as stock market performance, inflation rates, GDP, interest rates, employment data, and housing index, all of which are crucial for understanding the state of the economy. By analysing this dataset, one can gain insights into the causes and effects of past recessions in the US, which can inform investment decisions and policy-making.

There are 20 columns and 343 rows spanning 1990-04 to 2022-10

The columns are:

1. Price: Price column refers to the S&P 500 lot price over the years. The S&P 500 is a stock market index that measures the performance of 500 large companies listed on stock exchanges in the United States. This variable represents the value of the S&P 500 index from 1980 to present. Industrial Production: This variable measures the output of industrial establishments in the manufacturing, mining, and utilities sectors. It reflects the overall health of the manufacturing industry, which is a key component of the US economy.

2. INDPRO: Industrial production measures the output of the manufacturing, mining, and utility sectors of the economy. It provides insights into the overall health of the economy, as a decline in industrial production can indicate a slowdown in economic activity. This data can be used by policymakers and investors to assess the state of the economy and make informed decisions.

3. CPI: CPI stands for Consumer Price Index, which measures the change in the prices of a basket of goods and services that consumers purchase. CPI inflation represents the rate at which the prices of goods and services in the economy are increasing.

4. Treasure Bill rate (3 month to 30 Years): Treasury bills (T-bills) are short-term debt securities issued by the US government. This variable represents the interest rates on T-bills with maturities ranging from 3 months to 30 years. It reflects the cost of borrowing money for the government and provides an indication of the overall level of interest rates in the economy.

5. GDP: GDP stands for Gross Domestic Product, which is the value of all goods and services produced in a country. This dataset is taking into account only the Nominal GDP values. Nominal GDP represents the total value of goods and services produced in the US economy without accounting for inflation.

6. Rate: The Federal Funds Rate is the interest rate at which depository institutions lend reserve balances to other depository institutions overnight. It is set by the Federal Reserve and is used as a tool to regulate the money supply in the economy.

7. BBK_Index: The BBKI are maintained and produced by the Indiana Business Research Center at the Kelley School of Business at Indiana University. The BBK Coincident and Leading Indexes and Monthly GDP Growth for the U.S. are constructed from a collapsed dynamic factor analysis of a panel of 490 monthly measures of real economic activity and quarterly real GDP growth. The BBK Leading Index is the leading subcomponent of the cycle measured in standard deviation units from trend real GDP growth.

8. Housing Index: This variable represents the value of the housing market in the US. It is calculated based on the prices of homes sold in the market and provides an indication of the overall health of the housing market.

9. Recession binary column: This variable is a binary indicator that takes a value of 1 when the US economy is in a recession and 0 otherwise. It is based on the official business cycle dates provided by the National Bureau of Economic Research.

ABSTRACT The paper discusses the determination of inflation in Brazil, especially after the great recession of 2015-2016, to assess the adequacy of manipulating interest rates to control the rise in prices due to permanent cost pressure. The burden of using the interest rate to fight cost inflation is to create a highly conventional level of the real interest rate, which benefits the rentier class in a financialized economy. In the light of the post-Keynesian macroeconomics, a high-interest rate convention keeps the economy with a low growth rate and a low investment rate, which in the case of the Brazilian economy has resulted in a regression in the productive matrix and productivity stagnation, and both contribute to perpetuating cost pressures on prices. The empirical analysis corroborates the discussion about recent inflation having its origin in cost pressures over which the interest rate impact for its control is limited. We complement the empirical analysis by testing the response to the SELIC interest rate of the variables used to explain the fluctuation of market prices and administered prices: commodity price index, exchange rate and activity level. As expected, the impact of an increase in the interest rate appreciates the exchange rate, favouring inflation control and reducing the level of activity but has no impact on the commodity price index.

This report analyses the Official Cash Rate (OCR) of the Reserve Bank of New Zealand (Te Putea Matua). The main objective of the OCR is to maintain price stability (between 1-3% inflation) and support sustainable full employment. The RBNZ influences market interest rates and the cost of borrowing and lending money through its OCR decisions. Interest rates affect the level of household and business spending, which has an impact on the prices of goods and services. The RBNZ generally reviews the OCR every six weeks. The data for this report is sourced from the Reserve Bank of New Zealand and is presented as the average rate over each financial year.

The Japan Mortgage/Loan Brokers Market, valued at ¥5.20 billion in 2025, is projected to experience steady growth with a Compound Annual Growth Rate (CAGR) of 3.92% from 2025 to 2033. This growth is driven primarily by increasing urbanization, a rising young population entering the housing market, and government initiatives aimed at boosting homeownership. Low interest rates in recent years have also stimulated mortgage demand. However, fluctuating economic conditions and potential regulatory changes pose challenges. The market is segmented by mortgage loan type (conventional, jumbo, government-insured, and others), loan terms (15, 20, and 30-year mortgages, and others), interest rates (fixed and adjustable), and provider (primary and secondary lenders). Major players include prominent Japanese financial institutions like the Bank of Japan, Bank of China (with significant operations in Japan), Suruga Bank, SMBC Trust Bank, Shinsei Bank, and several international banks with a presence in the Japanese market. The market's future trajectory will likely depend on the effectiveness of government policies supporting homeownership, the stability of the Japanese economy, and the adaptability of brokers to evolving technological advancements in financial services. Competition among brokers is expected to intensify, pushing for innovation in services and digital platforms to attract customers. The dominance of established financial institutions in the market highlights the need for smaller brokers to establish strong partnerships or differentiate themselves through specialized services. While the 30-year mortgage remains a significant segment, growing awareness of financial prudence and shorter-term financial goals could lead to increased demand for 15 and 20-year mortgage options. The increasing adoption of online platforms and fintech solutions is also anticipated to transform how mortgage brokerage services are delivered, potentially impacting the operational models of traditional players. Analyzing trends in interest rates and their correlation with overall market growth will be crucial for predicting future market performance. The impact of macroeconomic factors, such as inflation and unemployment, will also play a significant role in influencing mortgage demand and consequently, the growth of the brokerage market. Recent developments include: In March 2024, Leading Japanese online stocks broker Matsui Stocks Co., Ltd. established a partnership with global fintech firm Broadridge Financial Solutions, Inc. to boost its stock lending business via Broadridge's cloud-based SaaS post-trade processing technology., In July 2023, Mitsubishi UFJ Financial Group and Morgan Stanley expanded their 15-year-old partnership. At their joint brokerage operations, the Japanese and American institutions have decided to work together more closely on forex trading, as well as on researching and selling Japanese stocks to institutional investors.. Key drivers for this market are: Increase in demand for Financial Home Loan Solutions, Increased Accessibility to Loan Broker Services. Potential restraints include: Increase in demand for Financial Home Loan Solutions, Increased Accessibility to Loan Broker Services. Notable trends are: Consistent level of interest rate and Increasing Real Estate price affecting Japan's Mortgage/Loan Broker Market..

View market daily updates and historical trends for Effective Federal Funds Rate. from United States. Source: Federal Reserve. Track economic data with YC…

Description:

This dataset provides key economic indicators from various countries between 2010 and 2023. The dataset includes monthly data on inflation rates, GDP growth rates, unemployment rates, interest rates, and stock market index values. The data has been sourced from reputable global financial institutions and is suitable for economic analysis, machine learning models, and forecasting economic trends.

Data Sources:

The data has been generated to simulate real-world economic conditions, mimicking information from trusted sources like: - World Bank for GDP growth and inflation data - International Monetary Fund (IMF) for macroeconomic data - OECD for labor market statistics - National Stock Exchanges for stock market index values

Columns:

1. Date: The specific date (in Year/Month/Day format) representing when the data was collected.
2. Country: The country the data pertains to (e.g., USA, Germany, Japan).
3. Inflation Rate (%): The rate of inflation for that country, showing how fast prices for goods and services are increasing.
4. GDP Growth Rate (%): The percentage growth of the country’s Gross Domestic Product (GDP), indicating economic expansion or contraction.
5. Unemployment Rate (%): The percentage of the working-age population that is unemployed.
6. Interest Rate (%): The central bank's interest rate, used to control inflation and influence the economy.
7. Stock Index Value: The value of the country’s main stock market index, reflecting the performance of the stock market.

Potential Uses: - Economic Analysis: Researchers and analysts can use this dataset to study trends in inflation, GDP growth, unemployment, and other economic factors. - Machine Learning: This dataset can be used to train models for predicting economic trends or market performance. Financial Forecasting: Investors and economists can leverage this data for forecasting market movements based on economic conditions. - Comparative Studies: The dataset allows comparisons across countries and regions, offering insights into global economic performance.

The U.S. federal funds rate peaked in 2023 at its highest level since the 2007-08 financial crisis, reaching 5.33 percent by December 2023. A significant shift in monetary policy occurred in the second half of 2024, with the Federal Reserve implementing regular rate cuts. By December 2024, the rate had declined to 4.48 percent. What is a central bank rate? The federal funds rate determines the cost of overnight borrowing between banks, allowing them to maintain necessary cash reserves and ensure financial system liquidity. When this rate rises, banks become more inclined to hold rather than lend money, reducing the money supply. While this decreased lending slows economic activity, it helps control inflation by limiting the circulation of money in the economy. Historic perspective The federal funds rate historically follows cyclical patterns, falling during recessions and gradually rising during economic recoveries. Some central banks, notably the European Central Bank, went beyond traditional monetary policy by implementing both aggressive asset purchases and negative interest rates.

Techsalerator offers an extensive dataset of End-of-Day Pricing Data for all 2200 companies listed on the Australian Securities Exchange* (XASX) in Australia. 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 Australia:

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 Australia:

S&P/ASX 200 Index: The S&P/ASX 200 is the benchmark stock market index in Australia. It tracks the performance of the 200 largest publicly listed companies on the Australian Securities Exchange (ASX) and is widely used as a measure of the Australian stock market's overall performance.

Australian Dollar (AUD): The Australian Dollar is the official currency of Australia and is commonly abbreviated as AUD. It is one of the most traded currencies in the world and is used for both domestic and international transactions.

Reserve Bank of Australia (RBA): The central bank of Australia responsible for monetary policy, issuing currency, and maintaining financial stability. The RBA's decisions on interest rates and monetary policy have a significant impact on the Australian economy.

Australian Securities Exchange (ASX): The ASX is the primary stock exchange in Australia, where domestic and international companies are listed and traded. It plays a crucial role in facilitating capital raising and investment in Australia's financial markets.

Australian Government Bonds: These are debt securities issued by the Australian government to fund government operations and infrastructure projects. Australian Government Bonds are considered safe investments and are used as benchmarks for interest rates and economic sentiment.

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

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 Australia?

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 Australia 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, d...

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.

Arecor's (AREC) Therapeutic Advancements: A Question of Impact

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