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.

Short-term and floating-rate bonds are typically a popular investment choice during times of increasing rates. Roughly 52 percent of investors noted investing in assets that benefit from higher interest rates when anticipating an economic recession. While over 55 percent of investors choose to invest in fewer singular companies and increase asset allocation to conviction stocks.

Graph and download economic data for Bank Prime Loan Rate Changes: Historical Dates of Changes and Rates (PRIME) from 1955-08-04 to 2024-12-20 about prime, loans, interest rate, banks, interest, depository institutions, rate, and USA.

In December 2024, the yield on a 10-year U.S. Treasury note was 4.39 percent, forecasted to decrease to reach 3.27 percent by August 2025. Treasury securities are debt instruments used by the government to finance the national debt. Who owns treasury notes? Because the U.S. treasury notes are generally assumed to be a risk-free investment, they are often used by large financial institutions as collateral. Because of this, billions of dollars in treasury securities are traded daily. Other countries also hold U.S. treasury securities, as do U.S. households. Investors and institutions accept the relatively low interest rate because the U.S. Treasury guarantees the investment. Looking into the future Because these notes are so commonly traded, their interest rate also serves as a signal about the market’s expectations of future growth. When markets expect the economy to grow, forecasts for treasury notes will reflect that in a higher interest rate. In fact, one harbinger of recession is an inverted yield curve, when the return on 3-month treasury bills is higher than the ten year rate. While this does not always lead to a recession, it certainly signals pessimism from financial markets.

We argue that the vast bulk of movements in aggregate real economic activity during the Great Recession were due to financial frictions. We reach this conclusion by looking through the lens of an estimated New Keynesian model in which firms face moderate degrees of price rigidities, no nominal rigidities in wages, and a binding zero lower bound constraint on the nominal interest rate. Our model does a good job of accounting for the joint behavior of labor and goods markets, as well as inflation, during the Great Recession. According to the model the observed fall in total factor productivity and the rise in the cost of working capital played critical roles in accounting for the small drop in inflation that occurred during the Great Recession. (JEL E12, E23, E24, E31, E32, E52)

The year 2021 saw the peak in issuance of residential mortgage backed securities (MBS), at 3.7 trillion U.S. dollars. Since then, MBS issuance has slowed, reaching 1.1 trillion U.S. dollars in 2023. What are mortgage backed securities? A mortgage backed security is a financial instrument in which a group of mortgages are bundled together and sold to the investors. The idea is that the risk of these individual mortgages is pooled when they are packaged together. This is a sound investment policy, unless the foreclosure rate increases significantly in a short amount of time. Mortgage risk Since mortgages are loans backed by an asset, the house, the risk is often considered relatively low. However, the loan maturities are very long, sometimes decades, meaning lenders must factor in the risk of a shift in the economic climate. As such, interest rates on longer mortgages tend to be higher than on shorter loans. The ten-year treasury yield influences these rates, since it is a long-term rate that most investors accept as risk-free. Additionally, a drop in the value of homeowner equity could lead to a situation where the debtor is “underwater” and owes more than the home is worth.

Historical dataset of the daily level of the federal funds rate back to 1954. The fed funds rate is the interest rate at which depository institutions (banks and credit unions) lend reserve balances to other depository institutions overnight, on an uncollateralized basis. The Federal Open Market Committee (FOMC) meets eight times a year to determine the federal funds target rate.

Graph and download economic data for Interest Rates: Long-Term Government Bond Yields: 10-Year: Main (Including Benchmark) for United States (IRLTLT01USM156N) from Apr 1953 to Jan 2025 about long-term, 10-year, bonds, yield, government, interest rate, interest, rate, and USA.

August 2024 marked a significant shift in the UK's monetary policy, as it saw the first reduction in the official bank base interest rate since August 2023. This change came after a period of consistent rate hikes that began in late 2021. In a bid to minimize the economic effects of the COVID-19 pandemic, the Bank of England cut the official bank base rate in March 2020 to a record low of 0.1 percent. This historic low came just one week after the Bank of England cut rates from 0.75 percent to 0.25 percent in a bid to prevent mass job cuts in the United Kingdom. It remained at 0.1 percent until December 2021 and was increased to one percent in May 2022 and to 2.25 percent in October 2022. After that, the bank rate increased almost on a monthly basis, reaching 5.25 percent in August 2023. It wasn't until August 2024 that the first rate decrease since the previous year occurred, signaling a potential shift in monetary policy. Why do central banks adjust interest rates? Central banks, including the Bank of England, adjust interest rates to manage economic stability and control inflation. Their strategies involve a delicate balance between two main approaches. When central banks raise interest rates, their goal is to cool down an overheated economy. Higher rates curb excessive spending and borrowing, which helps to prevent runaway inflation. This approach is typically used when the economy is growing too quickly or when inflation is rising above desired levels. Conversely, when central banks lower interest rates, they aim to encourage borrowing and investment. This strategy is employed to stimulate economic growth during periods of slowdown or recession. Lower rates make it cheaper for businesses and individuals to borrow money, which can lead to increased spending and investment. This dual approach allows central banks to maintain a balance between promoting growth and controlling inflation, ensuring long-term economic stability. Additionally, adjusting interest rates can influence currency values, impacting international trade and investment flows, further underscoring their critical role in a nation's economic health. Recent interest rate trends Between 2021 and 2024, most advanced and emerging economies experienced a period of regular interest rate hikes. This trend was driven by several factors, including persistent supply chain disruptions, high energy prices, and robust demand pressures. These elements combined to create significant inflationary trends, prompting central banks to raise rates in an effort to temper spending and borrowing. However, in 2024, a shift began to occur in global monetary policy. The European Central Bank (ECB) was among the first major central banks to reverse this trend by cutting interest rates. This move signaled a change in approach aimed at addressing growing economic slowdowns and supporting growth.

We investigate the heterogeneous boom and bust patterns across countries that emerge as a result of global shocks. Our analysis sheds light on the emergence of core and periphery countries, and the joint determination of the depth of recessions and tightness of credit across countries. The model implies that interest rates are similar across core and periphery countries in booms, with larger credit and output growth in periphery countries. However, a common global shock that leads to a credit crunch across the globe gives rise to a sharper spike in interest rates and a deeper recession in periphery countries, while a credit flight to the core alleviates the adverse consequences in these countries. We explore the implication of the model about credit spreads, portfolio rebalancing, investment, non-performing debt and concentration of debt ownership during booms and busts, both in the time series and in the cross-section, and connect them to existing stylized facts. We further demonstrate how the anatomy of the global economy evolves as a result of aggregate demand and supply shocks to financing, such as a global saving glut.

The Volcker Shock was a period of historically high interest rates precipitated by Federal Reserve Chairperson Paul Volcker's decision to raise the central bank's key interest rate, the Fed funds effective rate, during the first three years of his term. Volcker was appointed chairperson of the Fed in August 1979 by President Jimmy Carter, as replacement for William Miller, who Carter had made his treasury secretary. Volcker was one of the most hawkish (supportive of tighter monetary policy to stem inflation) members of the Federal Reserve's committee, and quickly set about changing the course of monetary policy in the U.S. in order to quell inflation. The Volcker Shock is remembered for bringing an end to over a decade of high inflation in the United States, prompting a deep recession and high unemployment, and for spurring on debt defaults among developing countries in Latin America who had borrowed in U.S. dollars.

Monetary tightening and the recessions of the early '80s

Beginning in October 1979, Volcker's Fed tightened monetary policy by raising interest rates. This decision had the effect of depressing demand and slowing down the U.S. economy, as credit became more expensive for households and businesses. The Fed funds rate, the key overnight rate at which banks lend their excess reserves to each other, rose as high as 17.6 percent in early 1980. The rate was allowed to fall back below 10 percent following this first peak, however, due to worries that inflation was not falling fast enough, a second cycle of monetary tightening was embarked upon starting in August of 1980. The rate would reach its all-time peak in June of 1981, at 19.1 percent. The second recession sparked by these hikes was far deeper than the 1980 recession, with unemployment peaking at 10.8 percent in December 1980, the highest level since The Great Depression. This recession would drive inflation to a low point during Volcker's terms of 2.5 percent in August 1983.

The legacy of the Volcker Shock

By the end of Volcker's terms as Fed Chair, inflation was at a manageable rate of around four percent, while unemployment had fallen under six percent, as the economy grew and business confidence returned. While supporters of Volcker's actions point to these numbers as proof of the efficacy of his actions, critics have claimed that there were less harmful ways that inflation could have been brought under control. The recessions of the early 1980s are cited as accelerating deindustrialization in the U.S., as manufacturing jobs lost in 'rust belt' states such as Michigan, Ohio, and Pennsylvania never returned during the years of recovery. The Volcker Shock was also a driving factor behind the Latin American debt crises of the 1980s, as governments in the region defaulted on debts which they had incurred in U.S. dollars. Debates about the validity of using interest rate hikes to get inflation under control have recently re-emerged due to the inflationary pressures facing the U.S. following the Coronavirus pandemic and the Federal Reserve's subsequent decision to embark on a course of monetary tightening.

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.

DTRTU Stock: Are We Headed for a Recession?

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

Explore the stability of gold prices amidst economic uncertainty in the U.S., despite slight dips and fluctuating market conditions.

ABSTRACT Beyond representing coordination or government failures, the Brazilian financial crisis in the 1980s characterized the dominance of financial interests on public policies. This paper shows that such dominance began with the external debt negotiations in 1982, which put international creditors’ interest first. It argues that the imposed external adjustment - specially the exchange rates devaluation, public investment cuts and the hike in real interest rates - generated recession and financial instability (notoriously inflation), which would threat depreciating private wealth. Therefore, both the external adjustment and the private wealth protection only turned possible due to the increasing public deficits and debts - including by transferences of debt from private to public sector. The dominant perspective, found in the literature on the period, blaming government deficits and debts for the financial instability of the 1980s is wrong. Economists, even heterodox ones, still believe that Brazil’s financial crisis in the 1980s resulted from budget deficits and public debts. This paper shows, contrary to the dominant view, that once the public sector had to allow private wealth adjustment to the external conditions imposed by foreign creditors, public deficits were the only possible outcome in that conditions.

Home prices in the U.S. reach new heights The American housing market continues to show remarkable resilience, with the S&P/Case Shiller U.S. National Home Price Index reaching an all-time high of 325.78 in July 2024. This figure represents a significant increase from the index value of 166.24 recorded in January 2015, highlighting the substantial growth in home prices over the past decade. The S&P Case Shiller National Home Price Index is based on the prices of single-family homes and is the leading indicator of the American housing market and one of the indicators of the state of the broader economy. The S&P Case Shiller National Home Price Index series also includes S&P/Case Shiller 20-City Composite Home Price Index and S&P/Case Shiller 10-City Composite Home Price Index – measuring the home price changes in the major U.S. metropolitan areas, as well as twenty composite indices for the leading U.S. cities. Market fluctuations and recovery Despite the overall upward trend, the housing market has experienced some fluctuations in recent years. During the housing boom in 2021, the number of existing home sales reached the highest level since 2006. However, transaction volumes quickly plummeted, as the soaring interest rates and out-of-reach prices led to housing sentiment deteriorating. Factors influencing home prices Several factors have contributed to the rise in home prices, including a chronic supply shortage, the gradual decline in interest rates, and the spike in demand during the COVID-19 pandemic. During the subprime mortgage crisis (2007-2010), the construction of new homes declined dramatically. Although it has gradually increased since then, the number of new building permits, home starts, and completions are still shy from the levels before the crisis. With demand outweighing supply, competition for homes can be fierce, leading to bidding wars and soaring prices. The supply of existing homes is further constrained, as homeowners are less likely to sell and move homes due to the worsened lending conditions.

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.

TA:TSX Stock: Are We Headed for a Recession?

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

The survey studied Finnish public opinion on the country's potential membership in the European Community. First, the respondents were asked whether the Government had been wrong or right in applying for the membership, and whether the respondents opposed or supported the membership. They were also asked how interested they were in issues connected with European integration and the EC, and how well informed they were of these issues. The survey also investigated opinions on the reliability of various information sources (e.g. radio and television, trade unions, company executives, Prime Minister) on the EC membership issue. Views were probed on the impact of the EC membership on interest rate, taxation, wages, prices, food quality, culture, education, social security, health care, Finland's relations with Russia, crime, etc. The respondents were asked to what extent they agreed with a number of statement relating to the EC and Finland's EC membership. One set of questions focused on the causes and culprits of economic recession in Finland. Regarding the recession, the respondents were also asked to assess the present and future financial situation of certain banks, and how soon Finland would emerge from the recession. One theme pertained to energy issues: the respondents were asked whether Finland should increase or decrease the use of certain energy sources in electricity generation. Opinions on the construction of a fifth nuclear power plant or the Vuotos reservoir were charted, and likewise perceptions of major energy companies. Background variables included the respondent's gender, age group, size of the municipality, province of residence, basic and vocational education, economic activity, employment sector, and which political party R would vote for if the parliamentary elections were held at that time.

After a period of record-low mortgage interest rates, the cost of mortgage borrowing in Germany surged in 2022. In 2019, mortgage rates declined notably, falling as low as 1.16 percent in December 2020. This downward trend reversed in 2021, as mortgage rates started to gradually pick up. Five-to-ten-year mortgage loans had the lowest rates in October 2023 at 3.85 percent, while floating rate mortgages up to one year were the most expensive at 5.53 percent. Mortgages with over 10-year fixed period – the most popular loan type among homebuyers - had an interest rate of 3.9 percent.

Why did mortgage rates in Germany increase?

In 2022, the yearly inflation rate in Germany experienced a swift rise, prompting the central bank to raise interest rates to counter this surge. The European Central Bank (ECB) is responsible for determining Germany's central bank interest rate. In July 2022, following a prolonged period of stability, the average interest rates in Germany began a steady rise, which persisted consistently thereafter.  This increase is intended to stabilize prices, but it also means higher borrowing costs for those seeking mortgages.

Downturn in Germany's home loan borrowing

From 2022 onward, the gross residential mortgage lending in Germany fell dramatically. Besides the higher interest rates, the downturn can be explained by the slowed pace of economic growth, which makes individuals and businesses more cautious about big investments such as buying a home. Additionally, the German housing market suffers a chronic undersupply, meaning that homebuyers often struggle to find an affordable home to purchase.

Gold prices, recently at $3,057.31, may drop to $1,820 due to supply-demand dynamics, interest rates, and new mines, says Morningstar's David Sekera.

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.

APTX Stock: Are We Headed for a Recession?

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