Graph and download economic data for Equity Market Volatility Tracker: Macroeconomic News and Outlook: Interest Rates (EMVMACROINTEREST) from Jan 1985 to Jun 2025 about volatility, uncertainty, equity, interest rate, interest, rate, and USA.

The Equity Market Volatility tracker moves with the VIX and with the realized volatility of returns on the S&P 500.

For more information, see Baker, Scott, Nicholas Bloom and Steven Davis (2019), 'Policy News and Stack Market Volatility' (https://www.policyuncertainty.com/media/Policy%20News%20and%20Stock%20Market%20Volatility.pdf)

We explore several explicit and alternating-direction implicit (ADI) finite difference methods for pricing compound options with early exercise opportunities. Stock prices, stock price volatilities, and interest rates are assumed to follow correlated stochastic processes.

United States - Equity Market Volatility Tracker: Macroeconomic News and Outlook: Interest Rates was 6.33178 Index in May of 2025, according to the United States Federal Reserve. Historically, United States - Equity Market Volatility Tracker: Macroeconomic News and Outlook: Interest Rates reached a record high of 23.32740 in October of 1987 and a record low of 1.74079 in May of 2017. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Equity Market Volatility Tracker: Macroeconomic News and Outlook: Interest Rates - last updated from the United States Federal Reserve on July of 2025.

Following the BoE’s interest rate cut, explore the immediate impact on the UK economy and how finance professionals and businesses can navigate the prospect of future reductions.

Abstract (en): We show how changes in the volatility of the real interest rate at which small open emerging economies borrow have an important effect on variables like output, consumption, investment, and hours. We start by documenting the strong evidence of time-varying volatility in the real interest rates faced by four emerging economies: Argentina, Brazil, Ecuador, and Venezuela. We estimate a stochastic volatility process for real interest rates. Then, we feed this process in a standard small open economy business cycle model. We find that an increase in real interest rate volatility triggers a fall in output, consumption, investment, hours, and debt. (JEL E13, E20, E32, E43, F32, F43, 011)

Price discovery and volatility spillovers in interest rate derivatives market (datasets)

Aside from two outliers the majority of Vanguard's fixed-income securities were projected to have an average ******* annualized volatility rate of under *** percent. Fixed income is used to refer to any investment in which a borrower/issuer is required to pay interest to the lender on the amount given. Due to the stable nature of fixed-income products in comparison to other securities such as equities the level of volatility is comparably low.

This paper estimates a model in which persistent fluctuations in expected consumption growth, expected inflation, and their time-varying volatility determine asset price variation. The model features Epstein-Zin recursive preferences, which determine the market price of macro risk factors. Analysis of the US nominal term structure data from 1953 to 2006 shows that agents dislike high uncertainty and demand compensation for volatility risks. Also, the time variation of the term premium is driven by the compensation for inflation volatility risk, which is distinct from consumption volatility risk. The central role of inflation volatility risk in explaining the time-varying term premium is consistent with other empirical evidence including survey data. In contrast, the existing long-run risks literature emphasizes consumption volatility risk and ignores inflation-specific time-varying volatility. The estimation results of this paper suggest that inflation-specific volatility risk is essential for fitting the time series of the US nominal term structure data.

While higher interest rates increase the cost of credit financing for businesses, this study finds that the direct impact of this traditional credit transmission mechanism on corporate bankruptcy risk is limited. Instead, our research reveals that changes in corporate behavior induced by rising debt financing costs are the root cause of bankruptcy risk. In the short term, an increase in interest rates drives businesses to substitute supply chain financing for credit financing in pursuit of profit maximization. This mismatch of short-term debt and long-term investments undermines the sustainability of the supply chain, ultimately reducing financial security—sacrificing safety for profitability. In the long term, higher interest rates exacerbate the overcapacity problem in industries, increasing the unsustainability of the production and sales balance. Using data from China’s construction industry, this study empirically tests these findings and, based on the main conclusions, provides policy suggestions regarding the long- and short-term effects of monetary policy on the sustainable development of China’s construction industry: (1) focus on short-term interest rate risks and be vigilant against commercial credit bubbles; (2) long-term monetary policy should prioritize industrial structure optimization.

The zip file contains programs and data for the paper

Interest rate, enterprise bankruptcy risk, and financing structure.

The benchmark interest rate in the United States was last recorded at 4.50 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.

Regression results of default risk on interest rate.

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

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.

CBOE Volatility Index Options & Futures Prediction

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

TraditionData’s Swaptions Market Data service offers comprehensive market coverage for swaptions across multiple currencies.

• Provides datasets for At-the-Money (ATM) and Out-of-the-Money (OTM) vol surfaces.
• Real-time, intraday, and end-of-day prices available for interest rate markets.
• Service is tailored with focused and granular packages based on region and product.

For a detailed exploration, visit Swaptions Market Data.

ABSTRACT This short article shows that since 1999 the interest rate has been correlated to exchange rate volatility in Brazil. Therefore, it would be one of the reasons for not reducing the interest rate in Brazil.

Investment Trust Market Outlook

The global investment trust market size was valued at approximately USD 2.5 trillion in 2023 and is projected to reach around USD 4.1 trillion by 2032, growing at a compound annual growth rate (CAGR) of 5.5% during the forecast period. The growth of this market is driven by several factors including increasing investor preference for diversified portfolios and the growing availability of various types of investment trusts to meet different investment goals. These factors are expected to propel the market significantly over the coming years.

Expanding middle-class populations and increasing disposable incomes in emerging economies are also contributing significantly to the growth of the investment trust market. With more individuals seeking avenues for better returns on their investments, investment trusts offer an attractive proposition due to their diversified nature and professional management. Additionally, the growing awareness about the benefits of investing in such diversified instruments, as opposed to individual stocks or bonds, is a crucial growth factor.

Technological advancements and digitalization have made it easier for investors to access investment trusts. Online platforms have simplified the process of investing, enabling real-time tracking and management of investment portfolios. This ease of access has broadened the market's appeal, attracting a younger, tech-savvy investor base. The integration of artificial intelligence and machine learning in these platforms further enhances their capabilities, making investment decisions more data-driven and informed.

The rising trend of sustainable and responsible investing is another significant driver for the investment trust market. Many investors are now seeking to align their portfolios with their personal values, focusing on environmental, social, and governance (ESG) criteria. Investment trusts that prioritize ESG factors are seeing increased demand, as investors look to not only generate financial returns but also contribute positively to society and the environment.

Regionally, North America and Europe dominate the investment trust market, primarily due to their well-established financial sectors and higher levels of investor sophistication. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period. The increasing economic development and growing middle-class population in countries like China and India are major contributors to this growth. As more individuals in these regions become financially literate, the demand for diverse investment options like investment trusts is expected to rise steadily.

Type Analysis

Equity investment trusts, fixed-income investment trusts, hybrid investment trusts, and other specialized types form the various segments of the investment trust market. Equity investment trusts, which primarily invest in stocks, remain the most popular due to their potential for high returns. These trusts appeal to investors looking for growth opportunities, particularly in sectors showing robust performance. The volatility of stock markets, however, poses a risk, making it essential for these trusts to maintain a well-diversified portfolio to mitigate potential losses.

Fixed-income investment trusts focus on bonds and other debt instruments, offering a more stable and predictable income stream, which is particularly attractive to conservative investors or those nearing retirement. These trusts typically have lower risk compared to equity trusts, but also potentially lower returns. With interest rates playing a critical role in their performance, the recent trends of fluctuating interest rates have made these trusts more appealing as they adapt to the changing economic landscape.

Hybrid investment trusts combine both equity and fixed-income investments, providing a balanced approach that appeals to a broader range of investors. These trusts aim to achieve a mix of income generation and capital appreciation, making them suitable for investors with moderate risk tolerance. The flexibility offered by hybrid trusts allows them to adjust their asset allocation based on market conditions, enhancing their appeal in uncertain economic climates.

Other types of investment trusts include those specializing in real estate, commodities, and niche sectors like technology or healthcare. These specialized trusts cater to investors looking to focus on specific sectors that they believe will outperform the broader market. While they offer t

Recent sovereign defaults are accompanied by interest rate spikes and deep recessions. This paper develops a small open economy model to study default risk and its interaction with output and foreign debt. Default probabilities and interest rates depend on incentives for repayment. Default is more likely in recessions because this is when it is more costly for a risk averse borrower to repay noncontingent debt. The model closely matches business cycles in Argentina predicting high volatility of interest rates, higher volatility of consumption relative to output, and negative correlations of output with interest rates and the trade balance.