This data set contains the simulated international inflation-linked bond return series used to create Table 4 (annual) and Table A.4 (monthly) of Swinkels (2018).

This dataset includes economic statistics on inflation, prices, unemployment, and pay & benefits provided by the Bureau of Labor Statistics (BLS). This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

This panel dataset contains quarterly series on inflation targets, bands, and track records for 41 inflation targeting countries from 1990 to 2024. Data on inflation targets and bands are collected through each central bank’s historical documents and rules-based track record measures are calculated by the author to assess actual inflation outcomes with respect to the central banks’ stated policy objectives. The dataset supports research work in Zhang (2025), Zhang and Wang (2022), and Zhang (2021). Please cite the papers when using the data.

Z. Zhang, Does inflation targeting track record matter for asset prices? Evidence from stock, bond, and foreign exchange markets, Journal of International Financial Markets, Institutions and Money, Volume 101, 2025, 102141. Z. Zhang, S. Wang, Do actions speak louder than words? Assessing the effects of inflation targeting track records on macroeconomic performance, 2022, IMF Working Papers 2022/227.
Z. Zhang, Stock returns and inflation redux: An explanation from monetary policy in advanced and emerging markets, 2021, IMF Working Papers 2021/219.

Graph and download economic data for Inflation, consumer prices for the United States (FPCPITOTLZGUSA) from 1960 to 2024 about consumer, CPI, inflation, price index, indexes, price, and USA.

This dataset contains monthly and quarterly time-series data from 2012 to 2024 for Indonesian sovereign credit risk (∆CDS), global volatility (VIX), international equity proxy (MSCI World Index), Indonesia Stock Exchange Composite Index (IHSG), exchange rate (USD/IDR), and inflation. The dataset supports the empirical analysis in the article titled “The Interaction Between Sovereign Risk, Global Volatility, and Domestic Stock Returns: An Indonesian Case Study.

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.

Inflation on the Rise: What Does This Mean for You?

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

Fault Lines Widen in the Global Recovery

Economic prospects have diverged further across countries since the April 2021 World Economic Outlook (WEO) forecast. Vaccine access has emerged as the principal fault line along which the global recovery splits into two blocs: those that can look forward to further normalization of activity later this year (almost all advanced economies) and those that will still face resurgent infections and rising COVID death tolls. The recovery, however, is not assured even in countries where infections are currently very low so long as the virus circulates elsewhere.

The global economy is projected to grow 6.0 percent in 2021 and 4.9 percent in 2022.The 2021 global forecast is unchanged from the April 2021 WEO, but with offsetting revisions. Prospects for emerging market and developing economies have been marked down for 2021, especially for Emerging Asia. By contrast, the forecast for advanced economies is revised up. These revisions reflect pandemic developments and changes in policy support. The 0.5 percentage-point upgrade for 2022 derives largely from the forecast upgrade for advanced economies, particularly the United States, reflecting the anticipated legislation of additional fiscal support in the second half of 2021 and improved health metrics more broadly across the group.

Recent price pressures for the most part reflect unusual pandemic-related developments and transitory supply-demand mismatches. Inflation is expected to return to its pre-pandemic ranges in most countries in 2022 once these disturbances work their way through prices, though uncertainty remains high. Elevated inflation is also expected in some emerging market and developing economies, related in part to high food prices. Central banks should generally look through transitory inflation pressures and avoid tightening until there is more clarity on underlying price dynamics. Clear communication from central banks on the outlook for monetary policy will be key to shaping inflation expectations and safeguarding against premature tightening of financial conditions. There is, however, a risk that transitory pressures could become more persistent and central banks may need to take preemptive action.

Risks around the global baseline are to the downside. Slower-than-anticipated vaccine rollout would allow the virus to mutate further. Financial conditions could tighten rapidly, for instance from a reassessment of the monetary policy outlook in advanced economies if inflation expectations increase more rapidly than anticipated. A double hit to emerging market and developing economies from worsening pandemic dynamics and tighter external financial conditions would severely set back their recovery and drag global growth below this outlook’s baseline.

Multilateral action has a vital role to play in diminishing divergences and strengthening global prospects. The immediate priority is to deploy vaccines equitably worldwide. A $50 billion IMF staff proposal, jointly endorsed by the World Health Organization, World Trade Organization, and World Bank, provides clear targets and pragmatic actions at a feasible cost to end the pandemic. Financially constrained economies also need unimpeded access to international liquidity. The proposed $650 billion General Allocation of Special Drawing Rights at the IMF is set to boost reserve assets of all economies and help ease liquidity constraints. Countries also need to redouble collective efforts to reduce greenhouse gas emissions. These multilateral actions can be reinforced by national-level policies tailored to the stage of the crisis that help catalyze a sustainable, inclusive recovery. Concerted, well-directed policies can make the difference between a future of durable recoveries for all economies or one with widening fault lines—as many struggle with the health crisis while a handful see conditions normalize, albeit with the constant threat of renewed flare-ups.

View data of the S&P 500, an index of the stocks of 500 leading companies in the US economy, which provides a gauge of the U.S. equity market.

White dwarf (WD) stars evolve simply and predictably, making them reliable age indicators. However, self-consistent validation of the methods for determining WD total ages has yet to be widely performed. This work uses 1565 wide (>100au) WD+WD binaries and 24 new triples containing at least two WDs to test the accuracy and validity of WD total age determinations. For these 1589 wide double WD binaries and triples, we derive the total age of each WD using photometric data from all-sky surveys, in conjunction with Gaia parallaxes and current hydrogen atmosphere WD models. Ignoring the initial-to-final mass relation and considering only WD cooling ages, we find that roughly 21%-36% of the more massive WDs in a system have a shorter cooling age. Since more massive WDs should be born as more massive main-sequence stars, we interpret this unphysical disagreement as evidence of prior mergers or the presence of an unresolved companion, suggesting that roughly 21%-36% of wide WD+WD binaries were once triples. Among the 423 wide WD+WD pairs that pass high-fidelity cuts, we find that 25% total age uncertainties are generally appropriate for WDs with masses >0.63M_{sun} and temperatures <12000K and provide suggested inflation factors for age uncertainties for higher-mass WDs. Overall, WDs return reliable stellar ages, but we detail cases where the total ages are least reliable, especially for WDs <0.63M{sun}_.

House Price Index YoY in the United States decreased to 2.80 percent in May from 3.20 percent in April of 2025. This dataset includes a chart with historical data for the United States FHFA House Price Index YoY.

The yield on 10 Year TIPS Yield eased to 1.90% on August 1, 2025, marking a 0.07 percentage point decrease from the previous session. Over the past month, the yield has fallen by 0.06 points, though it remains 0.14 points higher than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. This dataset includes a chart with historical data for the United States 10 Year TIPS Yield.

Gold rose to 3,362.51 USD/t.oz on August 1, 2025, up 2.25% from the previous day. Over the past month, Gold's price has risen 0.15%, and is up 37.65% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Gold - values, historical data, forecasts and news - updated on August of 2025.

The benchmark interest rate in Pakistan was last recorded at 11 percent. This dataset provides - Pakistan Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Silver rose to 37.02 USD/t.oz on August 1, 2025, up 0.93% from the previous day. Over the past month, Silver's price has risen 1.25%, and is up 29.60% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Silver - values, historical data, forecasts and news - updated on August of 2025.

The USD/JPY exchange rate fell to 147.2680 on August 1, 2025, down 2.35% from the previous session. Over the past month, the Japanese Yen has weakened 2.61%, and is down by 0.53% over the last 12 months. Japanese Yen - values, historical data, forecasts and news - updated on August of 2025.