This paper investigates the role of commodity price information when evaluating inflation risk. Using a model averaging approach, we provide strong evidence of in-sample and out-of-sample predictive ability from commodity prices and convenience yields to inflation, establishing clear point and density forecast performance gains when incorporating disaggregated commodities price information. The resulting forecast densities are used to calculate the (ex-ante) risk of inflation breaching defined thresholds that broadly characterize periods of high and low inflation. We find that information in commodity prices significantly enhances our ability to pick out tail inflation events and to characterize the level of risks associated with periods of high volatility in commodity prices.

For 2024, cyber incidents were a leading business risk to companies of all sizes globally according to risk management experts worldwide. Some industries are more prone to cyberattacks than others. For instance, manufacturing was the most targeted industry globally by ransomware incidents in 2023. Meanwhile, the number of cyber incidents in the financial sector increased in recent years. How does cybercrime jeopardize businesses? Cyber incidents pose a multitude of risks to businesses across various aspects. Financially, they can result in direct losses through theft, ransom payments, or disruptions in operations, which affect revenue streams and stability. Between 2001 and 2023, the monetary damage from cybercrime in the United States rose from 17.8 million U.S. dollars to a staggering 12.5 billion dollars. What challenges do businesses face due to inflation? Inflation poses numerous challenges to organizations, affecting consumer spending, interest rates, driving up operational expenses, and creating uncertainty in strategic planning. Rising prices frequently result in increased costs for raw materials and wages, thereby reducing profit margins. Throughout much of the 2010s, inflation was consistently low, especially between 2013 and 2020, when it fluctuated between 2.7 and 3.6 percent. However, the annual global inflation rate peaked in 2022, at 8.71 percent, and is expected to decline in the following years. This heightened inflation was a sign that the global economy was undergoing a period of great uncertainty, which made it more expensive to do business.

Inflation Rate in the United States decreased to 2.80 percent in February from 3 percent in January of 2025. This dataset provides - United States Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

As of June 2022, the ongoing inflation posed the biggest risk to the ASEAN-5 economies. In the Philippines, the risk was particularly high, reaching an index score of 93 out of 100. In Thailand, all three leading economic risks were evaluated with scores of 60 or over, with the Chinese economic slowdown being as much of a concern for Thailand's economy as the inflation.

This dataset is the Vulnerability Indices for Mortgage, Petroleum and Inflation Risks and Expenditure (VAMPIRE) for Australian Capital Cities for the year of 2001. The data has been calculated for each Census Collection District (CCD) within the Greater Capital City regions following the 2001 Australian Standard Geographical Classification (ASGC).

The VAMPIRE index developed at Griffith University's Urban Research Program provides a measure of socio-economic oil price vulnerability in Australian cities based on an analysis of socio-economic indicators from the Australian Bureau of Statistics (ABS) Census Data.

The inflation rate in Germany was 1.35 percent in 2019. The current rate meets the European Central Bank’s target rate, which is “below, but close to, 2 percent.” Many central bankers favor inflation between 2 and 3 percent, but Germans in particular would rather risk deflation than too much inflation.

Causes of inflation

Central bankers like low, stable inflation because this is a sign of a growing economy. When the economy grows, workers become more productive and spend more, and prices slowly rise. Monetary policy can cause inflation, but Germany has given this responsibility to the European Central Bank (ECB). Importantly, inflation expectations affect inflation, making it a self-fulfilling prophecy.

The German context

During the eurozone crisis, German politicians were advocating for the ECB to raise interest rates quickly. This would have reduced inflation, possibly causing deflation, but would have presented another hurdle for the struggling Greek economy. This is because of the hyperinflation of the Weimar Republic in the 1920s, when Germans carried their pay home in wheelbarrows because the banknotes had lost so much value. Ever since, Germans often warn that inflation harms pensioners and that personal provisions are necessary in any case. Fortunately for them, this statistic forecasts stable, modest inflation that does not alarm many economists.

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.

We monitor and process economic data and financial indicators across 200+ global markets, covering inflation trends, bankruptcy filings, and consensus estimates with 100+ key data points for macroeconomic analysis, risk modeling, and investment strategies.

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This is not going to be an article or Op-Ed about Michael Jordan. Since 2009 we've been in the longest bull-market in history, that's 11 years and counting. However a few metrics like the stock market P/E, the call to put ratio and of course the Shiller P/E suggest a great crash is coming in-between the levels of 1929 and the dot.com bubble. Mean reversion historically is inevitable and the Fed's printing money experiment could end in disaster for the stock market in late 2021 or 2022. You can read Jeremy Grantham's Last Dance article here. You are likely well aware of Michael Burry's predicament as well. It's easier for you just to skim through two related videos on this topic of a stock market crash. Michael Burry's Warning see this YouTube. Jeremy Grantham's Warning See this YouTube. Typically when there is a major event in the world, there is a crash and then a bear market and a recovery that takes many many months. In March, 2020 that's not what we saw since the Fed did some astonishing things that means a liquidity sloth and the risk of a major inflation event. The pandemic represented the quickest decline of at least 30% in the history of the benchmark S&P 500, but the recovery was not correlated to anything but Fed intervention. Since the pandemic clearly isn't disappearing and many sectors such as travel, business travel, tourism and supply chain disruptions appear significantly disrupted - the so-called economic recovery isn't so great. And there's this little problem at the heart of global capitalism today, the stock market just keeps going up. Crashes and corrections typically occur frequently in a normal market. But the Fed liquidity and irresponsible printing of money is creating a scenario where normal behavior isn't occurring on the markets. According to data provided by market analytics firm Yardeni Research, the benchmark index has undergone 38 declines of at least 10% since the beginning of 1950. Since March, 2020 we've barely seen a down month. September, 2020 was flat-ish. The S&P 500 has more than doubled since those lows. Look at the angle of the curve: The S&P 500 was 735 at the low in 2009, so in this bull market alone it has gone up 6x in valuation. That's not a normal cycle and it could mean we are due for an epic correction. I have to agree with the analysts who claim that the long, long bull market since 2009 has finally matured into a fully-fledged epic bubble. There is a complacency, buy-the dip frenzy and general meme environment to what BigTech can do in such an environment. The weight of Apple, Amazon, Alphabet, Microsoft, Facebook, Nvidia and Tesla together in the S&P and Nasdaq is approach a ridiculous weighting. When these stocks are seen both as growth, value and companies with unbeatable moats the entire dynamics of the stock market begin to break down. Check out FANG during the pandemic. BigTech is Seen as Bullet-Proof me valuations and a hysterical speculative behavior leads to even higher highs, even as 2020 offered many younger people an on-ramp into investing for the first time. Some analysts at JP Morgan are even saying that until retail investors stop charging into stocks, markets probably don’t have too much to worry about. Hedge funds with payment for order flows can predict exactly how these retail investors are behaving and monetize them. PFOF might even have to be banned by the SEC. The risk-on market theoretically just keeps going up until the Fed raises interest rates, which could be in 2023! For some context, we're more than 1.4 years removed from the bear-market bottom of the coronavirus crash and haven't had even a 5% correction in nine months. This is the most over-priced the market has likely ever been. At the night of the dot-com bubble the S&P 500 was only 1,400. Today it is 4,500, not so many years after. Clearly something is not quite right if you look at history and the P/E ratios. A market pumped with liquidity produces higher earnings with historically low interest rates, it's an environment where dangerous things can occur. In late 1997, as the S&P 500 passed its previous 1929 peak of 21x earnings, that seemed like a lot, but nothing compared to today. For some context, the S&P 500 Shiller P/E closed last week at 38.58, which is nearly a two-decade high. It's also well over double the average Shiller P/E of 16.84, dating back 151 years. So the stock market is likely around 2x over-valued. Try to think rationally about what this means for valuations today and your favorite stock prices, what should they be in historical terms? The S&P 500 is up 31% in the past year. It will likely hit 5,000 before a correction given the amount of added liquidity to the system and the QE the Fed is using that's like a huge abuse of MMT, or Modern Monetary Theory. This has also lent to bubbles in the housing market, crypto and even commodities like Gold with long-term global GDP meeting many headwinds in the years ahead due to a...

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.

According to a survey carried out in 2024, the top concerns financial instruments could mitigate over the next 10 years included debt, inflation, and asset bubble bursts, highlighting a strong focus on economic stability. Social risks like inequality and the lack of infrastructure were also recognized, though with less confidence in financial solutions. Environmental risks, such as extreme weather events, ranked lower, suggesting the need for alternative approaches beyond financial instruments.

The dataset contains data related to credit risk related factors that influence the banks in Pakistan.

Until the 90s information on risk premiums based on empirical studies for the German capital market was only available sporadically and for short time horizons. Therefore a long term comparison of risk and return was not possible. Markus Morawietz investigates profitability and risk of German stock and bond investments since 1870. He takes inflation and tax issues into account. His work contains a comprehensive collection of primary data since 1870 on key figures on a monthly basis which describe the German capital market. The goal of the study is to identify empirical statements on parameters of the German capital market. Therefore the exposition of theoretical economic models is not of primary importance in this study. A special focus is on the potential applicability of existing Germen index numbers as base data on the empirical investigation. The first chapter “methodological bases of performance measurement” concludes with the definition of the term “performance”. The following hypothesis is tested within this study: “There is a risk premium on securities taking inflation and influences of taxes into account.” The test of this hypothesis is run over the longest time period possible. Therefore monthly data on stock and bond investment are subject of the investigation because they are the most actively traded assets. Furthermore a substitute for the risk-free investment was developed in order to determine the risk premium. Before the explicit performance measurement of the different assets takes place, empirical starting points for performance measurement will be defined. These starting points contain a relevant demarcation of the investigation period and a description of the historical events during the investigation periods for all periods. Hereby special consideration is given to the specific problems of long term German value series (interruption trough the First World War with the following Hyperinflation and the Second World War). The analysis of the basics of performance measurement concludes the empirical starting points for performance measurement. The starting points contain the definition of a substitute for the certain segment, the description and preparation of the underlying data material and the calculation method used to determine performance. The third chapter contains a concrete empirical evaluation of the available data. This evaluation is subdivided into two parts: (a) performance measurement with unadjusted original data and (b) performance measurement with adjusted primary data (adjusted for inflation and tax influences). Both parts are structured in the same way. First the performance measurement of the specific asset (stocks, bonds and risk-free instruments) will be undertaken each by itself subdivided by partial periods. Afterwards the results of the performance measurement over the entire investigation period will be analyzed. The collection of derived partial results in the then following chapter shows return risk differences between the different assets. To calculate the net performance the nominal primary data is adjusted by inflation and tax influences. Therefore measured values for the changes in price level and for tax influences will be determined in the beginning of the third chapter. Following the performance measurement will be undertaken with the adjusted primary data. A comparison of the most important results of the different analysis in the last chapter concludes.

Data tables in histat (topic: money and currencies):

A. Discount and Lombard rate A.1 Discount rate: monthly average values, yearly average values (1870-1992) A.2 Lombard rate: monthly average values, yearly average values (1870-1992)

B. Stock price index, dividends and bond market und B.1a Stock price index: monthly average values, yearly average values (1870-1992) B.2 Dividends: monthly average values (1870-1992) B.3 Bond market: monthly average values, yearly average values (1870-1992)

C. Risk free instrument C.1 Private discount rate: monthly average values, yearly average values (1870-1991) C.2 Overnight rate: monthly average values, yearly average values (1924-1992)

D. Inflation rate D.1 Price index for costs of living (base1913/14 = 100), monthly average values, yearly average values (1870-1992) D.2 Inflation rate (base 1913 = 100), M monthly average values, yearly average values (1870-1992)

The COVADIS data standard for risk prevention plans includes all the technical and organisational specifications for the digital storage of geographical data represented in the risk prevention plans (RPPs). The PPR tool is part of the Law of 22 July 1987 on the organisation of civil security, the protection of the forest against fire and the prevention of major risks. The development of a RPP is the responsibility of the State. It is decided by the Prefect.

The COVADIS data standard for risk prevention plans includes all the technical and organisational specifications for the digital storage of geographical data represented in the risk prevention plans (RPPs). The PPR tool is part of the Law of 22 July 1987 on the organisation of civil security, the protection of the forest against fire and the prevention of major risks. The development of a RPP is the responsibility of the State. It is decided by the Prefect.

Of the major developed and emerging economies, China had the lowest inflation rate at 0.1 percent in December 2024. On the other end of the spectrum, the inflation rate in Russia stood at nearly 10 percent. The country's inflation rate increased sharply after the country's President, Vladimir Putin, decided to invade Ukraine, declined somewhat in 2023, before increasing slowly again since. The rate of inflation reflects changes in the cost of a specified basket containing a representative selection of goods and services. It is derived from the consumer price index (CPI).

Mexico Comm Banks: Cap Requirement: Mkt Risk: Dom Inflation Indexed Rate data was reported at 6,042.100 MXN mn in Feb 2019. This records an increase from the previous number of 6,033.660 MXN mn for Jan 2019. Mexico Comm Banks: Cap Requirement: Mkt Risk: Dom Inflation Indexed Rate data is updated monthly, averaging 4,767.500 MXN mn from Jan 2010 (Median) to Feb 2019, with 110 observations. The data reached an all-time high of 6,653.000 MXN mn in Feb 2012 and a record low of 3,519.790 MXN mn in Jun 2016. Mexico Comm Banks: Cap Requirement: Mkt Risk: Dom Inflation Indexed Rate data remains active status in CEIC and is reported by Bank of Mexico. The data is categorized under Global Database’s Mexico – Table MX.KB022: Capital Adequacy Ratio: Commercial Banks.

Inflation rates in the Association of Southeast Asian Nations (ASEAN) ranged from 31 percent inflation in Laos to 0.37 percent inflation in Brunei Darussalam. While countries like Vietnam are likely benefitting from more stable inflation than earlier seen, only a few countries are in the 2 to 6 percent range that many economists view as optimal for emerging economies. Effects of high inflation High inflation is generally detrimental to the economy. Prices tend to rise faster than wages, meaning that people and firms have less purchasing power. This in turn leads to slower growth in the gross domestic product (GDP). It also leads to a weaker currency. For countries with a positive trade balance this can be beneficial, because exports are relatively cheaper to foreign buyers. Through the same mechanism, net importers suffer from a weaker currency. Additionally, inflation makes a country’s national debt less expensive if the debt is denominated in the local currency. However, most of this debt is in U.S. dollars, so inflation makes the debt more difficult to service and repay. Risks of deflation With deflation, consumers and firms delay investments because they expect prices to be lower in the future. This slows consumption and investment, two major components of GDP growth. The most common example of this is Japan, where the GDP growth rate has been low for a long time due, in large part, to deflation. For this reason, countries like Brunei would rather see low and stable inflation than slight deflation.

The COVADIS data standard for risk prevention plans includes all the technical and organisational specifications for the digital storage of geographical data represented in the risk prevention plans (RPPs). The PPR tool is part of the Law of 22 July 1987 on the organisation of civil security, the protection of the forest against fire and the prevention of major risks. The development of a RPP is the responsibility of the State. It is decided by the Prefect.

Discover the most recent developments in the economic landscape of the United States and assess the performance of various industries during the previous quarter.