Graph and download economic data for Inflation Risk Premium (TENEXPCHAINFRISPRE) from Jan 1982 to Aug 2025 about premium, inflation, and USA.

Ten-Year Expected Inflation and Real and Inflation Risk Premia is a part of the Inflation Expectations indicator of the Federal Reserve Bank of Cleveland.

Inflation Risk Premium - Historical chart and current data through 2025.

The average market risk premium in the United States decreased slightly to *** percent in 2023. This suggests that investors demand a slightly lower return for investments in that country, in exchange for the risk they are exposed to. This premium has hovered between *** and *** percent since 2011. What causes country-specific risk? Risk to investments come from two main sources. First, inflation causes an asset’s price to decrease in real terms. A 100 U.S. dollar investment with three percent inflation is only worth ** U.S. dollars after one year. Investors are also interested in risks of project failure or non-performing loans. The unique U.S. context Analysts have historically considered the United States Treasury to be risk-free. This view has been shifting, but many advisors continue to use treasury yield rates as a risk-free rate. Given the fact that U.S. government securities are available at a variety of terms, this gives investment managers a range of tools for predicting future market developments.

Graph and download economic data for Real Risk Premium (TENEXPCHAREARISPRE) from Jan 1982 to Aug 2025 about premium, real, and USA.

We report average expected inflation rates over the next one through 30 years. Our estimates of expected inflation rates are calculated using a Federal Reserve Bank of Cleveland model that combines financial data and survey-based measures. Released monthly.

Every investment carries a risk, and in an uncertain economic environment, this risk can cost investors. In almost all major markets surveyed, the risk premium for office investments decreased between the first and the third quarter of 2022. One of the reasons for the decrease is the rising borrowing costs due to soaring inflation. Dubai had the highest risk premium amounting to **** percent, whereas Singapore, Seoul and Hong Kong had negative risk premiums. What this means is that investors in these markets are hypothetically likely to make higher returns from investment in government bonds than offices.

The average market risk premium in Canada was *** percent in 2024. This means investors demanded an extra *** Canadian dollars on a 100 Canadian dollar investment. This extra cost should compensate for the risk of an investment based in Canada. What causes risk? As far as country-specific factors are concerned, macroeconomic trends can cause risk. For example, the inflation rate in relation to other countries can change the relative value of an investment. Lower inflation in Canada could weaken the Canadian dollar, reducing the value of Canadian assets in terms of another currency, such as the euro or U.S. dollar. The Canadian context As a country, Canada has a fairly high national debt. Some economists point to this as an increased default risk, since debt servicing can become costly. However, most investors agree that Canada, as an advanced economy, is creditworthy and not at risk of defaulting. A better measure is to look at Canada’s risk premium in the context of interest rates from other countries. These deposit rates can be used as a baseline for the market risk premium of other countries, though they do not include all the factors that have been used to calculate this statistic.

Expected Inflation Term Structure is a part of the Inflation Expectations indicator of the Federal Reserve Bank of Cleveland.

The average market risk premium in South Africa increased to *** percent in 2024. Market premium risk represents the difference between return on equities and a risk-free investment, which is normally associated with short-term government bonds. For comparison, the U.S. market premium risk amounted to *** percent in the same year. Risk-free rate Most analysts consider the U.S. treasury rate to be the risk-free rate for the term of their investment, assuming the United States government will not default. Just as consumers in the Unites States get a credit rating, agencies such as Standard & Poor’s rate countries’ credit risks. Using these data, analysts compute the country-specific default risk, which in turn has an influence on the value of risk-free rate. What influences the return on equities? The economic factors such as political stability in a country, inflation rate, level of indebtment, trade deficit and investments have an influence on the activities of companies and their valuation on the stock exchanges. Apart from the economic cycle, the company’s operations itself, which are reflected in the results published in the financial reports, can boost or diminish the stock returns.

ABSTRACT The objective of this article is to analyze the implications of Bresser-Nakano hypothesis, that risk-premium is positive related to domestic rate of interest, over time paths of nominal interest rate and nominal exchange rate in a small open economy whose regime of economic policy is characterized by flexible exchange rate, inflation targeting and short run capital mobility. In the theoretical framework developed in the article, we are able to shown that, in the case of a strong positive feedback of nominal interest rate over risk-premium, (i) there are multiple time paths of nominal interest rate and nominal exchange rate; (ii) all such paths are compatible with some degree of price stability and (iii) some of these paths, however, are related to an increase in current account deficit and/or a continuous increase in fiscal deficit. The logical conclusion of these results is that the achievement of current account and fiscal equilibrium can only be obtained by a change in the regime of economic policy.

Ten-Year TIPS Yields versus Real Yields is a part of the Inflation Expectations indicator of the Federal Reserve Bank of Cleveland.

D'Amico, Kim, and Wei use a no-arbitrage term structure model to decompose TIPS inflation compensation into three components: inflation expectation, inflation risk premium, and TIPS liquidity premium over the 1983-present period. The model is also used to decompose nominal yields or forward rates into four components: expected real short rate, expected inflation, inflation risk premium, and real term premium.

For over ten years, the Treasury has issued index-linked debt. This paper describes the methodology for fitting a smoothed yield curve to these securities that is used at the Federal Reserve Board every day, and makes the estimates public. Comparison with the corresponding nominal yield curve allows measures of inflation compensation to be computed. We discuss the interpretation of inflation compensation, and provide evidence that it is not a pure measure of inflation expectations being distorted by inflation risk premium and liquidity premium components. We attempt to estimate the TIPS liquidity premium and to extract underlying inflation expectations. (JEL E31, E43, H63)

ABSTRACT This paper investigates the drivers of long term real interest rates in Brazil. It is shown that long term yield on inflation linked bonds are driven by yields on 10 year interest rates of United States (US) government bonds and 10 year risk premium, as measured by the Credit Default Swap (CDS). Long term interest rates in Brazil were on a downward trend, following US real rates and stable risk premium, until the taper tantrum in the first half of 2013. From then onwards, real interest rates rose due to the increase in US real rates in anticipation of the beginning of monetary policy normalization and, more recently, due to a sharp increase in Brazilian risk premium. Policy interest rates do not significantly affect long term real interest rates.

his paper presents an equilibrium bond-pricing model that jointly explains the upward-sloping nominal and real yield curves and the violation of the expectations hypothesis. Instead of relying on the inflation risk premium, the ambiguity-averse agent faces different amounts of Knightian uncertainty in the long run versus the short run; hence the model-implied nominal and real short rate expectations are upward-sloping under the agent's worst-case equilibrium beliefs. The expectations hypothesis roughly holds under investors' worst-case beliefs. The difference between the worst-case scenario and the true distribution makes realized excess returns on long-term bonds predictable.

Data and code for peer-reviewed article published in American Economic Review: Insights.

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)

As of July 18, 2025, the major economy with the highest yield on 10-year government bonds was Turkey, with a yield of ** percent. This is due to the risks investors take when investing in Turkey, notably due to high inflation rates potentially eradicating any profits made when using a foreign currency to investing in securities denominated in Turkish lira. Of the major developed economies, United Kingdom had one the highest yield on 10-year government bonds at this time with **** percent, while Switzerland had the lowest at **** percent. How does inflation influence the yields of government bonds? Inflation reduces purchasing power over time. Due to this, investors seek higher returns to offset the anticipated decrease in purchasing power resulting from rapid price rises. In countries with high inflation, government bond yields often incorporate investor expectations and risk premiums, resulting in comparatively higher rates offered by these bonds. Why are government bond rates significant? Government bond rates are an important indicator of financial markets, serving as a benchmark for borrowing costs, interest rates, and investor sentiment. They affect the cost of government borrowing, influence the price of various financial instruments, and serve as a reflection of expectations regarding inflation and economic growth. For instance, in financial analysis and investing, people often use the 10-year U.S. government bond rates as a proxy for the longer-term risk-free rate.

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)

Term premia implied by maximum likelihood estimates of affine term structure models are misleading because of small-sample bias. We show that accounting for this bias alters the conclusions about the trend, cycle, and macroeconomic determinants of the term premia estimated in Wright (2011). His term premium estimates are essentially acyclical, and often just parallel the secular trend in longterm interest rates. In contrast, bias-corrected term premia show pronounced countercyclical behavior, consistent with theoretical and empirical arguments about movements in risk premia.