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Forward rates in the money market are systematically higher than realised spot rates, reflecting an unobservable term premium. This paper uses a Kalman filter specification to produce time‐varying estimates of the term premia in New Zealand and Australia. Three time series specifications are used to examine the properties of the premia, such as the average size, volatility, and the degree of mean reversion. Compared to the constant term premia estimates, the time‐varying estimates explain significantly more of the difference between forward and spot rates. The results suggest that the premium in New Zealand is slowly mean‐reverting, while the Australian premium reverts quickly to the mean. It is not clear whether the method of monetary policy implementation affects the term premium, although in New Zealand the premium has been smaller and less variable since the introduction of the Official Cash Rate in March 1999. A related finding is that the size of the term premium is correlated with the volatility of short‐term rates.

The purpose of this paper is to estimate foreign direct investment (FDI) premia in the former Soviet states.

The authors follow an empirical approach. Using Orbis data for a sample of more than 3,000 companies, the authors characterize FDI involvement and FDI premia of firms from three distinctive groups of former Soviet states, designated “upper-middle”-income, “lower-middle”-income and “high”-income countries. This yields interesting within-group and between-group results on the effects of outward FDI (OFDI) and inward FDI (IFDI) on firm-level innovation.

The authors unveil new facts about innovation and FDI in the former Soviet states. FDI firms innovate more than non-FDI firms and OFDI firms innovate more than IFDI firms. The innovation effect of OFDI is the largest for firms from the “lower-middle” countries, followed by the “high” and “upper-middle” countries. The innovation effect of IFDI is the largest for firms from the “lower-middle” countries, followed by the “upper-middle” and “high” countries. FDI to and from Europe has the largest impact on innovation; this holds across country groups.

The estimates of this paper document robust FDI premia, i.e., a positive and significant correlation between firm-level innovation and FDI. However, the cross-sectional nature of the data does not permit a proper causality analysis.

The paper contributes to the literature on FDI premia by: considering IFDI and OFDI in a unified empirical framework; dissecting IFDI and OFDI by location; measuring firm-level productivity in terms of innovation; and providing cross-country comparable evidence on both emerging and advanced economies. At the same time, the paper contributes to the literature on FDI from emerging economies by: taking a firm-level quantitative approach; focusing on a relatively unexplored set of countries; and providing comparable cross-country evidence on both emerging and advanced economies.

The purpose of this paper is to forecast future inflation using a joint model of the nominal and real yield curves estimated with survey data. The model is arbitrage free and embodies incompleteness between the nominal and real bond markets.

The methodology is based on the affine class of term structure of interest rate. The model is estimated using the Kalman filter technique.

The authors show that the inclusion of survey data in the estimation procedure improves significantly the inflation forecasting. Moreover, the authors find that the monetary policy has significant effects on the inflation expectation and risk premium.

This paper is the first to estimate inflation using a joint model of nominal and real yield curves with Brazilian data. Moreover, the authors propose a simple arbitrage-free model that takes it account incompleteness between the nominal and real bond markets.

This study aims to spot wheat data and disaggregated commitment of trader data for CME traded wheat futures to examine the effect of exogenous shocks for hedging positions of Producers and Swap Dealers on cash-futures basis and excess futures returns.

A Bayesian vector autoregression (BVAR) methodology is used to capture volatility transfer effects.

Evidence is presented that institutional short hedging positions play a major role in the pricing of asymmetric information held by Swap Dealers into the basis. The results also indicate that producer hedging contains information when conditions in the supply chain create a shift in long vs short hedging demand. Finally, the results demonstrate that that Swap Dealer short hedging has the greatest effect on risk premium size and historical volatility.

Various proxies for spot prices are used in the literature, although actual spot price data is not common. In addition, stationarity for basis and open interest data is induced using the Baxter-King filter which allows us to work with levels, rather than percentage changes, in the time series data. This provides the ability to directly observe the effect of outright open interest positions for hedgers on contemporaneous innovations in basis and in excess returns. The use of a BVAR methodology represents an improvement over other structural VAR models by capturing contemporaneous systemic effects within an endogeneity based structural framework.

The purpose of this paper is to study the variance risk premium in corn and soybean markets, where the variance risk premium is defined as the difference between the historical realized variance and the corresponding risk-neutral expected variance.

The authors compute variance risk premiums using historical derivatives data. The authors use regression analysis and time series econometrics methods, including EGARCH and the Kalman filter, to analyze variance risk premiums.

There are moderate commonalities in variance within the agricultural sector, but fairly weak commonalities between the agricultural and the equity sectors. Corn and soybean variance risk premia in dollar terms are time-varying and correlated with the risk-neutral expected variance. In contrast, agricultural commodity variance risk premia in log return terms are more likely to be constant and less correlated with the log risk-neutral expected variance. Variance and price (return) risk premia in agricultural markets are weakly correlated, and the correlation depends on the sign of the returns in the underlying commodity.

Commodity variance (i.e. volatility) risk cannot be hedged using futures markets. The results have practical implications for US crop insurance programs because the implied volatilities from the relevant options markets are used to estimate the price volatility factors used to generate premia for revenue insurance products such as “Revenue Protection” and “Revenue Protection with Harvest Price Exclusion.” The variance risk premia found implies that revenue insurance premia are overpriced.

The empirical results suggest that the implied volatilities in corn and soybean futures market overestimate true expected volatility by approximately 15 percent. This has implications for derivative products, such as revenue insurance, that use these implied volatilities to calculate fair premia.

This study aims to document the time varying risk premia for market, size, value and momentum factors for an emerging market using a sophisticated conditional asset pricing model. The focus of this study is Turkish stock market denominated in local currency with its peculiar risk premia.

The authors employ Gagliardini et al.'s (2016) econometric method that uses cross-sectional and time series information simultaneously to infer the path of risk premia from individual stocks.

Using this methodology, the authors assess several conditioning information and conclude that local dividend yield, inflation and exchange rates have the most explanatory power. The authors document the time varying risk premia in Turkey over three decades.

Existing studies on dynamic estimation of risk premia lack a consensus as to which state variables should be included and to what extent they impact the magnitude of the premium. The authors extend the conditioning information set beyond the ones existing in the literature to determine variables that are specifically important for an emerging market.

This paper aims to study whether noisy public information that investors receive about the expected aggregate dividend growth rate can help better understand the large average equity premium and stock return volatility in the US financial market.

This paper considers a dynamic asset pricing model with a representative agent, who cannot observe the expected growth rate of dividends and must learn its value by using noisy information. In addition, this paper presents a simple model for noisy information calibration.

With a coefficient of relative risk aversion below 10 and the time impatience parameter between 0 and 1, the calibrated model is able to yield an average risk-free interest rate, equity premium and stock return volatility that are close to the stylized facts in the US financial market.

First, this paper presents a different equilibrium model with a simple “catching up with the Joneses” preference and noisy information. Second, this paper develops a simple calibration procedure to calibrate the information process to study whether the calibrated model can help explain the large average equity premium and stock return volatility in the US financial market data.

This paper aims to investigate the impact of uncertainty on the predictive power of term spread and its components for future stock market returns and economic activity in Korea and the USA. This paper finds that the stock market’s expected excess return and growth of economic activity are positively related to the risk-neutral expectation, one of the term spread’s components, particularly during high uncertainty periods. These findings are consistent with the importance of the monetary policy by the central bank in a high uncertainty environment created by unexpected shocks. The results are robust to alternate definitions of high uncertainty periods.

Long-term interest rates of small open economies (SOE) correlate strongly with the USA long-term rate. Can central banks in those countries decouple from the United States? An estimated Dynamic Stochastic General Equilibrium (DSGE) model for the UK (vis-á-vis the USA) establishes three structural empirical results: (1) Comovement arises due to nominal fluctuations, not through real rates or term premia; (2) the cause of comovement is the central bank of the SOE accommodating foreign inflation trends, rather than systematically curbing them; and (3) SOE may find themselves much more affected by changes in USA inflation trends than the United States itself. All three results are shown to be intuitive and backed by off-model evidence.

This study aims to explore the oil–stock market nexus from a novel angle by examining the predictive role of oil prices over the excess returns associated with the market, size, book-to-market and momentum factors via bivariate cross-quantilograms.

This study makes use of the bivariate cross-quantilogram methodology recently developed by Han et al. (2016) to analyze the predictability patterns across the oil and stock markets by focusing on various quantiles that formally distinguish between normal, bull and bear as well as extreme market states.

The study analysis of systematic risk premia across the four regions shows that crude oil returns indeed capture predictive information regarding excess factor returns in stock markets, particularly those associated with market, size and momentum factors. However, the predictive power of oil return over excess factor returns is asymmetric and primarily concentrated on extreme quantiles, suggesting that large fluctuations in oil prices capture markedly different predictive information over stock market risk premia during up and down states of the oil market.

The findings have significant implications for the profitability of factor- or style-based active portfolio strategies and suggest that the predictive information contained in oil market fluctuations could be used to enhance returns via conditional strategies based on these predictability patterns.

This study contributes to the vast literature on the oil–stock market nexus from a novel perspective by exploring the effect of oil price fluctuations on the risk premia associated with the systematic risk factors including market, size, value and momentum.