Gold price dynamics and the role of uncertainty

This study focuses on the dynamics of the gold price against bonds, stocks and exchange rates based on a disaggregation of the underlying relationships across different frequencies applying a wavelet decomposition. To analyze joint extreme movements (i.e. tail dependence), we adopt a copula approach, which helps us to assess the dependence between the returns of gold and other assets in calm and turmoil market times and therefore the hedge and safe haven functions of gold. We also examine whether gold prices are directly affected by changes in macroeconomic uncertainty, economic policy uncertainty and/or CPI forecasters disagreement. Analyzing data for nine economies for a sample period starting in 1985, we find that the role of gold changes significantly after the collapse of Lehman Brothers in 2008. Gold is unable to serve as a hedge or safe haven in the classical sense while the findings for the period prior to 2008 mostly suggest that gold is able to shield investors. Uncertainty measures display a surprising and time-varying relationship with the path of the gold price. While economic policy uncertainty is positively correlated with gold price changes, macroeconomic uncertainty and inflation uncertainty among forecasters are both negatively related to gold price changes.     

The Role of Media for Inflation Forecast Disagreement of Households and Professional Forecasters

This paper investigates the effects of media coverage about consumer price inflation on inflation forecast disagreement of German households and professional forecasters. We adopt a Bayesian learning model in which media coverage of inflation affects forecast disagreement by influencing information sets as well as predictor choice. Our empirical results show that disagreement of households depends on the heterogeneity of story content and on the reporting intensity, especially of news on rising inflation. Disagreement of professional forecasters does not depend on media coverage. With respect to the influence of macroeconomic variables, we provide evidence that disagreement of professional forecasters primarily depends on the inflation rate and on inflation volatility. The response of households to inflation is much less pronounced.     

A Closer Look at the Behavior of Uncertainty and Disagreement: Micro Evidence from the Euro Area

This paper examines point and density forecasts of real GDP growth, inflation, and unemployment from the European Central Bank's Survey of Professional Forecasters. We analyze individual uncertainty measures as well as introduce individual point‐ and density‐based disagreement measures. The analysis indicates forecasters’ uncertainty and disagreement display substantial heterogeneity and persistence, with the latter feature challenging a key prediction of expectations models emphasizing information frictions. We also find that uncertainty is characterized by prominent respondent effects and disagreement by prominent time effects, suggesting these divergent properties underlie the well‐documented weak uncertainty–disagreement linkage. Taken together, our results provide a basis for further development of expectations models.     

Disagreement and Biases in Inflation Expectations

Disagreement in inflation expectations observed from survey data varies systematically over time in a way that reflects the level and variance of current inflation. This paper offers a simple explanation for these facts based on asymmetries in the forecasters' costs of over- and underpredicting inflation. Our model implies (i) biased forecasts, (ii) positive serial correlation in forecast errors, (iii) a cross-sectional dispersion that rises with the level and the variance of the inflation rate, and (iv) predictability of forecast errors at different horizons by means of the spread between the short- and long-term variance of inflation. We find empirically that these patterns are present in inflation forecasts from the Survey of Professional Forecasters. A constant bias component, not explained by asymmetric loss and rational expectations, is required to explain the shift in the sign of the bias observed for a substantial portion of forecasters around 1982.     

Inattentive professional forecasters

Using the ECB Survey of Professional Forecasters to characterize expectations at the micro-level, we emphasize two new facts: forecasters (i) fail to systematically update their forecasts and (ii) disagree even when updating. It is moreover found that forecasters have predictable forecast errors. These facts are qualitatively supportive of recent models of inattention and suggest a setup where agents imperfectly process information due to both sticky information à la Mankiw–Reis, and noisy information à la Sims. However, building and estimating such an expectation model, we find that it cannot quantitatively replicate the error and disagreement observed in the data.     

Two currencies,one model? Evidence from the Wall Street Journal forecast poll

We use the foreign exchange forecasts of the Wall Street Journal (WSJ) poll to analyze the expectation formation process of forecasters for the exchange rates of the euro and the yen vis-à-vis the U.S. dollar for the period 1999–2005. We also compare the expectation formation process with the actual exchange rate process. We find that most forecasters have contrarian exchange rate expectations, but our results also indicate significant heterogeneity between forecasters. While the actual exchange rate process of the yen/dollar exchange rate shows negative autocorrelation, the dollar/euro exchange rate exhibits positive autocorrelation.     

Differential Interpretation in the Survey of Professional Forecasters

In this paper, I estimate a simple Bayesian learning model to expectations data from the Survey of Professional Forecasters. I reformulate the model in terms of forecast revisions, which allows one to abstract from differences in priors and to focus the analysis on the relationship between news and revisions. The empirical analysis shows that there is significant heterogeneity in the interpretation of news among forecasters, in particular at longer horizons, while it decreases closer to the forecast target date. The results also indicate a positive relationship between prior sentiment and interpretation of the signal, in the sense that relatively optimistic (pessimistic) forecasters are likely to believe that the signal under (over) estimates the future realization and assign it a low (high) weight in the forecast revision.     

The impact of risk and uncertainty on expected returns

We study asset pricing in economies featuring both risk and uncertainty. In our empirical analysis, we measure risk via return volatility and uncertainty via the degree of disagreement of professional forecasters, attributing different weights to each forecaster. We empirically model the typical risk-return trade-off and augment these models with our measure of uncertainty. We find stronger empirical evidence for an uncertainty-return trade-off than for the traditional risk-return trade-off. Finally, we investigate the performance of a two-factor model with risk and uncertainty in the cross section.     

Survey forecasts in Brazil: A prismatic assessment of epidemiology,performance, and determinants

This paper assesses the behavior of survey forecasts in Brazil during the inflation targeting regime, when managing expectations is one of the cornerstones of the conduct of monetary policy. The distinctive database of the survey conducted by the Central Bank of Brazil (BCB) among professional forecasters allows for a thorough investigation of the epidemiology, determinants, and performance of forecasts. The main results are: i) top performing forecasters are influential to other forecasters; ii) survey forecasts perform better than vector autoregressive model-based forecasts; iii) common forecast errors prevail over idiosyncratic components across respondents; iv) inflation targets play an important role in inflation expectations; and v) agents perceive the BCB as following a Taylor rule consistent with inflation targeting. The last two suggest high credibility of the monetary authority.     

Fundamental disagreement

We document a novel set of facts about disagreement among professional forecasters: (1) forecasters disagree at all horizons, including the long run; (2) the term structure of disagreement is downward sloping for real output growth, relatively flat for inflation, and upward sloping for the federal funds rate; (3) disagreement is time varying at all horizons. We propose a generalized model of imperfect information that can jointly explain these facts. We further use the term structure of disagreement to show that the monetary policy rule perceived by professional forecasters features a high degree of interest-rate smoothing and time variation in the intercept.     

News on Inflation and the Epidemiology of Inflation Expectations

This paper examines the nexus between news coverage on inflation and households’ inflation expectations. In doing so, we test the epidemiological foundations of the sticky information model (Carroll 2003, 2006 ). We use both aggregate and household‐level data from the Survey Research Center at the University of Michigan. We highlight a fundamental disconnection among news on inflation, consumers’ frequency of expectation updating, and the accuracy of their expectations. Our evidence provides at best weak support to the epidemiological framework, as most of the consumers who update their expectations do not revise them toward professional forecasters’ mean forecast.     

Signals from the government: Policy disagreement and the transmission of fiscal shocks

We investigate the effects of fiscal policy communication on the propagation of government spending shocks. To this aim, we propose a new index measuring the coordination effects of policy communication on private agents׳ expectations. This index is based on the disagreement amongst US professional forecasters about future government spending. The underlying intuition is that a clear fiscal policy communication can coalesce expectations, reducing disagreement. Results indicate that, in times of low disagreement, the output response to fiscal spending innovations is positive and large, mainly due to private investment response. Conversely, periods of elevated disagreement are characterised by muted output response.     

What do professional forecasters' stock market expectations tell us about herding,information extraction and beauty contests?

We study how professional forecasters form equity market expectations based on a new micro-level dataset which includes rich cross-sectional information about individual characteristics. We focus on testing whether agents rely on the beliefs of others, i.e., consensus expectations, when forming their own forecast. We find strong evidence that the average of all forecasters' beliefs influences an individual's own forecast. This effect is stronger for young and less experienced forecasters as well as forecasters whose pay depends more on performance relative to a benchmark. Further tests indicate that neither information extraction to incorporate dispersed private information, nor herding for reputational reasons can fully explain these results, leaving Keynes' beauty contest argument as a potential candidate for explaining forecaster behavior.     

Nonlinear exchange rate predictability

We study whether the nonlinear behavior of the real exchange rate can help us account for the lack of predictability of the nominal exchange rate. We construct a smooth nonlinear error-correction model that allows us to test the hypotheses of nonlinear predictability of the nominal exchange rate and nonlinear behavior on the real exchange rate in the context of a fully specified cointegrated system. Using a panel of 19 countries and three numeraires, we find evidence of nonlinear predictability of the nominal exchange rate and of nonlinear mean reversion of the real exchange rate. Out-of-sample Theil’s U -statistics show a higher forecast precision of the nonlinear model than the one obtained with a random walk specification. Although the robustness of the out-of-sample results over different forecast windows is somewhat limited, we are able to obtain significant predictability gains—from a parsimonious structural model with PPP fundamentals—even at short-run horizons.     

Forecasting exchange rates: Do banks know better?

We first evaluate the performance of major commercial banks in forecasting future spot exchange rates, using the random-walk model as the benchmark. We then investigate the sources of forecast errors, and the forecasting tendencies of banks. Our analysis is based on the forecasts made for the US dollar exchange rates of the British pound (BP), German mark (DM), Swiss franc (SF), and Japanese yen (JY), over 3-, 6-, 9-, and 12-month forecast horizons. Key findings include: first, a majority of banks shows some evidence of outperforming the random-walk model for the three currencies other than the JY. Second, the imperfect correlation between predicted and actual exchange rate changes is the dominant source of prediction errors of banks. Third, the home-country bank generally forecasts the country's currency rate more accurately than the other banks, suggesting a degree of information asymmetry. Fourth, the forecasts of a majority of banks exhibit a bandwagon type effect. That is, most banks are momentum forecasters, tending to extrapolate the recent currency changes. Interestingly, a “contrarian” bank is found to outperform the other banks.     

Why do forecasters disagree? Lessons from the term structure of cross-sectional dispersion

Key sources of disagreement among economic forecasters are identified by using data on cross-sectional dispersion in forecasters’ long- and short-run predictions of macroeconomic variables. Dispersion among forecasters is highest at long horizons where private information is of limited value and lower at short forecast horizons. Moreover, differences in views persist through time. Such differences in opinion cannot be explained by differences in information sets; our results indicate they stem from heterogeneity in priors or models. Differences in opinion move countercyclically, with heterogeneity being strongest during recessions where forecasters appear to place greater weight on their prior beliefs.     

The impact of the U.S. employment report on exchange rates

The impact of the U.S. Employment Report and analyst forecasts of that report’s major statistics on Pound/Dollar, Yen/Dollar, and Euro/Dollar exchange rates are explored. While the nonfarm payroll employment figure has the greatest impact, we find that the exchange rates also react to the announced revision to last month’s payroll figure and to the unemployment rate. In all three markets, the exchange rate response to the payroll employment figure is strongly conditioned on pre-release analyst uncertainty. The median analyst forecast from Bloomberg anticipates over 80% of the monthly variation in the payroll figure and is basically unbiased. The markets appear to respond to these analyst forecasts prior to the government release. Analyst forecast dispersion tends to increase following large forecast errors indicating that when the announced figure is far from what analysts expected, they tend to disagree on the implications for future payroll levels.     

Does foreign exchange risk matter to equity research analysts when forecasting stock prices? Evidence from U.S. firms

We study the relationship between the foreign exchange risk and analyst target price forecast error using U.S. firm-level data for the sample period between 1999 and 2014. We find that the target price forecast error is higher when foreign exchange risk is higher. The relationship is stronger for smaller firms and less pronounced among financial firms. Collectively, the findings suggest that analysts make fewer errors when forecasting for firms that are more capable of managing foreign exchange risks. These findings imply that either analyst does not make a significant effort in incorporating foreign exchange risk into their forecast models, or they do not have the skills for that task.     

Explaining exchange rate anomalies in a model with Taylor-rule fundamentals and consistent expectations

We introduce boundedly-rational expectations into a standard asset-pricing model of the exchange rate, where cross-country interest rate differentials are governed by Taylor-type rules. Agents augment a lagged-information random walk forecast with a term that captures news about Taylor-rule fundamentals. The coefficient on fundamental news is pinned down using the moments of observable data such that the resulting forecast errors are close to white noise. The model generates volatility and persistence that is remarkably similar to that observed in monthly exchange rate data for Canada, Japan, and the U.K. Regressions performed on model-generated data can deliver the well-documented forward premium anomaly.     

Do Macroforecasters Herd?

We show that typical tests of whether forecasters herd will falsely indicate herding behavior for a variety of types of behavior and forecasting environments that give rise to disagreement among forecasters. We establish that forecasters will appear to herd if differences between them reflect noise as opposed to private information, or if they arise from informational rigidities. Noise can have a behavioral interpretation and if so will depend on the behavioral model under consideration. An application of the herding tests to U.S. quarterly survey forecasts of inflation and output growth data 1981–2013 does not support herding behavior.