The impact of uncertainty on professional exchange rate forecasts

This paper analyzes the role of uncertainty on both exchange rate expectations and forecast errors of professionals for four major currencies based on survey data provided by FX4casts. We consider economic policy, macroeconomic, and financial uncertainty as well as disagreement among CPI inflation forecasters to account for different dimensions of uncertainty. Based on a Bayesian VAR approach, we observe that uncertainty effects on forecast errors of professionals turn out to be more significant compared to the adjustment of exchange rate expectations. Our findings are robust to different forecasting horizons and point to an unpredictable link between exchange rates and fundamentals. Furthermore, we illustrate the importance of considering common unpredictable components for a large number of variables. We also focus on the post-crisis period and the relationship between uncertainty and disagreement among exchange rate forecasters and identify a strong relationship between them.     

Measuring Inflation Expectations Uncertainty Using High‐Frequency Data

Inflation expectations play a key role in determining future economic outcomes. The associated uncertainty provides a direct gauge of how well‐anchored the inflation expectations are. We construct a model‐based measure of inflation expectations uncertainty by augmenting a standard unobserved components model of inflation with information from noisy and possibly biased measures of inflation expectations obtained from financial markets. This new model‐based measure of inflation expectations uncertainty is more accurately estimated and can provide valuable information for policymakers. Using U.S. data, we find significant changes in inflation expectations uncertainty during the Great Recession.     

New Measures for Inflation Uncertainty and Disagreement from Treasury Auctions: Alternative to Surveys

In this article, we propose a novel methodology to construct new uncertainty and disagreement measures for the long-term inflation rate with the use of micro data of Treasury auctions. We employ individual bids submitted in Treasury auctions for nominal and inflation indexed bonds. We argue that these newly formed indicators do not have the problems associated with the survey and market-based uncertainty and disagreement measures. We also focus on the interactions of our proposed measures for inflation rate by comparing the measures commonly used in the literature. The findings of this article are believed to enhance the effectiveness of policy-making by introducing new proxies for crucial economic variables and also by providing the opportunity for other emerging economies with inadequate surveys to construct historical uncertainty and disagreement measures for inflation rates.     

The long-run equity risk premium

Based on a survey of US Chief Financial Officers (CFOs), we present expectations of the equity risk premium measured over a 10-year horizon relative to a 10-year US Treasury bond. This multi-year survey has been conducted each quarter from June 2000 to June 2005. Each quarter the survey also provides measures of cross-sectional disagreement about the risk premium, skewness, and a measure of individual uncertainty. The individual uncertainty is deduced from the 80% confidence interval that each respondent provides for his or her risk premium assessment. We also present evidence on the determinants of the long-run risk premium. Our analysis suggests there is a positive correlation between the ex ante risk premium and real interest rates as reflected in Treasury Inflation Indexed Notes.     

Economic policy uncertainty and stock price crash risk

This paper studies the impact of economic policy uncertainty on stock price crash risk using data from China. We develop a new index to measure Chinese economic policy uncertainty and find that economic policy uncertainty has a remarkable positive effect on stock price crash risk. However, the effect reverses later. The results also indicate that the positive effect of economic policy uncertainty on stock price crash risk is more prominent for state‐owned enterprises. Moreover, this effect is more prominent for firms with higher information asymmetry and firms with greater disagreement among investors, indicating that economic policy uncertainty affects crash risk through two mechanisms: managers’ concealment of bad news and investors’ heterogeneous beliefs.     

Disagreement and Learning: Dynamic Patterns of Trade

The empirical evidence on investor disagreement and trading volume is difficult to reconcile in standard rational expectations models. We develop a dynamic model in which investors disagree about the interpretation of public information. We obtain a closed‐form linear equilibrium that allows us to study which restrictions on the disagreement process yield empirically observed volume and return dynamics. We show that when investors have infrequent but major disagreements, there is positive autocorrelation in volume and positive correlation between volume and volatility. We also derive novel empirical predictions that relate the degree and frequency of disagreement to volume and volatility dynamics.     

Bidder behavior in central bank repo auctions: Evidence from the Bundesbank

For many central banks, repo auctions are the most important monetary policy instrument. This paper employs a unique data set of individual bids submitted in the repo auctions of the Bundesbank to analyze the determinants of banks’ bidding behavior and the empirical performance of repo auctions. We conduct a panel analysis to estimate how banks bidding is affected by various auction as well as bidder-specific factors including interest rate expectations, interest rate uncertainty, maturing allotment, reserve fulfillment and a bank’s size.     

Why disagreement may not matter (much) for asset prices

A simple consumption-based two-period model is used to study the (theoretical) effects of disagreement on asset prices. Analytical and numerical results show that individual uncertainty has a much larger effect on risk premia than disagreement if (i) the risk aversion is reasonably high and (ii) individual uncertainty is not much smaller than disagreement. Evidence from survey data on beliefs about output growth suggests that the latter is more than satisfied.     

Why Does Return Predictability Concentrate in Bad Times?

We build an equilibrium model to explain why stock return predictability concentrates in bad times. The key feature is that investors use different forecasting models, and hence assess uncertainty differently. As economic conditions deteriorate, uncertainty rises and investors' opinions polarize. Disagreement thus spikes in bad times, causing returns to react to past news. This phenomenon creates a positive relation between disagreement and future returns. It also generates time‐series momentum, which strengthens in bad times, increases with disagreement, and crashes after sharp market rebounds. We provide empirical support for these new predictions.     

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.     

Disagreement and asset prices

How do differences of opinion affect asset prices? Do investors earn a risk premium when disagreement arises in the market? Despite their fundamental importance, these questions are among the most controversial issues in finance. In this paper, we use a novel data set that allows us to directly measure the level of disagreement among Wall Street mortgage dealers about prepayment speeds. We examine how disagreement evolves over time and study its effects on expected returns, return volatility, and trading volume in the mortgage-backed security market. We find that increased disagreement is associated with higher expected returns, higher return volatility, and larger trading volume. These results imply that there is a positive risk premium for disagreement in asset prices. We also show that volatility in and of itself does not lead to higher trading volume. Instead, only when disagreement arises in the market is higher uncertainty associated with more trading. Finally, we are able to distinguish empirically between two competing hypotheses regarding how information in markets gets incorporated into asset prices. We find that sophisticated investors appear to update their beliefs through a rational expectations mechanism when disagreement arises.     

Forecast uncertainty and the Taylor rule

In this paper, we derive a modification of a forward-looking Taylor rule by integrating two variables that measure the uncertainty of inflation and GDP growth forecasts into an otherwise standard New Keynesian model. We show that certainty-equivalence in New Keynesian models is a consequence of log-linearization and that a second-order Taylor approximation leads to a reaction function that includes the uncertainty of macroeconomic expectations. To test the model empirically, we use the standard deviation of individual forecasts around the median Consensus Forecast as a proxy for forecast uncertainty. Our sample covers the euro area, the United Kingdom, and the United States for the period 1990Q1–2016Q4. We find that the Bank of England and the European Central Bank have a significantly negative reaction to inflation forecast uncertainty. Our findings also reveal that the Federal Reserve (Bank of England) lowers (raises) its interest rate in response to higher GDP growth forecast uncertainty. We conclude by offering some implications for optimal monetary policy rules and central bank watchers.     

Forecasting global stock market volatilities in an uncertain world

We investigate the predictive relationship between uncertainty and global stock market volatilities from a high-frequency perspective. We show that uncertainty contains information beyond fundamentals (volatility) and strongly affects stock market volatility. Using several crucial uncertainty measures (i.e., uncertainty and implied volatility indices), we prove that the CBOE volatility index (VIX) performs best in point (density) forecasting; the financial stress index (FSI) in directional forecasting. Furthermore, VIX's predictive power improved dramatically after the COVID-19 outbreak, and the VIX-based portfolio strategy enables mean-variance investors to achieve higher returns. There are two empirical properties of VIX: (i) it helps reduce significantly forecast variance rather than bias; and (ii) its forecasts encompass other uncertainty forecasts well. Overall, we highlight the importance of considering uncertainty when exploring the expected stock market volatility.     

Too Good to be True? An Analysis of the Options Market's Reactions to Earnings Releases

Using option implied risk neutral return distributions before and after earnings announcements, we study the option market's reaction to extreme events over earnings announcements. While earnings announcements generally reduce short‐term uncertainty about the stock price, very good news does not reduce uncertainty and slightly bad news actually increases uncertainty. We also find that left tail probabilities decrease over earnings releases while right tail probabilities increase. We interpret these findings as evidence of maintained investor expectations that very good news is generally not released during earnings announcements, combined with skepticism in the form of lingering uncertainty at the release of such very good news.     

Market ambiguity and individual investor information demand

We examine whether ambiguity in the market leads to an increase in information demand by individual investors. Drawing on the asset-pricing model proposed by Mele and Sangiorgi (2015), which incorporates market ambiguity, we measure individual information demand using daily Google searches and measure market ambiguity using a metric based on the market trades of institutional investors. We find that individual investors increase their information demand during periods of greater market ambiguity. We also provide evidence that information demand from individual investors spikes around earnings announcement days primarily when market uncertainty is driven by net-selling activity. Overall, these results suggest that the disagreement among institutional investors either represents uncertainty or contributes to the uncertainty related to a stock, leading to increased demand for information from individual investors.     

Disagreement and the Cost of Capital

We assess how forms of disagreement among investors affect a firm's cost of capital. Firms experience a lower cost of capital if investors perceive that other investors are ignoring relevant disclosures (perceived errors of omission), but a higher cost of capital if investors perceive that others are responding to irrelevant disclosures (perceived errors of commission). The impact of these two sources of disagreement on the cost of capital is determined by the distribution of opinion and the nature of disclosure. For example, even though aggregated disclosures reveal less to investors, aggregated disclosures may decrease the cost of capital by eliminating disagreement associated with perceived errors of commission. These and additional results arise because the cost of capital is driven not only by investors’ uncertainty about the firm's future earnings performance, but also by investors’ uncertainty about the evolution of beliefs, which partly determines the path of prices.     

商业保险对居民消费影响研究——基于中国省级面板数据的经验证据

当前中国经济社会处于快速转型期,伴随着改革进程的不确定性风险日趋凸显,成为制约居民消费进一步扩张的重要因素。本文采用2003~2017年中国省级面板数据,考察了商业保险对居民消费行为的影响效应及其作用机制。研究发现,以商业保险密度和保险强度为表征的商业保险发展对居民消费有着显著正向影响,相较于农村居民消费,商业保险对城镇居民呈现更强的消费效应,同时财产保险消费效应明显高于人身保险对居民消费影响,进一步地,中介效应检验发现,不确定性缓解可能是商业保险影响居民消费的一个重要机制。基于此,本文认为,构筑完善的商业保险服务体系对于启动居民消费具有重要意义。     

Rare disaster risk and the expected equity risk premium

Consistent with the predictions of rare disaster models, we find that a proxy for the time‐varying probability of rare disasters helps to explain fluctuations in expectations of the equity risk premium. Our proxy for disaster risk is a recently developed measure of global political instability, and the expected market risk premium is from Value Line analysts' expected stock returns. Consistent with long‐run risk models, uncertainty about expected GDP growth and expected consumption growth is also significantly positively related to the expected market risk premium. We obtain similar results when we use the earnings–price ratio and the dividend–price ratio as proxies for the expected market risk premium.     

Consumption risk and the cross-section of government bond returns

In this paper we provide a consumption-based explanation of risk in nominal US Treasury bond portfolios. We use a consumption-CAPM with Epstein–Zin–Weil recursive preferences. Our model introduces two sources of risk: uncertainty about current consumption (reflected in contemporaneous consumption growth) and uncertainty about prospects of consumption in a long run (reflected in innovations to expectations about future consumption growth). We use a novel approach to estimate pricing factors in our model: we employ a factor-augmented VAR model with common factors, extracted from a large panel of macroeconomic and financial data, as state variables. We find that the important source of risk in US bonds is related to uncertainty in prospects in future consumption and it induces a positive and significant risk premium. We find as well that covariance risk related to innovations in expectations about future consumption growth is greater for long term bond portfolios than for short term bond portfolios, which is consistent with a duration measure of risk and justifies why long term bonds require greater premium than short term bonds. Our model explains well the cross-sectional variation in average excess returns of bonds with different maturities over the period 1975–2011 and compares favorably with competing models.     

The Great Capitol Hill Baby Sitting Co‐op: Anecdote or Evidence for the Optimum Quantity of Money?

This paper studies a centralized market with idiosyncratic uncertainty and money as a medium of exchange from a theoretical as well as an experimental perspective. In our model, prices are fixed and markets are cleared by rationing. We prove the existence of stationary monetary equilibria and of an optimum quantity of money. The rational solution of our model, which is based on the assumption of individual rationality and rational expectations, is compared with actual behavior in a laboratory experiment. The theoretical results are strongly supported by this experiment.