This article proposes a functional dynamic factor model for the evaluation of the impact of scalar– and curve–valued factors on the shapes of intraday price curves. The asymptotic theory leads to practically useful confidence intervals for the factor coefficients. The main findings pertain to the impact of the shapes of intraday oil futures on the shapes of intraday prices of blue chip stocks. ...

This paper studies the information content of some Ifo indicators. In particular, we investigate whether two Ifo indicators, one on the current business situation, the other on current production development, provide information on revisions of German industrial production. A new feature of our analysis is the construction and use of a real-time dataset. We conclude that the Ifo indicators play...

This paper offers an explanation for stock market crashes which focuses on the role of rational but uninformed traders. We show that uninformed traders can precipitate a price crash because as prices decline, they surmise that informed traders received negative information, which leads them to reduce their demand for assets and drive the price of stocks even lower. The model yields several impl...

This paper develops a Bayesian quantile regression model with time-varying parameters (TVPs) for forecasting inflation risks. The proposed parametric methodology bridges the empirically established benefits of TVP regressions ability to flexibly whole distribution inflation. In order make our approach accessible and relevant forecasting, we derive an efficient Gibbs sampler by transforming stat...

We propose a dynamic model for financial market volatility with an heterogeneous structure for three components: continuous volatiilty, leverage and jumps. We find that each of the three components plays a significant role in volatility forecasting and neglecting one of them is detrimental to the forecasting performance. Importantly, we find remarkable forecasting power for the negative past re...

Technical traders base their analysis on the premise that the patterns in market prices are assumed to recur in the future, and thus, these patterns can be used for predictive purposes. This paper uses the daily Dow Jones Industrial Average Index from 1897 to 1988 to examine the linear and nonlinear predictability of stock market returns with simple technical trading rules. The nonlinear specif...

Prediction Markets in Theory and Practice Prediction Markets, sometimes referred to as “information markets,” “idea futures” or “event futures”, are markets where participants trade contracts whose payoffs are tied to a future event, thereby yielding prices that can be interpreted as market-aggregated forecasts. This article summarizes the recent literature on prediction markets, highlighting b...

Recently, investment in high technology companies boomed as people invested large sums of money even when there was little chance of the company being profitable. This is contrary to classical beliefs that investors have rational expectations and maximise their utility. Instead we must consider the idea that people are irrational and make decisions for many reasons, few of which involve a judic...

Modeling financial volatility is an important part of empirical finance. This paper provides a literature review of the most relevant volatility models, with a particular focus on forecasting models. We firstly discuss the empirical foundations of different kinds of volatility. The paper, then, analyses the non-parametric measure of volatility, named realized variance, and its empirical applica...

This paper identifies two channels through which the economy can generate endogenous inflation and output volatility, an empirical regularity, by introducing model uncertainty into a Lucas-type monetary model. The equilibrium path of inflation depends on agents’ expectations and a vector of exogenous random variables. Following Branch and Evans (2006a) agents are assumed to underparameterize th...