Policy impact studies often suffer from endogeneity problems. Consider the case of the ECB Securities Markets Programme. If Eurosystem interventions were triggered by sudden and strong price deteriorations, looking at daily (or weekly) price changes may bias downwards the correlation between...

Motivated by policy statements of central bankers, we propose to regard the central banker as a risk manager who aims at containing inflation and the deviation of output from potential within pre-specified bounds. We develop formal tools of risk management that may be used to quantify the risks...

In deciding a monetary policy stance, central bankers need to evaluate carefully the risks the current economic situation poses to price stability. We propose to regard the central banker as a risk manager who aims to contain inflation within pre-specified bounds. We develop formal tools of risk...

This paper deals with the estimation of the risk-return trade-off. We use a MIDAS model for the conditional variance and allow for possible switches in the risk-return relation through a Markov-switching specification. We find strong evidence for regime changes in the risk-return relation. This...

We combine self-collected historical data from 1867 to 1907 with CRSP data from 1926 to 2012, to examine over 140 years of risk and return of one of the most popular mechanical trading strategies—momentum. We find that the momentum strategy has earned abnormally high risk-adjusted returns—a...

We consider estimating volatility risk factors using large panels of filtered or realized volatilities. The data structure involves three types of asymptotic expansions. There is the cross-section of volatility estimates at each point in time, namely i = 1,…, N observed at dates t = 1,…, T:...

It is well known that temporal aggregation has adverse effects on Granger causality tests. Time series are often sampled at different frequencies. This is typically ignored, and data are merely aggregated to the common lowest frequency. We develop a set of Granger causality tests that explicitly...

Can we design statistical models to predict corporate earnings which either perform as well as, or even better than analysts? If we can, then we might consider automating the process, and notably apply it to small and international firms which typically have either sparse or no analyst coverage....

We examine the effects of mixed sampling frequencies and temporal aggregation on standard tests for cointegration. We find that the effects of aggregation on the size of the tests may be severe. Matching sampling schemes of all series generally reduces size, and the nominal size is obtained when...

This paper presents an innovative approach to extracting factors which are shown to predict the VIX, the S&P 500 Realized Volatility and the Variance Risk Premium. The approach is innovative along two different dimensions, namely: (1) we extract factors from panels of filtered volatilities - in...