While economic variables have been used extensively to forecast the U.S. bond risk premia, little attention has been paid to the use of technical indicators which are widely employed by practitioners. In this paper, we fill this gap by studying the predictive ability of using a variety of technical indicators vis-á-vis the economic variables. We find that the technical indicators have significa...

This paper applies the Model Confidence Set (MCS) procedure of Hansen, Lunde, and Nason (2003) to a set of volatility models. A MCS is analogous to confidence interval of a parameter in the sense that the former contains the best forecasting model with a certain probability. The key to the MCS is that it acknowledges the limitations of the information in the data. The empirical exercise is base...

This paper utilizes the nonparametric functional autoregressive approach (FAR) to model the time-varying distribution of UK monthly inflation rates using disaggregated cross-sectional data. Our approach is free of any assumptions on the class or structure of the density functions themselves, or the number of dimensions in which the densities may vary. The “pseudo real time” in-sample forecastin...

“Nudge”-style interventions are typically evaluated on the basis of their effects on behavior, not social welfare. We use a field experiment to measure the welfare effects of one especially policy-relevant intervention, home energy conservation reports. We measure consumer welfare by sending introductory reports and using an incentive-compatible multiple price list to determine willingness-to-p...

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...

We investigate the relationship between low-level incidents of political violence and communication patterns seven months after the 2012 Ivorian Civil War using network traffic from all of Orange Telecom’s Côte d’Ivoire cell towers and 500,000 randomly sampled cell phone subscribers. We first show that in the days preceding small violent incidents, mobile phone call volumes increase by 10% and ...

This paper contains a forecasting exercise on 30 time series, ranging on several fields, from economy to ecology. The statistical approach to artificial neural networks modelling developed by the author is compared to linear modelling and to other three well-known neural network modelling procedures: Information Criterion Pruning (ICP), Cross-Validation Pruning (CVP) and Bayesian Regularization...

Factor models have been successfully employed in summarizing large datasets with few underlying latent factors and in building time series forecasting models for economic variables. When the objective is to forecast a target variable y with a large set of predictors x, the construction of the summary of the xs should be driven by how informative on y it is. Most existing methods first reduce th...

This paper considers the issue of forecasting financial fragility of banks and insurances using a panel data set of performance indicators, namely distance-todefault, taking unobserved common factors into account. We show that common factors are important in the performance of banks and insurances, analyze the influences of a number of observable factors on banking and insurance performance, an...

This paper provides an empirical comparison of various selection and penalized regression approaches for forecasting with vector autoregressive systems. In particular, we investigate the effect of the system size as well as the effect of various prior specification choices on the relative and overall forecasting performance of the methods. The data set is a typical macroeconomic quarterly data ...