We discuss the finding that cross-sectional characteristic based models have yielded portfolios with higher excess monthly returns but lower risk than their arbitrage pricing theory counterparts in an analysis of equity returns of stocks listed on the JSE. Under the assumption of general...

Fundaments of classification lie on the interdependences between the features and the labels to classify. For social parameters, this relationships are difficult to model and measure. In this paper, a way of obtaining a social indicator using sentiment analysis in Twitter is explained. With the...

This study compares a broad range of risk models for managing multi-asset portfolios. The investment universe is extended to a range of systematic strategies with varying risk and return profiles. Focusing on risk parity portfolios, it is shown that considering tail risks can successfully reduce...

This paper assesses the accuracy of decomposing income risk into permanent and transitory components using income and consumption data. We develop a specific approximation to the optimal consumption growth rule and use Monte Carlo evidence to show that this approximation can provide a robust...

This paper concerns the decomposition of income risk into permanent and transitory components using repeated cross-section data on income and consumption. Our focus is on the detection of changes in the magnitudes of variances of permanent and transitory risks. A new approximation to the optimal...

We develop a new approach to the decomposition of income risk within a nonstationary model of intertemporal choice. The approach allows for changes in income risk over the life-cycle and with the business cycle. It requires only repeated cross-section data and can allow for mixtures of...

Als Teil des operationellen Risikos stellt das Modellrisiko eine wichtige Komponente für die Risikoermittlung bei Finanzinstitutionen dar. Da letztere z.B. bei der Tarifierung und Bepreisung von Derivaten bzw. Portfolien oder bei der Markt- und Kreditrisikoberechnung auf stochastische Modelle...

This paper proposes a large-scale Bayesian vector autoregression with factor stochastic volatility to investigate the macroeconomic consequences of international uncertainty shocks in G7 countries. The curse of dimensionality is addressed by means of a global-local shrinkage prior that mimics...

In this paper we estimate a Bayesian vector autoregressive model with factor stochastic volatility in the error term to assess the effects of an uncertainty shock in the Euro area. This allows us to treat macroeconomic uncertainty as a latent quantity during estimation. Only a limited number of...

We develop a new approach to the decomposition of income risk within a non- stationary model of intertemporal choice. The approach allows for changes in in- come risk over the life cycle and across the business cycle, allowing for mixtures of persistent and transitory components in the dynamic...