In this paper, we illustrate the macroeconomic risk associated with the early stage of the corona-virus outbreak. Using monthly data ranging from July 1991 to March 2020 on a recently developed coincidence indicator of global output growth, we estimate an autoregressive model with GARCH effects...

In this paper, we analyse the heavy-tailed behaviour in the dynamics of housing-price returns in the United States. We investigate the sources of heavy tails by estimating autoregressive models in which innovations can be subject to GARCH effects and/or non-Gaussianity. Using monthly data...

This paper considers a simple Continuous Beliefs System (CBS) toinvestigate the effects on price dynamics of several behavioralassumptions: (i) herd behaviour; (ii) a-synchronous updating ofbeliefs; and (iii) heterogeneity in time horizons (memory) amongagents. The recently introduced concept of...

Empirical studies showed that many types of network traffic exhibit long-range dependence (LRD),i.e., burstiness on a wide variety of time-scales. Given that traffic streams are indeed endowed withLRD properties, a next question is: what is their impact on network performance? To assess...

We consider a queue fed by a large number, say n, of on-off sources with generally distributed on-and off-times. The queueing resources are scaled by n: the buffer is B=nb and link rate is C=nc.The model is versatile: it allows us to model both long range dependent traffic (by using heavy-tailed...

In this paper, we analyse Okun's law - a relation between the change in the unemployment rate and GDP growth - using data from Australia, the euro area, the United Kingdom and the United States. More specifically, we assess the relevance of non-Gaussianity when modelling the relation. This is...

Actual portfolios contain fewer stocks than are implied by standard financial analysis that balances the costs of diversification against the benefits in terms of the standard deviation of the returns. Suppose a safety first investor cares about downside risk and recognizes the heavytail feature...

Consider the portfolio problem of choosing the mix between stocks and bonds under a downside risk constraint. Typically stock returns exhibit fatter tails than bonds corresponding to their greater downside risk. Downside risk criteria like the safety first criterion therefore often select corner...

Estimators of regression coefficients are known to be asymptotically normally distributed, provided certain regularity conditions are satisfied. In small samples and if the noise is not normally distributed, this can be a poor guide to the quality of the estimators. The paper addresses this...

We develop a new model for the multivariate covariance matrix dynamics based on daily return observations and daily realized covariance matrix kernels based on intraday data. Both types of data may be fat-tailed. We account for this by assuming a matrix-F distribution for the realized kernels,...