We develop a semiparametric model to track a large number of quantiles of a time series. The model satisfies the condition of non crossing quantiles and the defining property of fixed quantiles. A key feature of the specification is that the updating scheme for time varying quantiles at each...

This paper shows that different states of the financial system command a different effect in worsening financial conditions on economic vulnerability. As soon as financial conditions start deteriorating, the economic outlook becomes more pessimistic and uncertain. No increase in macroeconomic...

Quasi maximum likelihood estimation of Value at Risk (VaR) and Expected Shortfall (ES) is discussed. The reference likelihood is that of a location-scale asymmetric Laplace distribution, related to a family of loss functions that lead to strictly consistent scoring functions for joint estimation...

This paper addresses the problem of estimating multiple quantiles from a time series. A flexible class of dynamic multiple quantile (DMQ) models is specified, ensuring that estimated quantiles do not cross and that extreme quantiles are estimated by exploiting information coming from all the...

We study the properties of an M-estimator arising from the minimisation of an integrated version of the quantile loss function. The estimator depends on a tuning parameter which controls the degree of robustness. We show that the sample median and the sample mean are obtained as limit cases....

This paper studies the behaviour of Bitcoin returns at different sample frequencies. We consider high frequency returns starting from tick-by-tick price changes traded at the Bitstamp and Coinbase exchanges. We find evidence of a smooth intra-daily seasonality pattern, and an abnormal trade- and...