Cryptocurrencies, especially Bitcoin (BTC), which comprise a new revolutionary asset class, have drawn extraordinary worldwide attention. The characteristics of the cryptocurrency/ BTC include a high level of speculation, extreme volatility and price discontinuity. In this paper, we propose a...

Inflation expectation (IE) is often considered to be an important determinant of actual inflation in modern economic theory, we are interested in investigating the main risk factors that determine its dynamics. We first apply a joint arbitrage-free term structure model across different European...

Modelling dynamic conditional heteroscedasticity is the daily routine in time series econometrics. We propose a weighted conditional moment estimation to potentially improve the efficiency of the QMLE (quasi maximum likelihood estimation). The weights of conditional moments are selected based on...

This paper proposes a dynamic spatial autoregressive quantile model. Using predetermined network information, we study dynamic tail event driven risk using a system of conditional quantile equations. Extending Zhu et. al. (2019), we allow the contemporaneous dependency of nodal responses by...

We propose a novel approach to calibrate the conditional value-at-risk (CoVaR) of financial institutions based on neural network quantile regression. Building on the estimation results, we model systemic risk spillover effects in a network context across banks by considering the marginal effects...

Estimating natural rate of unemployment (NAIRU) is important for understanding the joint dynamics of unemployment, inflation, and inflation expectation. However, existing literature falls short of endogenizing inflation expectation together with NAIRU in a model consistent way. We estimate a...

It is a challenging task to understand the complex dependency structures in an ultra-high dimensional network, especially when one concentrates on the tail dependency. To tackle this problem, we consider a network quantile autoregression model (NQAR) to characterize the dynamic quantile behavior...

In the present paper we study the dynamics of penalization parameter λ of the least absolute shrinkage and selection operator (Lasso) method proposed by Tibshirani (1996) and extended into quantile regression context by Li and Zhu (2008). The dynamic behaviour of the parameter λ can be...