In this paper we provide an overview of the growth model in China and its prospects, taking a medium-run to long-run perspective. Our main conclusions are as follows. First, the still prevailing producer-biased model of managed capitalism in China tends to engender, as an inherent byproduct,...

Building on the literature on regularization and dimension reduction methods, we have developed a quarterly forecasting model for euro area GDP. This method consists in bridging quarterly national accounts data using factors extracted from a large panel of monthly and quarterly series including...

Forecasting-volatility models typically rely on either daily or high frequency (HF) data and the choice between these two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer of many limitations. HF data feature microstructure problem,...

Call centers' managers are interested in obtaining accurate forecasts of call arrivals because these are a key input in staffing and scheduling decisions. Therefore their ability to achieve an optimal balance between service quality and operating costs ultimately hinges on forecast accuracy. We...

For forecasting volatility of futures returns, the paper proposes an indirect method based on the relationship between futures and the underlying asset for the returns and time-varying volatility. For volatility forecasting, the paper considers the stochastic volatility model with asymmetry and...

In this paper, I apply univariate and vector autoregressive (VAR) models to forecast inflation in Vietnam. To investigate the forecasting performance of the models, two naive benchmark models (one is a variant of a random walk and the other is an autoregressive model) are first built based on...

There has been increased interest in the use of "big data" when it comes to forecasting macroeconomic time series such as private consumption or unemployment. However, applications on forecasting GDP are rather rare. In this paper we incorporate Google search data into a Bridge Equation Model, a...

In this paper, the authors investigate the statistical properties of some cryptocurrencies by using three layers of analysis: alpha-stable distributions, Metcalfe's law and the bubble behaviour through the LPPL modelling. The results show, in the medium to long-run, the validity of Metcalfe's...

We introduce SRISK to measure the systemic risk contribution of a financial firm. SRISK measures the capital shortfall of a firm conditional on a severe market decline, and is a function of its size, leverage and risk. We use the measure to study top US financial institutions in the recent...

There are competing arguments about the likely effects of Sovereign Bond-Backed Securitisation on the liquidity of sovereign bond markets. By analysing hedging and diversification opportunities, this paper shows that positive liquidity spillovers would dominate or at least constrain the extent...