Taking advantage of a trades-and-quotes high-frequency database, we document the main stylized facts and dynamic properties of spot precious metals, i.e. gold, silver, palladium, and platinum. We analyze the behaviors of spot prices, returns, volume, and selected liquidity measures. We find...

The appropriate design of monetary policy in integrated financial markets is one of the most challenging areas for central banks. One hot topic is whether the rise in liquidity in recent years has contributed to the formation of price bubbles in asset markets. If strong linkages exist, the...

The appropriate design of monetary policy in integrated financial markets is one of the most challenging areas for central banks. One hot topic is whether the rise in liquidity in recent years has contributed to the formation of price bubbles in asset markets. If strong linkages exist, the...

In this paper we propose a new multivariate GARCH model with time-varying conditional correlation structure. The approach adopted here is based on the decomposition of the covariances into correlations and standard deviations. The time-varying conditional correlations change smoothly between two...

Given the process {X(t), t in T}, the definition of self-affinity is reformulated in terms of diameter of the space of the rescaled pdf's of X(t). Two necessary conditions are deduced which contribute to discriminate uniscaling processes. Furthermore, by properly choosing the distance, the...

We assess the predictive accuracy of a large number of multivariate volatility models in terms of pricing options on the Dow Jones Industrial Average. We measure the value of model sophistication in terms of dollar losses by considering a set 248 multivariate models that differ in their...

We explore properties of asymmetric generalized autoregressive conditional heteroscedasticity (GARCH) models in the threshold GARCH family and propose a more general Spline-GTARCH model, which captures high-frequency return volatility, low-frequency macroeconomic volatility as well as an...

Asset price bubbles have fascinated economists for decades. In consequence, the literature on bubbles and their detection is abundant, with many researchers taking very opposite positions on the topic, however. This survey gives a structured overview of the two branches of research that have...

We examine return predictability with machine learning in 46 international stock markets. We calculate 148 stock characteristics and use them to feed a repertoire of different models. The algorithms extract predictability mainly from simple, yet popular, factor types—such as momentum,...