Realized volatility of financial time series generally shows a slow–moving average level from the early 2000s to recent times, with alternating periods of turmoil and quiet. Modeling such a pattern has been variously tackled in the literature with solutions spanning from long–memory, Markov...

The Volume Weighted Average Price (VWAP) mixes volumes and prices at intra-daily intervals and is a benchmark measure frequently used to evaluate a trader's performance. Under suitable assumptions, splitting a daily order according to ex-ante volume predictions is a good strategy to replicate...

Realized volatilities measured on several assets exhibit a common secular trend and some idiosyncratic pattern. We accommodate such an empirical regularity extending the class of Multiplicative Error Models (MEMs) to a model where the common trend is estimated nonparametrically while the...

Empirical evidence shows that the dynamics of high frequency–based measures of volatility exhibit persistence and occasional abrupt changes in the average level. By looking at volatility measures for major indices, we notice similar patterns (including jumps at about the same time), with...

Persistence and occasional abrupt changes in the average level characterize the dynamics of high frequency based measures of volatility. Since the beginning of the 2000s, this pattern can be attributed to the dot com bubble, the quiet period of expansion of credit between 2003 and 2006 and then...

Financial time series analysis has focused on data related to market trading activity. Next to the modeling of the conditional variance of returns within the GARCH family of models, recent attention has been devoted to other variables: first, and foremost, volatility measured on the basis of...

When observed over a large panel, measures of risk (such as realized volatilities) usually exhibit a secular trend around which individual risks cluster. In this article we propose a vector Multiplicative Error Model achieving a decomposition of each risk measure into a common systematic and an...

The explosion of algorithmic trading has been one of the most prominent recent trends in the financial industry. Algorithmic trading consists of automated trading strategies that attempt to minimize transaction costs by optimally placing orders. The key ingredient of many of these strategies are...

Volatility forecasting is one of the main issues in the financial econometrics literature. Volatility measures may be derived from statistical models for conditional variance, or from option prices. In recent times, indices have been suggested which summarize the implied volatility of widely...

The literature on Markov switching models is increasing and producing interesting results both at theoretical and applied levels. Most often the number of regimes, i.e., of data generating processes, is considered known; this strong hypothesis is adopted to somewhat bypass the nuisance parameter...