Properly estimating correlations and understanding how they change under different economic conditions plays a key role in asset pricing models, risk management, and many econometric models. In this paper we introduce a robust framework to identify a meaningful correlation relationship, address...

We investigate the historical volatility of the 100 most capitalized stocks traded in US equity markets. An empirical probability density function (pdf) of volatility is obtained and compared with the theoretical predictions of a lognormal model and of the Hull and White model. The lognormal...

It is widely believed that fluctuations in transaction volume, as reflected in the number of transactions and to a lesser extent their size, are the main cause of clustered volatility. Under this view bursts of rapid or slow price diffusion reflect bursts of frequent or less frequent trading,...

We investigate the time series of the degree of minimum spanning trees (MSTs) obtained by using a correlation-based clustering procedure which starts from (i) asset return and (ii) volatility time series. The MST is obtained at different times by computing correlation among time series over a...

Instabilities in the price dynamics of a large number of financial assets are a clear sign of systemic events. By investigating a set of 20 high cap stocks traded at the Italian Stock Exchange, we find that there is a large number of high frequency cojumps. We show that the dynamics of these...

Market liquidity is a latent and dynamic variable. Building on Cont et al. (2014), we propose a dynamical price impact model at high-frequency, in which price impact is a product of daily, diurnal, and autoregressive stochastic intraday com- ponents. The model is estimated using a Kalman filter...