A method to generate synthetic datasets with controlled covariance structure is introduced and demonstrated on socio-spatial systems and financial time-series.
Levels of complexity in financial markets
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
abstract
We consider different levels of complexity which are observed in the empirical investigation of financial time series. We discuss recent empirical and theoretical work showing that statistical properties of financial time series are rather complex under several ways. Specifically, they are complex with respect to their (i) temporal and (ii) ensemble properties. Moreover, the ensemble return properties show a behavior which is specific to the nature of the trading day reflecting if it is a normal or an extreme trading day.
fields
stat.AP 1years
2019 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Second-order Control of Complex Systems with Correlated Synthetic Data
A method to generate synthetic datasets with controlled covariance structure is introduced and demonstrated on socio-spatial systems and financial time-series.