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Modeling tick-by-tick realized correlations

Francesco Audrino & Fulvio Corsi

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abstract A tree-structured heterogeneous autoregressive (tree-HAR) process is
proposed as a simple and parsimonious model for the estimation and prediction of tick-by-tick realized correlations. The model can account for different time and other relevant predictors' dependentregime shifts in the conditional mean dynamics of the realized correlation series. Testing the model on S&P 500 Futures and 30-year Treasury Bond Futures realized correlations, empirical evidence that the tree-HAR model reaches a good compromise between simplicity and flexibility is provided. The model yields accurate single- and multi-step out-of-sample forecasts. Such forecasts are also better than those obtained from other standard approaches, in particular when the final goal is multi-period forecasting
   
type journal paper
   
keywords High frequency data; Realized correlation;
Stock-bond correlation; Tree-structured models; HAR; Regimes.
   
language English
kind of paper journal article
date of appearance 1-11-2010
journal Computational Statistics and Data Analysis
publisher Elsevier Science (Amsterdam)
ISSN 0167-9473
ISSN (online) 1872-7352
DOI 10.1016/j.csda.2009.09.033
volume of journal 54
number of issue 11
page(s) 2372-2382
review double-blind review
   
citation Audrino, F., & Corsi, F. (2010). Modeling tick-by-tick realized correlations. Computational Statistics and Data Analysis, 54(11), 2372-2382, DOI:10.1016/j.csda.2009.09.033.