Modeling tick-by-tick realized correlations
Journal
Computational Statistics and Data Analysis
ISSN
0167-9473
ISSN-Digital
1872-7352
Type
journal article
Date Issued
2010-11-01
Author(s)
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
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
Language
English
Keywords
High frequency data
Realized correlation
Stock-bond correlation
Tree-structured models
HAR
Regimes.
HSG Classification
contribution to scientific community
Refereed
Yes
Publisher
Elsevier Science
Publisher place
Amsterdam
Volume
54
Number
11
Start page
2372
End page
2382
Pages
11
Subject(s)
Eprints ID
57803