Forecasting realized correlations: a MIDAS approach
作者： Alexander Kostrov , Anastasija Tetereva
DOI: 10.2139/SSRN.3346492
关键词:
摘要: Mixed data sampling (MIDAS) regression has received much attention in relation to modeling financial time series due its flexibility. Previous work mainly focused on forecasting of realized volatilities and rarely been used predict correlations. This paper considers a MIDAS approach forecast correlation matrices. A model is estimated via nonlinear least squares (NLS) using an analytical gradient-based optimization. Based the confidence set (MCS) procedure we discover that introduced superior compared established heterogeneous autoregressive (HAR) terms out-of-sample accuracy. preeminence flexible data-driven origin model. The latter results higher economic value with regard portfolio management applications. improvement considerable for longer horizons both calm times during periods market turbulence.
unisg.ch
sci-hub.se 参考文章(48)
KAUNG PYAE, Maintaining Traction Factor Value Of Belt Conveyor With Two Engine Drive #N#Third International Conference on Advances in Mechanical and Automation Engineering - MAE 2015#N#. ,(2015) , 10.15224/978-1-63248-080-4-73
Takalani Eric Mudzanani, Beyond storing old stuff: analysing the socio-economic value of museums On the Horizon. ,vol. 23, pp. 331- 338 ,(2015) , 10.1108/OTH-07-2015-0032
Yacine Aït-Sahalia, Jianqing Fan, Dacheng Xiu, High-Frequency Covariance Estimates With Noisy and Asynchronous Financial Data Journal of the American Statistical Association. ,vol. 105, pp. 1504- 1517 ,(2010) , 10.1198/JASA.2010.TM10163
Shirley Almon, The Distributed Lag Between Capital Appropriations and Expenditures Econometrica. ,vol. 33, pp. 178- ,(1965) , 10.2307/1911894
Alessandra Amendola, Giuseppe Storti, Model Uncertainty and Forecast Combination in High‐Dimensional Multivariate Volatility Prediction Journal of Forecasting. ,vol. 34, pp. 83- 91 ,(2015) , 10.1002/FOR.2322
Stanislav Anatolyev, Nikita Kobotaev, Modeling and forecasting realized covariance matrices with accounting for leverage Econometric Reviews. ,vol. 37, pp. 114- 139 ,(2018) , 10.1080/07474938.2015.1035165
Torben Andersen, Tim Bollerslev, Francis Diebold, Heiko Ebens, The Distribution of Stock Return Volatility Social Science Research Network. ,(2000) , 10.3386/W7933
Torben G. Andersen, Tim Bollerslev, Francis X. Diebold, Paul Labys, MODELING AND FORECASTING REALIZED VOLATILITY Econometrica. ,vol. 71, pp. 579- 625 ,(2003) , 10.1111/1468-0262.00418
Elena Andreou, Eric Ghysels, Andros Kourtellos, Regression models with mixed sampling frequencies Journal of Econometrics. ,vol. 158, pp. 246- 261 ,(2010) , 10.1016/J.JECONOM.2010.01.004
Francesco Audrino, Forecasting correlations during the late-2000s financial crisis Computational Statistics & Data Analysis. ,vol. 76, pp. 43- 60 ,(2014) , 10.1016/J.CSDA.2013.06.002