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Do High‐Frequency Data Improve High‐Dimensional Portfolio Allocations?

Citations

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Cited by:

  1. Hautsch, Nikolaus & Voigt, Stefan, 2019. "Large-scale portfolio allocation under transaction costs and model uncertainty," Journal of Econometrics, Elsevier, vol. 212(1), pages 221-240.
  2. Bauwens, Luc & Braione, Manuela & Storti, Giuseppe, 2017. "A dynamic component model for forecasting high-dimensional realized covariance matrices," Econometrics and Statistics, Elsevier, vol. 1(C), pages 40-61.
  3. Golosnoy, Vasyl & Gribisch, Bastian & Seifert, Miriam Isabel, 2019. "Exponential smoothing of realized portfolio weights," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 222-237.
  4. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-Scale Portfolio Allocation Under Transaction Costs and Model Uncertainty: Adaptive Mixing of High- and Low-Frequency Information," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168222, Verein für Socialpolitik / German Economic Association.
  5. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2018. "Modeling and forecasting (un)reliable realized covariances for more reliable financial decisions," Journal of Econometrics, Elsevier, vol. 207(1), pages 71-91.
  6. Llorens-Terrazas, Jordi & Brownlees, Christian, 2023. "Projected Dynamic Conditional Correlations," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1761-1776.
  7. Li, Yifan & Nolte, Ingmar & Vasios, Michalis & Voev, Valeri & Xu, Qi, 2022. "Weighted Least Squares Realized Covariation Estimation," Journal of Banking & Finance, Elsevier, vol. 137(C).
  8. Lai, Yu-Sheng, 2025. "Trading-hour and nontrading-hour volatility in crude oil and U.S. dollar markets and its implications for portfolio optimization," Journal of Commodity Markets, Elsevier, vol. 38(C).
  9. Taras Bodnar & Nestor Parolya & Erik Thorsen, 2021. "Dynamic Shrinkage Estimation of the High-Dimensional Minimum-Variance Portfolio," Papers 2106.02131, arXiv.org, revised Nov 2021.
  10. Bodnar, Taras & Lindholm, Mathias & Niklasson, Vilhelm & Thorsén, Erik, 2022. "Bayesian portfolio selection using VaR and CVaR," Applied Mathematics and Computation, Elsevier, vol. 427(C).
  11. Christian Brownlees & Eulàlia Nualart & Yucheng Sun, 2018. "Realized networks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 986-1006, November.
  12. Arumugam, Devika, 2023. "Algorithmic trading: Intraday profitability and trading behavior," Economic Modelling, Elsevier, vol. 128(C).
  13. Pirino, Davide & Pollastri, Alessandro & Trapin, Luca, 2025. "Testing liquidity: A statistical theory based on asset staleness," Econometrics and Statistics, Elsevier, vol. 35(C), pages 23-40.
  14. Billio, Monica & Caporin, Massimiliano & Panzica, Roberto & Pelizzon, Loriana, 2023. "The impact of network connectivity on factor exposures, asset pricing, and portfolio diversification," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 196-223.
  15. Cui, Tianxiang & Du, Nanjiang & Yang, Xiaoying & Ding, Shusheng, 2024. "Multi-period portfolio optimization using a deep reinforcement learning hyper-heuristic approach," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
  16. Taras Bodnar & Mathias Lindholm & Vilhelm Niklasson & Erik Thors'en, 2020. "Bayesian Quantile-Based Portfolio Selection," Papers 2012.01819, arXiv.org.
  17. Luo, Jiawen & Chen, Langnan, 2020. "Realized volatility forecast with the Bayesian random compressed multivariate HAR model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 781-799.
  18. Qu, Hui & Zhang, Yi, 2022. "Asymmetric multivariate HAR models for realized covariance matrix: A study based on volatility timing strategies," Economic Modelling, Elsevier, vol. 106(C).
  19. Laura Capera Romero & Anne Opschoor, 2025. "Revisiting EWMA in High-Frequency Portfolio Optimization: A Comparative Assessment," Tinbergen Institute Discussion Papers 25-041/III, Tinbergen Institute.
  20. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2021. "A non-elliptical orthogonal GARCH model for portfolio selection under transaction costs," Journal of Banking & Finance, Elsevier, vol. 125(C).
  21. Golosnoy, Vasyl & Gribisch, Bastian, 2022. "Modeling and forecasting realized portfolio weights," Journal of Banking & Finance, Elsevier, vol. 138(C).
  22. Golosnoy, Vasyl & Schmid, Wolfgang & Seifert, Miriam Isabel & Lazariv, Taras, 2020. "Statistical inferences for realized portfolio weights," Econometrics and Statistics, Elsevier, vol. 14(C), pages 49-62.
  23. Yu-Sheng Lai, 2018. "Dynamic hedging with futures: a copula-based GARCH model with high-frequency data," Review of Derivatives Research, Springer, vol. 21(3), pages 307-329, October.
  24. Jiawen Luo & Langnan Chen, 2019. "Multivariate realized volatility forecasts of agricultural commodity futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(12), pages 1565-1586, December.
  25. Laurent Callot & Anders B. Kock & Marcelo C. Medeiros, 2014. "Estimation and Forecasting of Large Realized Covariance Matrices and Portfolio Choice," Tinbergen Institute Discussion Papers 14-147/III, Tinbergen Institute.
  26. Xiangyu Cui & Xuan Zhang, 2021. "Index tracking strategy based on mixed-frequency financial data," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-15, April.
  27. Timo Dimitriadis & Yannick Hoga, 2022. "Dynamic CoVaR Modeling and Estimation," Papers 2206.14275, arXiv.org, revised Jan 2025.
  28. Lai, Yu-Sheng, 2023. "Economic evaluation of dynamic hedging strategies using high-frequency data," Finance Research Letters, Elsevier, vol. 57(C).
  29. Alfelt, Gustav & Bodnar, Taras & Javed, Farrukh & Tyrcha, Joanna, 2020. "Singular conditional autoregressive Wishart model for realized covariance matrices," Working Papers 2021:1, Örebro University, School of Business.
  30. Wang, Jiazhen & Jiang, Yuexiang & Zhu, Yanjian & Yu, Jing, 2020. "Prediction of volatility based on realized-GARCH-kernel-type models: Evidence from China and the U.S," Economic Modelling, Elsevier, vol. 91(C), pages 428-444.
  31. Weigand, Roland, 2014. "Matrix Box-Cox Models for Multivariate Realized Volatility," University of Regensburg Working Papers in Business, Economics and Management Information Systems 478, University of Regensburg, Department of Economics.
  32. Laura Capera Romero & Anne Opschoor, 2024. "Realized Variances vs. Correlations: Unlocking the Gains in Multivariate Volatility Forecasting," Tinbergen Institute Discussion Papers 24-059/III, Tinbergen Institute.
  33. Vladim'ir Hol'y & Petra Tomanov'a, 2020. "Streaming Approach to Quadratic Covariation Estimation Using Financial Ultra-High-Frequency Data," Papers 2003.13062, arXiv.org, revised Dec 2021.
  34. Andrea BUCCI, 2017. "Forecasting Realized Volatility A Review," Journal of Advanced Studies in Finance, ASERS Publishing, vol. 8(2), pages 94-138.
  35. Oh, Dong Hwan & Patton, Andrew J., 2016. "High-dimensional copula-based distributions with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 349-366.
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