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Large volatility matrix inference via combining low-frequency and high-frequency approaches. (2011). Zou, Jian ; Wang, Yahzen ; Yao, Qiwei ; Tao, Minjing .
In: LSE Research Online Documents on Economics.
RePEc:ehl:lserod:39321.

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  2. Discovering the drivers of stock market volatility in a data-rich world. (2023). Ryu, Doojin ; Cho, Hoon ; Chun, Dohyun.
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  3. Dynamic factor copula models with estimated cluster assignments. (2023). Patton, Andrew J ; Oh, Dong Hwan.
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  4. Identifying latent factors based on high-frequency data. (2023). Zhang, Chuanhai ; Xu, Wen ; Sun, Yucheng.
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  5. Dimension Reduction for High Dimensional Vector Autoregressive Models. (2022). Hecq, Alain ; Cubadda, Gianluca .
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  6. Dimension Reduction for High Dimensional Vector Autoregressive Models. (2022). Hecq, Alain ; Cubadda, Gianluca.
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  7. Unified discrete-time factor stochastic volatility and continuous-time Itô models for combining inference based on low-frequency and high-frequency. (2022). Wang, Yazhen ; Song, Xinyu ; Kim, Donggyu.
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  10. Does the Choice of Realized Covariance Measures Empirically Matter? A Bayesian Density Prediction Approach. (2021). Yang, Qiao ; Liu, Jia ; Jin, Xin.
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  11. Dynamic Factor Copula Models with Estimated Cluster Assignments. (2021). Patton, Andrew ; Oh, Dong Hwan.
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  13. Estimation of Common Factors for Microstructure Noise and Efficient Price in a High-frequency Dual Factor Model. (2021). Linton, O ; Chen, J ; Li, Y-N., .
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  14. Exponential GARCH-Ito Volatility Models. (2021). Kim, Donggyu.
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  15. Factor state–space models for high-dimensional realized covariance matrices of asset returns. (2020). Gribisch, Bastian ; Liesenfeld, Roman ; Hartkopf, Jan Patrick.
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  16. High-dimensional minimum variance portfolio estimation based on high-frequency data. (2020). Zheng, Xinghua ; Li, Yingying ; Hu, Jianchang ; Cai, Tony T.
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  17. Forecasting large covariance matrix with high-frequency data using factor approach for the correlation matrix. (2020). Tse, Yiu-Kuen ; Dong, Yingjie.
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  18. Dimension Reduction for High Dimensional Vector Autoregressive Models. (2020). Hecq, Alain ; Cubadda, Gianluca.
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  19. Unified Discrete-Time Factor Stochastic Volatility and Continuous-Time Ito Models for Combining Inference Based on Low-Frequency and High-Frequency. (2020). Song, Xinyu ; Kim, Donggyu ; Wang, Yazhen.
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  20. A dynamic conditional approach to portfolio weights forecasting. (2020). Palandri, Alessandro ; Gallo, Giampiero M ; Cipollini, Fabrizio.
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  21. The Impact of Jumps and Leverage in Forecasting the Co-Volatility of Oil and Gold Futures. (2019). McAleer, Michael ; GUPTA, RANGAN ; Asai, Manabu.
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  22. The Impact of Jumps and Leverage in Forecasting the Co-Volatility of Oil and Gold Futures. (2019). McAleer, Michael ; GUPTA, RANGAN ; Asai, Manabu.
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  23. The Impact of Jumps and Leverage in Forecasting the Co-Volatility of Oil and Gold Futures. (2019). McAleer, Michael ; GUPTA, RANGAN ; Asai, Manabu.
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  24. A dynamic factor model with stylized facts to forecast volatility for an optimal portfolio. (2019). Belkacem, Lotfi ; Boubaker, Heni ; Karmous, Aida.
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  25. Knowing factors or factor loadings, or neither? Evaluating estimators of large covariance matrices with noisy and asynchronous data. (2019). Dai, Chaoxing ; Xiu, Dacheng ; Lu, Kun.
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  26. On a spiked model for large volatility matrix estimation from noisy high-frequency data. (2019). Shen, Keren ; Li, Wai Keung ; Yao, Jianfeng.
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  27. Large Volatility Matrix Prediction with High-Frequency Data. (2019). Song, Xinyu.
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  28. Time series models for realized covariance matrices based on the matrix-F distribution. (2019). Zhu, Ke ; Li, Wai Keung ; Jiang, Feiyu ; Zhou, Jiayuan.
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  29. Bayesian Parametric and Semiparametric Factor Models for Large Realized Covariance Matrices. (2018). Maheu, John ; Yang, Qiao ; Jin, Xin.
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  30. A nonparametric eigenvalue-regularized integrated covariance matrix estimator for asset return data. (2018). Feng, Phoenix ; Lam, Clifford.
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  31. A nonparametric eigenvalue-regularized integrated covariance matrix estimator for asset return data. (2018). Lam, Clifford ; Feng, Phoenix.
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  32. Two-stage stationary bootstrapping for bivariate average realized volatility matrix under market microstructure noise and asynchronicity. (2018). Hwang, Eunju ; Shin, Dong Wan.
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  33. High-dimensional covariance forecasting based on principal component analysis of high-frequency data. (2018). Jian, Zhi Hong ; Zhu, Zhican ; Deng, Pingjun.
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  34. The Generalized Conditional Autoregressive Wishart Model for Multivariate Realized Volatility. (2017). , Philip ; Ng, F C ; Li, W K.
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  35. Bayesian Parametric and Semiparametric Factor Models for Large Realized Covariance Matrices. (2017). Maheu, John ; Yang, Qiao ; Jin, Xin.
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  36. Using principal component analysis to estimate a high dimensional factor model with high-frequency data. (2017). Ait-Sahalia, Yacine ; Xiu, Dacheng.
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  37. Modelling multivariate volatilities via latent common factors. (2016). Yao, Qiwei ; Li, Kunpeng ; Gao, Jing.
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  38. Asymptotic theory for large volatility matrix estimation based on high-frequency financial data. (2016). Zou, Jian ; Kim, Donggyu ; Wang, Yazhen.
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  39. Unified discrete-time and continuous-time models and statistical inferences for merged low-frequency and high-frequency financial data. (2016). Kim, Donggyu ; Wang, Yazhen.
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  40. Statistical Inference for Unified Garch–Itô Models with High-Frequency Financial Data. (2016). Kim, Donggyu.
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  41. Forecasting co-volatilities via factor models with asymmetry and long memory in realized covariance. (2015). McAleer, Michael ; Asai, Manabu.
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  42. Leverage and feedback effects on multifactor Wishart stochastic volatility for option pricing. (2015). McAleer, Michael ; Asai, Manabu.
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  44. Leverage and Feedback Effects on Multifactor Wishart Stochastic Volatility for Option Pricing. (2013). McAleer, Michael ; Asai, Manabu.
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  45. Leverage and Feedback Effects on Multifactor Wishart Stochastic Volatility for Option Pricing. (2013). McAleer, Michael ; Asai, Manabu.
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  47. Estimation in the presence of many nuisance parameters: Composite likelihood and plug-in likelihood. (2013). Wu, Billy ; Zhu, Shiwu ; Yao, Qiwei.
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  21. 09/11 on the USD/EUR foreign exchange market. (2006). Mende, Alexander.
    In: Applied Financial Economics.
    RePEc:taf:apfiec:v:16:y:2006:i:3:p:213-222.

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  22. Predicting volatility: getting the most out of return data sampled at different frequencies. (2006). Valkanov, Rossen ; Santa-Clara, Pedro ; Ghysels, Eric.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:131:y:2006:i:1-2:p:59-95.

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  23. Realized Variance and Market Microstructure Noise. (2006). Lunde, Asger ; Hansen, Peter.
    In: Journal of Business & Economic Statistics.
    RePEc:bes:jnlbes:v:24:y:2006:p:127-161.

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  24. Estimating Integrated Volatility Using Absolute High-Frequency Returns. (2006). Ysusi, Carla .
    In: Working Papers.
    RePEc:bdm:wpaper:2006-13.

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  25. Detecting Jumps in High-Frequency Financial Series Using Multipower Variation. (2006). Ysusi, Carla .
    In: Working Papers.
    RePEc:bdm:wpaper:2006-10.

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  26. Practical volatility and correlation modeling for financial market risk management. (2005). Diebold, Francis ; Christoffersen, Peter ; Bollerslev, Tim ; Andersen, Torben.
    In: CFS Working Paper Series.
    RePEc:zbw:cfswop:200502.

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  27. Finite Sample Accuracy of Integrated Volatility Estimators. (2005). Nielsen, Morten ; Frederiksen, Per Houmann.
    In: Working Papers.
    RePEc:qed:wpaper:1225.

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  28. Practical Volatility and Correlation Modeling for Financial Market Risk Management. (2005). Diebold, Francis ; Christoffersen, Peter ; Bollerslev, Tim ; Andersen, Torben.
    In: PIER Working Paper Archive.
    RePEc:pen:papers:05-007.

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  29. Variation, jumps, market frictions and high frequency data in financial econometrics. (2005). Shephard, Neil ; Barndorff-Nielsen, Ole.
    In: Economics Series Working Papers.
    RePEc:oxf:wpaper:240.

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  30. Variation, jumps, market frictions and high frequency data in financial econometrics. (2005). Shephard, Neil ; Barndorff-Nielsen, Ole.
    In: Economics Papers.
    RePEc:nuf:econwp:0516.

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  31. Limit theorems for bipower variation in financial econometrics. (2005). Shephard, Neil ; Barndorff-Nielsen, Ole ; Jacod, Jean ; Graversen, Sven Erik.
    In: Economics Papers.
    RePEc:nuf:econwp:0506.

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  32. Estimating quadratic variation when quoted prices jump by a constant increment. (2005). Large, Jeremy.
    In: Economics Papers.
    RePEc:nuf:econwp:0505.

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  33. Multifrequency News and Stock Returns. (2005). Fisher, Adlai ; Calvet, Laurent.
    In: NBER Working Papers.
    RePEc:nbr:nberwo:11441.

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  34. Practical Volatility and Correlation Modeling for Financial Market Risk Management. (2005). Diebold, Francis ; Christoffersen, Peter ; Bollerslev, Tim ; Andersen, Torben.
    In: NBER Working Papers.
    RePEc:nbr:nberwo:11069.

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  35. 09/11 on the USD/EUR Foreign Exchange Market. (2005). Mende, Alexander.
    In: Hannover Economic Papers (HEP).
    RePEc:han:dpaper:dp-312.

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  36. Forecasting the Volatility of Australian Stock Returns: Do Common Factors Help?. (2005). Vahid, Farshid ; Anderson, Heather.
    In: ANU Working Papers in Economics and Econometrics.
    RePEc:acb:cbeeco:2005-451.

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  37. Détection non paramétrique de sauts dans la volatilité des marchés financiers. (2004). Perron, Benoit.
    In: L'Actualité Economique.
    RePEc:ris:actuec:v:80:y:2004:i:2:p:229-251.

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  38. Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies. (2004). Valkanov, Rossen ; Santa-Clara, Pedro ; Ghysels, Eric.
    In: NBER Working Papers.
    RePEc:nbr:nberwo:10914.

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  39. The Cross-Section of Volatility and Expected Returns. (2004). zhang, xiaoyan ; Xing, Yuhang ; Hodrick, Robert.
    In: NBER Working Papers.
    RePEc:nbr:nberwo:10852.

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  40. Local and spillover shocks in implied market volatility: evidence for the U.S. and Germany. (2004). Wagner, Niklas ; Szimayer, Alexander.
    In: Research in International Business and Finance.
    RePEc:eee:riibaf:v:18:y:2004:i:3:p:237-251.

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  41. Testing and Modelling Market Microstructure Effects with an Application to the Dow Jones Industrial Average. (2004). Awartani, Basel ; Corradi, Valentina.
    In: Econometric Society 2004 North American Summer Meetings.
    RePEc:ecm:nasm04:487.

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  42. Testing and Modelling Market Microstructure Effects with an Application to the Dow Jones Industrial Average. (2004). Awartani, Basel ; Distaso, Walter ; Corradi, Valentina.
    In: Econometric Society 2004 Australasian Meetings.
    RePEc:ecm:ausm04:273.

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  43. Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies. (2004). Valkanov, Rossen ; Santa-Clara, Pedro ; Ghysels, Eric.
    In: CIRANO Working Papers.
    RePEc:cir:cirwor:2004s-19.

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  44. Power and bipower variation with stochastic volatility and jumps. (2003). Shephard, Neil ; Barndorff-Nielsen, Ole E..
    In: Economics Series Working Papers.
    RePEc:oxf:wpaper:2003-w18.

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  45. Econometrics of testing for jumps in financial economics using bipower variation. (2003). Shephard, Neil ; Barndorff-Nielsen, Ole.
    In: Economics Papers.
    RePEc:nuf:econwp:0321.

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