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Microstructure noise in the continuous case: The pre-averaging approach. (2009). Podolskij, Mark ; Jacod, Jean ; Li, Yingying ; Mykland, Per A. ; Vetter, Mathias .
In: Stochastic Processes and their Applications.
RePEc:eee:spapps:v:119:y:2009:i:7:p:2249-2276.

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  1. Realized volatility, price informativeness, and tick size: A market microstructure approach. (2024). Yamamoto, Ryuichi ; Xiao, Xijuan.
    In: International Review of Economics & Finance.
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  2. Intraday variation in cross-sectional stock comovement and impact of index-based strategies. (2024). Shen, Yiwen ; Shi, Meiqi.
    In: Journal of Financial Markets.
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  3. Estimation of Large Dynamic Covariance Matrices: A Selective Review. (2024). Li, Degui.
    In: Econometrics and Statistics.
    RePEc:eee:ecosta:v:29:y:2024:i:c:p:16-30.

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  4. High frequency principal component analysis based on correlation matrix that is robust to jumps, microstructure noise and asynchronous observation times. (2024). Chen, Dachuan.
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  5. Nonparametric estimation for high-frequency data incorporating trading information. (2024). Wang, Jiandong ; Hu, Jie ; Cui, Wenhao.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:240:y:2024:i:1:s0304407624000368.

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  6. Realized regression with asynchronous and noisy high frequency and high dimensional data. (2024). Zhang, Lan ; Mykland, Per A ; Chen, Dachuan.
    In: Journal of Econometrics.
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  7. Optimal covariance matrix estimation for high-dimensional noise in high-frequency data. (2024). Tang, Cheng Yong ; Liu, Cheng ; Hu, Qiao ; Chang, Jinyuan.
    In: Journal of Econometrics.
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  8. Review of Statistical Approaches for Modeling High-Frequency Trading Data. (2023). Ravishanker, Nalini ; Basu, Sumanta ; Karpman, Kara ; Dutta, Chiranjit.
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  9. Streaming Approach to Quadratic Covariation Estimation Using Financial Ultra-High-Frequency Data. (2023). Tomanova, Petra ; Hol, Vladimir.
    In: Computational Economics.
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  10. The incremental information in the yield curve about future interest rate risk. (2023). Christensen, Bent Jesper ; Veliyev, Bezirgen ; Kjar, Mads Markvart.
    In: Journal of Banking & Finance.
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  11. Volatility analysis for the GARCH–Itô–Jumps model based on high-frequency and low-frequency financial data. (2023). Hao, Hong-Xia ; Lin, Jin-Guan ; Fu, Jin-Yu.
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  12. Discovering the drivers of stock market volatility in a data-rich world. (2023). Ryu, Doojin ; Cho, Hoon ; Chun, Dohyun.
    In: Journal of International Financial Markets, Institutions and Money.
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  13. The contribution of jump signs and activity to forecasting stock price volatility. (2023). Murphy, Anthony ; Izzeldin, Marwan ; Hizmeri, Rodrigo ; Bu, Ruijun ; Tsionas, Mike.
    In: Journal of Empirical Finance.
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  14. Volatility measurement with pockets of extreme return persistence. (2023). Todorov, Viktor ; Li, Yingying ; Andersen, Torben G ; Zhou, BO.
    In: Journal of Econometrics.
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  15. Adaptive robust large volatility matrix estimation based on high-frequency financial data. (2023). Fan, Jianqing ; Kim, Donggyu ; Shin, Minseok.
    In: Journal of Econometrics.
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  16. A GMM approach to estimate the roughness of stochastic volatility. (2023). Veliyev, Bezirgen ; Pakkanen, Mikko S ; Christensen, Kim ; Bolko, Anine E.
    In: Journal of Econometrics.
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  17. ETF Basket-Adjusted Covariance estimation. (2023). Vanduffel, Steven ; Boudt, Kris ; Sauri, Orimar ; Dragun, Kirill.
    In: Journal of Econometrics.
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  18. Modeling realized covariance measures with heterogeneous liquidity: A generalized matrix-variate Wishart state-space model. (2023). Hartkopf, Jan Patrick ; Gribisch, Bastian.
    In: Journal of Econometrics.
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  19. Distribution-free specification test for volatility function based on high-frequency data with microstructure noise. (2022). Zhang, Zhiyuan ; Tang, Yinfen ; Su, Tao.
    In: Metrika: International Journal for Theoretical and Applied Statistics.
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  20. Testing for Endogeneity of Irregular Sampling Schemes. (2022). Pirino, Davide ; Livieri, Giulia ; Kolokolov, Aleksey.
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  21. Inference on common intraday periodicity at high frequencies. (2022). Kong, Xin-Bing ; Wang, Guan-Jun ; Wu, Fan.
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  22. 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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  23. Design-free estimation of integrated covariance matrices for high-frequency data. (2022). Xia, Ningning ; Wang, Moming ; Liu, Cheng.
    In: Journal of Multivariate Analysis.
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  24. Stochastic leverage effect in high-frequency data: a Fourier based analysis. (2022). Sanfelici, Simona ; Curato, Imma Valentina.
    In: Econometrics and Statistics.
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  25. Correcting Intraday Periodicity Bias in Realized Volatility Measures. (2022). Kellermann, Janosch ; Golosnoy, Vasyl ; Dette, Holger.
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  26. Volatility of volatility: Estimation and tests based on noisy high frequency data with jumps. (2022). Zhang, Zhiyuan ; Liu, Guangying.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:229:y:2022:i:2:p:422-451.

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  27. The drift burst hypothesis. (2022). Reno, Roberto ; Oomen, Roel ; Christensen, Kim.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:227:y:2022:i:2:p:461-497.

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  28. Occupation density estimation for noisy high-frequency data. (2022). Bollerslev, Tim ; Li, Jia ; Zhang, Congshan.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:227:y:2022:i:1:p:189-211.

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  29. Nonparametric Estimation of Large Spot Volatility Matrices for High-Frequency Financial Data. (2022). Wang, H ; Linton, O ; Bu, R.
    In: Cambridge Working Papers in Economics.
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  30. State Heterogeneity Analysis of Financial Volatility using high?frequency Financial Data. (2022). Kim, Donggyu ; Chun, Dohyun.
    In: Journal of Time Series Analysis.
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  31. Asymptotic Normality for the Fourier spot volatility estimator in the presence of microstructure noise. (2022). Toscano, Giacomo ; Mariotti, Tommaso ; Mancino, Maria Elvira.
    In: Papers.
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  32. High-Frequency-Based Volatility Model with Network Structure. (2022). Wang, Junhui ; Li, Guodong ; Yuan, Huiling.
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  34. High-dimensional statistical learning techniques for time-varying limit order book networks. (2021). Schienle, Melanie ; Hardle, Wolfgang ; Chen, Shi.
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  35. Tests for jumps in yield spreads. (2021). Yao, Wenying ; Winkelmann, Lars.
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  36. Estimation for high-frequency data under parametric market microstructure noise. (2021). Potiron, Yoann ; Clinet, Simon.
    In: Annals of the Institute of Statistical Mathematics.
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  37. Quasi-likelihood analysis and Bayes-type estimators of an ergodic diffusion plus noise. (2021). Uchida, Masayuki ; Kaino, Yusuke ; Nakakita, Shogo H.
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  38. Beta-Adjusted Covariance Estimation. (2021). Vanduffel, Steven ; Sauri, Orimar ; Boudt, Kris ; Dragun, Kirill.
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  39. Measuring the Jump Risk Contribution under Market Microstructure Noise – Evidence from Chinese Stock Market. (2021). Zhao, Xujie ; Yu, Chao.
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  40. The Contribution of Jump Signs and Activity to Forecasting Stock Price Volatility. (2021). Izzeldin, Marwan ; Hizmeri, Rodrigo ; Bu, Ruijun ; Tsionas, Mike G ; Murphy, Anthony.
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  41. 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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  42. Estimation of high-dimensional integrated covariance matrix based on noisy high-frequency data with multiple observations. (2021). Xia, Ningning ; Wang, Moming.
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  45. FX market volatility modelling: Can we use low-frequency data?. (2021). Výrost, Tomáš ; Lyócsa, Štefan ; Vrost, Toma ; Plihal, Toma ; Lyocsa, Tefan.
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  46. Forecasting volatility using double shrinkage methods. (2021). Cheng, Mingmian ; Yang, Xiye ; Swanson, Norman R.
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  47. Volatility analysis with realized GARCH-Itô models. (2021). Wang, Yazhen ; Zhou, Yong ; Lu, Zhiping ; Cui, Xiangyu ; Yuan, Huiling ; Kim, Donggyu ; Song, Xinyu.
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  48. 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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  49. Robust Estimation of Integrated Volatility. (2021). Linton, O.
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  50. Effect of the U.S.--China Trade War on Stock Markets: A Financial Contagion Perspective. (2021). Kim, Donggyu ; Oh, Minseog.
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  51. Exponential GARCH-Ito Volatility Models. (2021). Kim, Donggyu.
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  52. The Role of Binance in Bitcoin Volatility Transmission. (2021). Kaeck, Andreas ; Heck, Daniel ; Alexander, Carol.
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  53. Overnight GARCH-It\^o Volatility Models. (2021). Wang, Yazhen ; Kim, Donggyu.
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  54. The incremental information in the yield curve about future interest rate risk. (2021). Veliyev, Bezirgen ; Kjar, Mads Markvart ; Christensen, Bent Jesper.
    In: CREATES Research Papers.
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  56. High-frequency trading during flash crashes: Walk of fame or hall of shame?. (2020). Reno, Roberto ; Pelizzon, Loriana ; Kolokolov, Aleksey ; Christensen, Kim ; Bellia, Mario.
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  57. Cojump anchoring. (2020). Yao, Wenying ; Winkelmann, Lars.
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  58. Volatility Regressions with Fat Tails. (2020). Meddahi, Nour ; Kim, Jihyun.
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  59. Hybrid estimation for ergodic diffusion processes based on noisy discrete observations. (2020). Uchida, Masayuki ; Nakakita, Shogo H ; Kaino, Yusuke.
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  60. Volatility Regressions with Fat Tails. (2020). Meddahi, Nour ; Kim, Ji Hyun.
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  61. Volatility transmission between oil prices and banks’ stock prices as a new source of instability: Lessons from the United States experience. (2020). Ehouman, Yao Axel.
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  62. Intraday price jumps, market liquidity, and the magnet effect of circuit breakers. (2020). Zhou, Jie ; Jian, Zhi Hong ; Wu, Shuai ; Zhu, Zhican.
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  63. Economic indicators and stock market volatility in an emerging economy. (2020). Ryu, Doojin ; Cho, Hoon ; Chun, Dohyun.
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  64. Volatility regressions with fat tails. (2020). Kim, Jihyun ; Meddahi, Nour.
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  65. Liquidity and volatility in the U.S. Treasury market. (2020). Fleming, Michael ; Engle, Robert ; Ghysels, Eric ; Nguyen, Giang.
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  66. Dependent microstructure noise and integrated volatility estimation from high-frequency data. (2020). Laeven, Roger ; Vellekoop, Michel H ; Li, Merrick Z.
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  67. 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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  68. Volatility transmission between oil prices and banks stock prices as a new source of instability: Lessons from the United States experience. (2020). Ehouman, Yao Axel.
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  69. Nonlinear and time-varying risk premia. (2020). Cai, Zongwu ; Mi, Xianhua ; Ma, Chaoqun.
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  70. Heteroscedasticity test of high-frequency data with jumps and microstructure noise. (2020). Liu, Zhi ; Zhang, Chuanhai.
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  71. Roughness in spot variance? A GMM approach for estimation of fractional log-normal stochastic volatility models using realized measures. (2020). Veliyev, Bezirgen ; Pakkanen, Mikko S ; Christensen, Kim ; Bolko, Anine E.
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  72. 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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  73. Streaming Perspective in Quadratic Covariation Estimation Using Financial Ultra-High-Frequency Data. (2020). Tomanov, Petra ; Hol, Vladim'Ir.
    In: Papers.
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  74. Forecasting Realized Volatility Matrix With Copula-Based Models. (2020). Tao, Minjing ; Wang, Wenjing.
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  75. Roughness in spot variance? A GMM approach for estimation of fractional log-normal stochastic volatility models using realized measures. (2020). Christensen, Kim ; Bolko, Anine E ; Veliyev, Bezirgen ; Pakkanen, Mikko S.
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  77. Laws of large numbers for Hayashi–Yoshida-type functionals. (2019). Vetter, Mathias ; Martin, Ole.
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  78. Estimating stochastic volatility: the rough side to equity returns. (2019). Haynes, Jonathan ; Grimm, Lukas ; Schmitt, Daniel.
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  79. Estimation of volatility in a high-frequency setting: a short review. (2019). Jacod, Jean.
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  80. Asymptotic properties of the realized skewness and related statistics. (2019). Liu, Zhi ; Koike, Yuta.
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  81. Factor High-Frequency-Based Volatility (HEAVY) Models. (2019). Xu, Wen ; Sheppard, Kevin.
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  82. Do High-frequency-based Measures Improve Conditional Covariance Forecasts?. (2019). Dumitrescu, Elena Ivona ; Banulescu-Radu, Denisa.
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  83. The Contribution of Jump Signs and Activity to Forecasting Stock Price Volatility. (2019). Tsionas, Mike ; Murphy, Anthony ; Izzeldin, Marwan ; Hizmeri, Rodrigo.
    In: Working Papers.
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  84. Empirical likelihood for high frequency data. (2019). Otsu, Taisuke ; Matsushita, Yukitoshi ; Camponovo, Lorenzo.
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  85. The signal and the noise volatilities. (2019). Chaker, Selma.
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  86. The realized empirical distribution function of stochastic variance with application to goodness-of-fit testing. (2019). Veliyev, Bezirgen ; Thyrsgaard, Martin ; Christensen, Kim.
    In: Journal of Econometrics.
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  87. High-dimensional multivariate realized volatility estimation. (2019). Bollerslev, Tim ; Meddahi, Nour ; Nyawa, Serge.
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  88. A rank test for the number of factors with high-frequency data. (2019). Liu, Zhi ; Kong, Xin-Bing ; Zhou, Wang.
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  89. A Hausman test for the presence of market microstructure noise in high frequency data. (2019). Xiu, Dacheng ; Ait-Sahalia, Yacine.
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  90. Testing if the market microstructure noise is fully explained by the informational content of some variables from the limit order book. (2019). Potiron, Yoann ; Clinet, Simon.
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  91. Structured volatility matrix estimation for non-synchronized high-frequency financial data. (2019). Kim, Donggyu ; Fan, Jianqing.
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  92. Factor GARCH-Itô models for high-frequency data with application to large volatility matrix prediction. (2019). Fan, Jianqing ; Kim, Donggyu.
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  93. Estimating the integrated volatility with tick observations. (2019). Jacod, Jean ; Zheng, Xinghua ; Li, Yingying.
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  94. 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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  95. Large-dimensional factor modeling based on high-frequency observations. (2019). Pelger, Markus.
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  96. The algebra of two scales estimation, and the S-TSRV: High frequency estimation that is robust to sampling times. (2019). Mykland, Per A ; Chen, Dachuan ; Zhang, Lan.
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  97. 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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  98. Volatility transmission between oil prices and banks stock prices as a new source of instability: Lessons from the US Experience. (2019). Ehouman, Yao Axel.
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  99. Dependent Microstructure Noise and Integrated Volatility: Estimation from High-Frequency Data. (2019). Laeven, Roger ; Vellekoop, M H ; Laeven, R. J. A., ; Li, Z M.
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  100. Bayesian Inference on Volatility in the Presence of Infinite Jump Activity and Microstructure Noise. (2019). Kuffner, Todd ; Jos'e E. Figueroa-L'opez, ; Wang, QI.
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  101. Forecasting securitys volatility using low-frequency historical data, high-frequency historical data and option-implied volatility. (2019). Cui, Xiangyu ; Zhang, Zhiyuan ; Zhou, Yong ; Yuan, Huiling.
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  102. Large Volatility Matrix Prediction with High-Frequency Data. (2019). Song, Xinyu.
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  103. Feature Engineering for Mid-Price Prediction with Deep Learning. (2019). Iosifidis, Alexandros ; Gabbouj, Moncef ; Kanniainen, Juho ; Mirone, Giorgio ; Ntakaris, Adamantios.
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  104. A Score-Driven Conditional Correlation Model for Noisy and Asynchronous Data: an Application to High-Frequency Covariance Dynamics. (2019). Lillo, Fabrizio ; Corsi, Fulvio ; Bormetti, Giacomo ; Buccheri, Giuseppe .
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  105. Testing if the market microstructure noise is fully explained by the informational content of some variables from the limit order book. (2019). Potiron, Yoann ; Clinet, Simon.
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  106. Time-varying Limit Order Book Networks. (2018). Schienle, Melanie ; Liang, Chong ; Chen, Shi ; Hardle, Wolfgang Karl.
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  107. The Magnet Effect of Circuit Breakers: A role of price jumps and market liquidity. (2018). Zhou, Jie ; Wu, Shuai ; Zhu, Zhican ; Jian, Zhihong.
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  108. Reviews of Books and Teaching Materials. (2018). Editors, The.
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  109. Time Varying Heteroskedastic Realized GARCH models for tracking measurement error bias in volatility forecasting. (2018). Storti, Giuseppe ; Naimoli, Antonio ; Gerlach, Richard.
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  110. Time Varying Heteroskedastic Realized GARCH models for tracking measurement error bias in volatility forecasting. (2018). Gerlach, Richard ; Storti, Giuseppe ; Naimoli, Antonio.
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  111. Risk Everywhere: Modeling and Managing Volatility. (2018). Bollerslev, Tim ; Pedersen, Lasse Heje ; Huss, John ; Hood, Benjamin.
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  112. “Scaling Down Downside Risk with Inter-Quantile Semivariances”. (2018). Uribe, Jorge.
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  113. A continuous and efficient fundamental price on the discrete order book grid. (2018). Bonart, Julius ; Lillo, Fabrizio.
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  114. Efficient asymptotic variance reduction when estimating volatility in high frequency data. (2018). Clinet, Simon ; Potiron, Yoann.
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  115. Estimating the integrated volatility using high-frequency data with zero durations. (2018). Liu, Zhi ; Jing, Bing-Yi ; Kong, Xin-Bing.
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  116. Adaptive thresholding for large volatility matrix estimation based on high-frequency financial data. (2018). Kim, Donggyu ; Wang, Yazhen ; Li, Cui-Xia ; Kong, Xin-Bing.
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  117. 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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  118. Risk Everywhere: Modeling and Managing Volatility. (2018). Bollerslev, Tim ; Pedersen, Lasse Heje ; Huss, John ; Hood, Benjamin.
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  119. Estimation of Ornstein-Uhlenbeck Process Using Ultra-High-Frequency Data with Application to Intraday Pairs Trading Strategy. (2018). Tomanov, Petra ; Hol, Vladim'Ir.
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  120. Nonparametric Bayesian volatility learning under microstructure noise. (2018). Gugushvili, Shota ; Spreij, Peter ; Schauer, Moritz ; van der Meulen, Frank .
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  121. Efficient asymptotic variance reduction when estimating volatility in high frequency data. (2018). Potiron, Yoann ; Clinet, Simon.
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  122. Model-Free Approaches to Discern Non-Stationary Microstructure Noise and Time-Varying Liquidity in High-Frequency Data. (2018). Mykland, Per A ; Chen, Richard Y.
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  123. The drift burst hypothesis. (2018). Reno, Roberto ; Oomen, Roel ; Christensen, Kim.
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  124. The realized empirical distribution function of stochastic variance with application to goodness-of-fit testing. (2018). Veliyev, Bezirgen ; Thyrsgaard, Martin ; Christensen, Kim.
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  125. Cross-sectional noise reduction and more efficient estimation of Integrated Variance. (2018). Mirone, Giorgio.
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  128. Bootstrapping Pre-Averaged Realized Volatility under Market Microstructure Noise. (2017). Goncalves, Silvia ; Meddahi, Nour ; Hounyo, Ulrich.
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  129. Determining the integrated volatility via limit order books with multiple records. (2017). Liu, Yiqi ; Ding, Deng.
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  130. Estimation of the Continuous and Discontinuous Leverage Effects. (2017). Fan, Jianqing ; Ait-Sahalia, Yacine ; Yang, Xiye ; Wang, Christina Dan.
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  131. Pre-averaged kernel estimators for the drift function of a diffusion process in the presence of microstructure noise. (2017). Heckman, Nancy ; Greenwood, Priscilla E ; Lee, Woo Yong ; Wefelmeyer, Wolfgang .
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  132. Jump-robust estimation of volatility with simultaneous presence of microstructure noise and multiple observations. (2017). Liu, Zhi.
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  133. On the number of common factors with high-frequency data. (2017). Kong, Xin-Bing.
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  134. Bootstrapping Pre-Averaged Realized Volatility under Market Microstructure Noise. (2017). Goncalves, Silvia ; Meddahi, Nour ; Hounyo, Ulrich.
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  135. Edgeworth expansion for the pre-averaging estimator. (2017). Veliyev, Bezirgen ; Yoshida, Nakahiro ; Podolskij, Mark.
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  136. Realized volatility forecasting of agricultural commodity futures using the HAR model with time-varying sparsity. (2017). Chen, Langnan ; Tian, Fengping ; Yang, KE.
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  137. Econometric analysis of multivariate realised QML: Estimation of the covariation of equity prices under asynchronous trading. (2017). Shephard, Neil ; Xiu, Dacheng.
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  138. On high frequency estimation of the frictionless price: The use of observed liquidity variables. (2017). Chaker, Selma .
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  139. Model-free approaches to discern non-stationary microstructure noise and time-varying liquidity in high-frequency data. (2017). Chen, Richard Y ; Mykland, Per A.
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  140. Inference from high-frequency data: A subsampling approach. (2017). Veliyev, Bezirgen ; Thamrongrat, N ; Podolskij, M ; Christensen, K.
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  141. Bootstrapping integrated covariance matrix estimators in noisy jump–diffusion models with non-synchronous trading. (2017). Hounyo, Ulrich.
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  142. Modeling spot rate using a realized stochastic volatility model with level effect and dynamic drift☆. (2017). Li, Shaoyu ; Zheng, Tingguo .
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  143. Empirical likelihood for high frequency data. (2017). Otsu, Taisuke ; Camponovo, Lorenzo ; Matsushita, Yukitoshi.
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  144. Estimation for high-frequency data under parametric market microstructure noise. (2017). Potiron, Yoann ; Clinet, Simon.
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  145. Decoupling the short- and long-term behavior of stochastic volatility. (2017). Bennedsen, Mikkel ; Pakkanen, Mikko S ; Lunde, Asger.
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  146. Is the diurnal pattern sufficient to explain the intraday variation in volatility? A nonparametric assessment. (2017). Podolskij, Mark ; Hounyo, Ulrich ; Christensen, Kim.
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  147. Decoupling the short- and long-term behavior of stochastic volatility. (2017). Pakkanen, Mikko S ; Lunde, Asger ; Bennedsen, Mikkel.
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  148. Inference from the futures: ranking the noise cancelling accuracy of realized measures. (2017). Mirone, Giorgio.
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  149. Forecasting the realized volatility in the Chinese stock market: further evidence. (2016). Pu, Wang ; Ma, Feng ; Chen, Yixiang.
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  150. Do We Need High Frequency Data to Forecast Variances?. (2016). Laurent, Sébastien ; Hurlin, Christophe ; Candelon, Bertrand ; BANULESCU-RADU, Denisa.
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  151. Jump Variation Estimation with Noisy High Frequency Financial Data via Wavelets. (2016). Wang, Yazhen ; Zhang, Xin ; Kim, Donggyu.
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  152. Market Microstructure Effects on Firm Default Risk Evaluation. (2016). Barsotti, Flavia ; Sanfelici, Simona.
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  153. Continuous and Jump Betas: Implications for Portfolio Diversification. (2016). Yao, Wenying ; Dungey, Mardi ; Alexeev, Vitali.
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  154. Asymptotic theory for large volatility matrix estimation based on high-frequency financial data. (2016). Zou, Jian ; Kim, Donggyu ; Wang, Yazhen.
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  155. Sparse PCA-based on high-dimensional Itô processes with measurement errors. (2016). Wang, Yazhen ; Kim, Donggyu.
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  156. Price and volatility co-jumps. (2016). Renò, Roberto ; Bandi, F M ; Reno, R.
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  157. Efficient estimation of integrated volatility incorporating trading information. (2016). Li, Yingying ; Zheng, Xinghua ; Xie, Shangyu.
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  158. Between data cleaning and inference: Pre-averaging and robust estimators of the efficient price. (2016). Mykland, Per A ; Zhang, Lan.
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  159. 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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  160. Increased correlation among asset classes: Are volatility or jumps to blame, or both?. (2016). Ait-Sahalia, Yacine ; Xiu, Dacheng.
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  161. A nonparametric test of a strong leverage hypothesis. (2016). Whang, Yoon-Jae ; LINTON, OLIVER ; Yen, Yu-Min .
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  162. A bias-corrected estimator of the covariation matrix of multiple security prices when both microstructure effects and sampling durations are persistent and endogenous. (2016). Ikeda, Shin.
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  163. Exploiting the errors: A simple approach for improved volatility forecasting. (2016). Quaedvlieg, Rogier ; Patton, Andrew ; Bollerslev, Tim.
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  164. Estimating the quadratic covariation matrix for asynchronously observed high frequency stock returns corrupted by additive measurement error. (2016). LINTON, OLIVER ; Park, Sujin ; Hong, Seok Young .
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  165. VOLATILITY ESTIMATORS WITH HIGH-FREQUENCY DATA FROM BUCHAREST STOCK EXCHANGE. (2016). Damian, Virgil ; Cepoi, Cosmin Octavian .
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  166. Bootstrapping pre-averaged realized volatility under market microstructure noise. (2016). Goncalves, Silvia ; Hounyo, Ulrich ; Meddahi, Nour ; Gonalves, Silvia.
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  167. Inference for Multi-dimensional High-frequency Data with an Application to Conditional Independence Testing. (2016). Bibinger, Markus ; Mykland, Per A.
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  168. Statistical Inference for Unified Garch–Itô Models with High-Frequency Financial Data. (2016). Kim, Donggyu.
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  169. An Unbiased Measure of Integrated Volatility in the Frequency Domain. (2016). Wang, Fangfang.
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  170. A continuous and efficient fundamental price on the discrete order book grid. (2016). Lillo, Fabrizio ; Bonart, Julius.
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  171. Semimartingale detection and goodness-of-fit tests. (2016). Bull, Adam D..
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  172. Testing for heteroscedasticity in jumpy and noisy high-frequency data: A resampling approach. (2016). Podolskij, Mark ; Hounyo, Ulrich ; Christensen, Kim.
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  173. News, volatility and jumps: the case of natural gas futures. (2015). Borovkova, Svetlana ; Mahakena, Diego .
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  174. Spot volatility estimation using delta sequences. (2015). Renò, Roberto ; Mattiussi, Vanessa ; Reno, Roberto ; Mancini, Cecilia.
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  175. Prediction-based estimating functions for stochastic volatility models with noisy data: comparison with a GMM alternative. (2015). Lunde, Asger ; Brix, Anne .
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  176. FloGARCH : Realizing long memory and asymmetries in returns volatility. (2015). Vander Elst, Harry.
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  177. Inference for Nonparametric High-Frequency Estimators with an Application to Time Variation in Betas. (2015). Kalnina, Ilze.
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  178. Inference for nonparametric high-frequency estimators with an application to time variation in betas. (2015). Kalnina, Ilze.
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  179. The SIML Estimation of Integrated Covariance and Hedging Coefficient Under Round-off Errors, Micro-market Price Adjustments and Random Sampling. (2015). Sato, Seisho ; Misaki, Hiroumi ; Kunitomo, Naoto.
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  180. Nonparametric test for a constant beta between Itô semi-martingales based on high-frequency data. (2015). Tauchen, George ; Todorov, Viktor ; Rei, Markus .
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  181. Microstructure noise in the continuous case: Approximate efficiency of the adaptive pre-averaging method. (2015). Jacod, Jean ; Mykland, Per A..
    In: Stochastic Processes and their Applications.
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  182. Functional stable limit theorems for quasi-efficient spectral covolatility estimators. (2015). Altmeyer, Randolf ; Bibinger, Markus.
    In: Stochastic Processes and their Applications.
    RePEc:eee:spapps:v:125:y:2015:i:12:p:4556-4600.

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  183. Volatility forecast of stock indices by model averaging using high-frequency data. (2015). Wang, Chengyang ; Nishiyama, Yoshihiko .
    In: International Review of Economics & Finance.
    RePEc:eee:reveco:v:40:y:2015:i:c:p:324-337.

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  184. Evaluating the performance of futures hedging using multivariate realized volatility. (2015). Ubukata, Masato ; Watanabe, Toshiaki .
    In: Journal of the Japanese and International Economies.
    RePEc:eee:jjieco:v:38:y:2015:i:c:p:148-171.

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  185. Volatility forecasting: The role of lunch-break returns, overnight returns, trading volume and leverage effects. (2015). Wang, Xunxiao ; Xu, Weidong ; Wu, Chongfeng.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:31:y:2015:i:3:p:609-619.

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  186. Trading price jump clusters in foreign exchange markets. (2015). Urga, Giovanni ; Novotn, Jan ; Petrov, Dmitri .
    In: Journal of Financial Markets.
    RePEc:eee:finmar:v:24:y:2015:i:c:p:66-92.

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  187. The fine structure of equity-index option dynamics. (2015). Tauchen, George ; Andersen, Torben ; Todorov, Viktor ; Bondarenko, Oleg.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:187:y:2015:i:2:p:532-546.

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  188. Does anything beat 5-minute RV? A comparison of realized measures across multiple asset classes. (2015). Patton, Andrew ; Liu, Lily ; Sheppard, Kevin.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:187:y:2015:i:1:p:293-311.

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  189. Econometrics of co-jumps in high-frequency data with noise. (2015). Winkelmann, Lars ; Bibinger, Markus.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:184:y:2015:i:2:p:361-378.

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  190. Edgeworth expansion for the pre-averaging estimator. (2015). Veliyev, Bezirgen ; Podolskij, Mark ; Yoshida, Nakahiro.
    In: Papers.
    RePEc:arx:papers:1512.04716.

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  191. The geometry of relative arbitrage. (2015). Pal, Soumik ; Wong, Ting-Kam Leonard .
    In: Papers.
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  192. Edgeworth expansion for the pre-averaging estimator. (2015). Veliyev, Bezirgen ; Yoshida, Nakahiro ; Podolskij, Mark.
    In: CREATES Research Papers.
    RePEc:aah:create:2015-60.

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  193. Inference from high-frequency data: A subsampling approach. (2015). Veliyev, Bezirgen ; Christensen, Kim ; Thamrongrat, Nopporn ; Podolskij, Mark.
    In: CREATES Research Papers.
    RePEc:aah:create:2015-45.

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  194. Validity of Edgeworth expansions for realized volatility estimators. (2015). Veliyev, Bezirgen ; Hounyo, Ulrich.
    In: CREATES Research Papers.
    RePEc:aah:create:2015-21.

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  195. Exploiting the Errors: A Simple Approach for Improved Volatility Forecasting. (2015). Quaedvlieg, Rogier ; Patton, Andrew ; Bollerslev, Tim.
    In: CREATES Research Papers.
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  196. Asymmetric Realized Volatility Risk. (2014). McAleer, Michael ; Allen, David ; Scharth, and Marcel .
    In: Tinbergen Institute Discussion Papers.
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  197. A Realized Stochastic Volatility Model With Box-Cox Transformation. (2014). Song, Tao ; Zheng, Tingguo .
    In: Journal of Business & Economic Statistics.
    RePEc:taf:jnlbes:v:32:y:2014:i:4:p:593-605.

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  198. On the Estimation of Integrated Volatility With Jumps and Microstructure Noise. (2014). Jing, Bing-Yi ; Liu, Zhi ; Kong, Xin-Bing.
    In: Journal of Business & Economic Statistics.
    RePEc:taf:jnlbes:v:32:y:2014:i:3:p:457-467.

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  199. Market variance risk premiums in Japan for asset predictability. (2014). Ubukata, Masato ; Watanabe, Toshiaki.
    In: Empirical Economics.
    RePEc:spr:empeco:v:47:y:2014:i:1:p:169-198.

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  200. Alternative Beta Risk Estimators in Emerging Markets: The Case of Tunisia. (2014). Hasnaoui, Habib .
    In: International Journal of Empirical Finance.
    RePEc:rss:jnljef:v2i2p5.

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  201. Kernel filtering of spot volatility in presence of Lévy jumps and market microstructure noise. (2014). Zhang, BO ; Fang, Yue ; Zhao, Xujie ; Yu, Chao .
    In: MPRA Paper.
    RePEc:pra:mprapa:63293.

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  202. Do We Need Ultra-High Frequency Data to Forecast Variances?. (2014). Laurent, Sébastien ; Hurlin, Christophe ; Candelon, Bertrand ; BANULESCU-RADU, Denisa.
    In: Working Papers.
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  203. Asymmetric Realized Volatility Risk. (2014). Scharth, Marcel ; McAleer, Michael ; Allen, David.
    In: JRFM.
    RePEc:gam:jjrfmx:v:7:y:2014:i:2:p:80-109:d:37458.

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  204. Inference on the Lévy measure in case of noisy observations. (2014). Vetter, Mathias .
    In: Statistics & Probability Letters.
    RePEc:eee:stapro:v:87:y:2014:i:c:p:125-133.

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  205. Limit theorems for the pre-averaged Hayashi–Yoshida estimator with random sampling. (2014). Koike, Yuta.
    In: Stochastic Processes and their Applications.
    RePEc:eee:spapps:v:124:y:2014:i:8:p:2699-2753.

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  206. Specification test for Markov models with measurement errors. (2014). Kim, Seonjin ; Zhao, Zhibiao.
    In: Journal of Multivariate Analysis.
    RePEc:eee:jmvana:v:130:y:2014:i:c:p:118-133.

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  207. Fact or friction: Jumps at ultra high frequency. (2014). Christensen, Kim ; OOMEN, Roel C. A., ; Podolskij, Mark.
    In: Journal of Financial Economics.
    RePEc:eee:jfinec:v:114:y:2014:i:3:p:576-599.

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  208. Estimating spot volatility with high-frequency financial data. (2014). Zu, Yang ; Boswijk, Peter H..
    In: Journal of Econometrics.
    RePEc:eee:econom:v:181:y:2014:i:2:p:117-135.

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  209. A quasi-maximum likelihood approach for integrated covariance matrix estimation with high frequency data. (2014). Liu, Cheng ; Tang, Cheng Yong.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:180:y:2014:i:2:p:217-232.

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  210. Optimal design of Fourier estimator in the presence of microstructure noise. (2014). Wang, Fangfang.
    In: Computational Statistics & Data Analysis.
    RePEc:eee:csdana:v:76:y:2014:i:c:p:708-722.

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  211. Disentangled jump-robust realized covariances and correlations with non-synchronous prices. (2014). Elst, Harry Vander ; Veredas, David.
    In: DES - Working Papers. Statistics and Econometrics. WS.
    RePEc:cte:wsrepe:ws142416.

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  212. Disentangled jump-robust realized covariances and correlations with non-synchronous prices. (2014). Veredas, David ; Elst, Harry Vander.
    In: DES - Working Papers. Statistics and Econometrics. WS.
    RePEc:cte:wsrepe:es142416.

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  213. Spectral Estimation of Covolatility from Noisy Observations Using Local Weights. (2014). Bibinger, Markus ; Rei, Markus .
    In: Scandinavian Journal of Statistics.
    RePEc:bla:scjsta:v:41:y:2014:i:1:p:23-50.

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  214. Testing the maximal rank of the volatility process for continuous diffusions observed with noise. (2014). Fissler, Tobias ; Podolskij, Mark.
    In: CREATES Research Papers.
    RePEc:aah:create:2014-52.

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  215. Bootstrapping integrated covariance matrix estimators in noisy jump-diffusion models with non-synchronous trading. (2014). Hounyo, Ulrich.
    In: CREATES Research Papers.
    RePEc:aah:create:2014-35.

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  216. Positive Semidefinite Integrated Covariance Estimation, Factorizations and Asynchronicity. (2014). Quaedvlieg, Rogier ; Laurent, Sébastien ; Boudt, Kris ; Lunde, Asger.
    In: CREATES Research Papers.
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  217. A Quantile-based Realized Measure of Variation: New Tests for Outlying Observations in Financial Data. (2013). Bos, Charles ; Janus, Pawel .
    In: Tinbergen Institute Discussion Papers.
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  218. Realized Volatility Risk. (2013). McAleer, Michael ; Allen, David ; Scharth, Marcel.
    In: Tinbergen Institute Discussion Papers.
    RePEc:tin:wpaper:20130092.

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  219. A direct approach to risk approximation for vast portfolios under gross-exposure constraint using high-frequency data. (2013). Kong, Xin-Bing.
    In: TEST: An Official Journal of the Spanish Society of Statistics and Operations Research.
    RePEc:spr:testjl:v:22:y:2013:i:4:p:647-669.

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  220. Limit Theorems for the Pre-averaged Hayashi-Yoshida Estimator with Random Sampling. (2013). Koike, Yuta.
    In: Global COE Hi-Stat Discussion Paper Series.
    RePEc:hst:ghsdps:gd12-276.

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  221. Pricing Nikkei 225 Options Using Realized Volatility. (2013). Ubukata, Masato ; Watanabe, Toshiaki .
    In: Global COE Hi-Stat Discussion Paper Series.
    RePEc:hst:ghsdps:gd12-273.

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  222. Adaptive Realized Kernels. (2013). Kotchoni, Rachidi ; Carrasco, Marine.
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  223. Measuring the relevance of the microstructure noise in financial data. (2013). Mancini, Cecilia .
    In: Stochastic Processes and their Applications.
    RePEc:eee:spapps:v:123:y:2013:i:7:p:2728-2751.

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  224. Volatility inference in the presence of both endogenous time and microstructure noise. (2013). Zheng, Xinghua ; Zhang, Zhiyuan ; Li, Yingying.
    In: Stochastic Processes and their Applications.
    RePEc:eee:spapps:v:123:y:2013:i:7:p:2696-2727.

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  225. Optimally thresholded realized power variations for Lévy jump diffusion models. (2013). Nisen, Jeffrey ; Figueroa-Lopez, Jose E..
    In: Stochastic Processes and their Applications.
    RePEc:eee:spapps:v:123:y:2013:i:7:p:2648-2677.

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  226. On covariation estimation for multivariate continuous Itô semimartingales with noise in non-synchronous observation schemes. (2013). Christensen, Kim ; Podolskij, Mark ; Vetter, Mathias .
    In: Journal of Multivariate Analysis.
    RePEc:eee:jmvana:v:120:y:2013:i:c:p:59-84.

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  227. The leverage effect puzzle: Disentangling sources of bias at high frequency. (2013). Fan, Jianqing ; Ait-Sahalia, Yacine.
    In: Journal of Financial Economics.
    RePEc:eee:jfinec:v:109:y:2013:i:1:p:224-249.

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  228. Disentangling the effect of jumps on systematic risk using a new estimator of integrated co-volatility. (2013). Liu, Junwei ; Wang, Kent .
    In: Journal of Banking & Finance.
    RePEc:eee:jbfina:v:37:y:2013:i:5:p:1777-1786.

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  229. Financial Risk Measurement for Financial Risk Management. (2013). Andersen, Torben G ; Diebold, Francis X ; Christoffersen, Peter F ; Bollerslev, Tim.
    In: Handbook of the Economics of Finance.
    RePEc:eee:finchp:2-b-1127-1220.

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  230. The role of realized ex-post covariance measures and dynamic model choice on the quality of covariance forecasts. (2013). Voev, Valeri ; Varneskov, Rasmus .
    In: Journal of Empirical Finance.
    RePEc:eee:empfin:v:20:y:2013:i:c:p:83-95.

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  231. Testing whether the underlying continuous-time process follows a diffusion: An infinitesimal operator-based approach. (2013). SONG, ZHAOGANG ; Chen, Bin.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:173:y:2013:i:1:p:83-107.

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  232. A Distributional Approach to Realized Volatility. (2013). Meddahi, Nour ; Chaker, Selma.
    In: Staff Working Papers.
    RePEc:bca:bocawp:13-49.

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  233. Volatility Forecasting when the Noise Variance Is Time-Varying. (2013). Meddahi, Nour ; Chaker, Selma.
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  234. The Fine Structure of Equity-Index Option Dynamics. (2013). Tauchen, George ; Andersen, Torben ; Todorov, Viktor ; Bondarenko, Oleg.
    In: CREATES Research Papers.
    RePEc:aah:create:2013-52.

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  235. Bootstrapping pre-averaged realized volatility under market microstructure noise. (2013). Meddahi, Nour ; Goncalves, Silvia ; Hounyo, Ulrich.
    In: CREATES Research Papers.
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  236. Estimating Stochastic Volatility Models using Prediction-based Estimating Functions. (2013). Lunde, Asger ; Brix, Anne Floor .
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  237. Bootstrap inference for pre-averaged realized volatility based on non-overlapping returns. (2013). Meddahi, Nour ; Goncalves, Silvia ; Hounyo, Ulrich ; Gonalves, Silvia.
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  238. Non-parametric estimation of the diffusion coefficient from noisy data. (2012). Schmisser, emeline .
    In: Statistical Inference for Stochastic Processes.
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  239. Econometric analysis of multivariate realised QML: efficient positive semi-definite estimators of the covariation of equity prices. (2012). Xiu, Dacheng ; Shephard, Neil.
    In: Economics Series Working Papers.
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  240. Efficient and feasible inference for the components of financial variation using blocked multipower variation. (2012). Sheppard, Kevin ; Shephard, Neil ; Mykland, Per A..
    In: Economics Series Working Papers.
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  241. Econometric analysis of multivariate realised QML: efficient positive semi-definite estimators of the covariation of equity prices. (2012). Shephard, Neil ; Xiu, Dacheng.
    In: Economics Papers.
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  242. Efficient and feasible inference for the components of financial variation using blocked multipower variation. (2012). Sheppard, Kevin ; Shephard, Neil ; Mykland, Per A..
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  243. Financial Risk Measurement for Financial Risk Management. (2012). Diebold, Francis ; Christoffersen, Peter ; Bollerslev, Tim ; Andersen, Torben.
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  244. Parametric Inference and Dynamic State Recovery from Option Panels. (2012). Andersen, Torben ; Fusari, Nicola ; Todorov, Viktor.
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  245. Stochastic volatility and stochastic leverage. (2012). Veraart, Almut.
    In: Annals of Finance.
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  246. Parametric Inference and Dynamic State Recovery from Option Panels. (2012). Andersen, Torben ; Fusari, Nicola ; Todorov, Viktor.
    In: Global COE Hi-Stat Discussion Paper Series.
    RePEc:hst:ghsdps:gd12-266.

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  247. Estimating the Quadratic Covariation Matrix for an Asynchronously Observed Continuous Time Signal Masked by Additive Noise. (2012). LINTON, OLIVER ; Park, Sujin .
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  248. Spot Volatility Estimation Using Delta Sequences. (2012). Renò, Roberto ; Mancini, Cecilia ; Mattiussi, Vanessa ; Reno, Roberto.
    In: Working Papers - Mathematical Economics.
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  249. Measuring the relevance of the microstructure noise in financial data. (2012). Mancini, Cecilia .
    In: Working Papers - Mathematical Economics.
    RePEc:flo:wpaper:2012-09.

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  250. Microstructure effect on firm’s volatility risk. (2012). Barsotti, Flavia.
    In: Working Papers - Mathematical Economics.
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  251. Estimation of Quarticity with High Frequency Data. (2012). Mancino, Maria Elvira.
    In: Working Papers - Mathematical Economics.
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  252. An estimator for the quadratic covariation of asynchronously observed Itô processes with noise: Asymptotic distribution theory. (2012). Bibinger, Markus.
    In: Stochastic Processes and their Applications.
    RePEc:eee:spapps:v:122:y:2012:i:6:p:2411-2453.

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  253. Jumps in equilibrium prices and market microstructure noise. (2012). Mykland, Per A. ; Lee, Suzanne S..
    In: Journal of Econometrics.
    RePEc:eee:econom:v:168:y:2012:i:2:p:396-406.

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  254. Testing for jumps in noisy high frequency data. (2012). Ait-Sahalia, Yacine ; Jacod, Jean ; At-Sahalia, Yacine .
    In: Journal of Econometrics.
    RePEc:eee:econom:v:168:y:2012:i:2:p:207-222.

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  255. On the estimation of integrated covariance matrices of high dimensional diffusion processes. (2012). Zheng, Xinghua ; Li, Yingying.
    In: Papers.
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  256. The Analysis of Stochastic Volatility in the Presence of Daily Realised Measures. (2011). Koopman, Siem Jan ; Scharth, Marcel.
    In: Tinbergen Institute Discussion Papers.
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  257. Financial Risk Measurement for Financial Risk Management. (2011). Diebold, Francis ; Christoffersen, Peter ; Bollerslev, Tim ; Andersen, Torben.
    In: PIER Working Paper Archive.
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  258. Testing for co-jumps in high-frequency financial data: an approach based on first-high-low-last prices. (2011). Liao, Yin ; Anderson, Heather.
    In: Monash Econometrics and Business Statistics Working Papers.
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  259. Multivariate realised kernels: Consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading. (2011). Lunde, Asger ; Hansen, Peter Reinhard ; Barndorff-Nielsen, Ole E. ; Shephard, Neil.
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  260. Multivariate realised kernels: Consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading. (2011). Shephard, Neil ; Hansen, Peter ; Lunde, Asger ; Barndorff-Nielsen, Ole E..
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  261. 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.
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  262. Asymptotic results for time-changed Lévy processes sampled at hitting times. (2011). TANKOV, PETER ; Rosenbaum, Mathieu.
    In: Stochastic Processes and their Applications.
    RePEc:eee:spapps:v:121:y:2011:i:7:p:1607-1632.

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  263. Limit theorems in the Fourier transform method for the estimation of multivariate volatility. (2011). Gloter, Arnaud ; Clement, Emmanuelle .
    In: Stochastic Processes and their Applications.
    RePEc:eee:spapps:v:121:y:2011:i:5:p:1097-1124.

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  264. Multivariate realised kernels: Consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading. (2011). Shephard, Neil ; Lunde, Asger ; Hansen, Peter ; Barndorff-Nielsen, Ole E..
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    RePEc:eee:econom:v:162:y:2011:i:2:p:149-169.

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  265. Subsampling high frequency data. (2011). Kalnina, Ilze.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:161:y:2011:i:2:p:262-283.

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  266. Covariance measurement in the presence of non-synchronous trading and market microstructure noise. (2011). Griffin, Jim ; OOMEN, Roel C. A., .
    In: Journal of Econometrics.
    RePEc:eee:econom:v:160:y:2011:i:1:p:58-68.

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  267. Estimating covariation: Epps effect, microstructure noise. (2011). Zhang, Lan.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:160:y:2011:i:1:p:33-47.

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  268. Edgeworth expansions for realized volatility and related estimators. (2011). Ait-Sahalia, Yacine ; Zhang, Lan ; Mykland, Per A..
    In: Journal of Econometrics.
    RePEc:eee:econom:v:160:y:2011:i:1:p:190-203.

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  269. Ultra high frequency volatility estimation with dependent microstructure noise. (2011). Ait-Sahalia, Yacine ; Zhang, Lan ; Mykland, Per A..
    In: Journal of Econometrics.
    RePEc:eee:econom:v:160:y:2011:i:1:p:160-175.

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  270. Non-parametric drift estimation for diffusions from noisy data. (2011). Emeline, Schmisser .
    In: Statistics & Risk Modeling.
    RePEc:bpj:strimo:v:28:y:2011:i:2:p:119-150:n:3.

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  271. Modeling microstructure noise with mutually exciting point processes. (2011). Hoffmann, Marc ; Bacry, E. ; Delattre, S. ; Muzy, J. F..
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  272. Parametric Inference and Dynamic State Recovery from Option Panels. (2011). Andersen, Torben ; Todorov, Viktor ; Fusari, Nicola.
    In: CREATES Research Papers.
    RePEc:aah:create:2012-11.

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  273. Financial Risk Measurement for Financial Risk Management. (2011). Diebold, Francis ; Christoffersen, Peter ; Bollerslev, Tim ; Andersen, Torben.
    In: CREATES Research Papers.
    RePEc:aah:create:2011-37.

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  274. Pre-averaging based estimation of quadratic variation in the presence of noise and jumps: Theory, implementation, and empirical evidence. (2010). Hautsch, Nikolaus ; Podolskij, Mark.
    In: CFS Working Paper Series.
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  275. New tests for jumps in semimartingale models. (2010). Podolskij, Mark ; Ziggel, D..
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  279. Threshold bipower variation and the impact of jumps on volatility forecasting. (2010). Renò, Roberto ; Pirino, Davide ; Corsi, Fulvio ; Reno, Roberto.
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