Jia li duke

Download CVupdated on Nov 24, School of Economics, Singapore Management University. Visiting Professor Spring.

We develop econometric tools for studying jump dependence of two processes from high-frequency observations on a fixed time interval. In this context, only segments of data around a few outlying observations are informative for the inference. We derive an asymptotically valid test for stability of a linear jump relation over regions of the jump size domain. The test has power against general forms of nonlinearity in the jump dependence as well as temporal instabilities. We further propose an efficient estimator for the linear jump regression model that is formed by optimally weighting the detected jumps with weights based on the diffusive volatility around the jump times.

Jia li duke

Date: March 25 th Wed. Time: pmpm. Location: Building 1, Room , Faculty Lounge. Language: English. We propose a semiparametric two-step inference procedure for a finite-dimensional parameter based on moment conditions constructed from high-frequency data. The population moment conditions take the form of temporally integrated functionals of state-variable processes that include the latent stochastic volatility process of an asset. In the first step, we nonparametrically recover the volatility path from high-frequency asset returns. The nonparametric volatility estimator is then used to form sample moment functions in the second-step GMM estimation, which requires the correction of a high-order nonlinearity bias from the first step. We show that the proposed estimator is consistent and asymptotically mixed Gaussian and propose a consistent estimator for the conditional asymptotic variance. We also construct a Bierens-type consistent specification test.

Hack Professor, Princeton University Verified email at princeton. New citations to this author.

We develop robust inference methods for studying linear dependence between the jumps of discretely observed processes at high frequency. Unlike classical linear regressions, jump regressions are determined by a small number of jumps occurring over a fixed time interval and the rest of the components of the processes around the jump times. The latter are the continuous martingale parts of the processes as well as observation noise. By sampling more frequently the role of these components, which are hidden in the observed price, shrinks asymptotically. The robustness of our inference procedure is with respect to outliers, which are of particular importance in the current setting of relatively small number of jump observations.

He was also the ninth ruler of Jin in the Spring and Autumn period and the second duke of Jin. He reigned for 26 years. During his reign, the State of Jin was one of the most powerful and largest states due to his conquests in many small neighboring states. He is also renowned for the slaughter and exile of many royal family members of Jin and for favoring one of his concubines named Li Ji. When he ascended the throne, Duke Xian of Jin and the duke of Guo visited King Hui of Zhou and they were given rewards which resulted to the increase of their popularity throughout the states. This resulted to the increase of the power of the duke and the loss of political power of the clan of the duke since the clan was almost annihilated. To increase the military power of the state, he expanded his army into 2 troops, each having 10, men some say 12,

Jia li duke

James L. Meriam Distinguished Professor of Biomedical Engineering. Director, Center for Quantitative Biodesign. University of Wisconsin at Madison, M. Chengdu University of Science and Technology China , My research revolves around ecology and evolution of microbial communities with specific emphases on antibiotic resistance, spatial dynamics, and pattern formation.

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Skip to main content. Try again later. Advanced Search. Associate Editor, Econometrica Present. Time: pmpm Location: Building 1, Room , Faculty Lounge Language: English Abstract: We propose a semiparametric two-step inference procedure for a finite-dimensional parameter based on moment conditions constructed from high-frequency data. Publication Type Journal Article. Advanced Search. The system can't perform the operation now. See Research. The , IAAE meetings. Email address for updates. In this context, only segments of data around a few outlying observations are informative for the inference.

In the last three decades, technological innovations, like the adoption of algorithmic trading, have paved the way for many changes in the U.

Information about your use of this site is shared with Google. School of Economics, Singapore Management University. Fellow, The Society for Financial Econometrics Copyright Owner and License Publisher. Merged citations. Add co-authors Co-authors. Publication Journal of the American Statistical Association. Tim Bollerslev Duke University Verified email at duke. Privacy Terms Help. Skip to main content. About Scholar Search help.