Sub-diffraction-limit Observation Realized by Nonlinear Metamaterial Lens (2009)
Wang, Zhiyu, Luo, Yu, Peng, Liang, Huangfu, Jiangtao, Jiang, Tao, Wang, Dongxing, ...
In this paper, we show by experiment that by covering a thin flat nonlinear lens on the sources, the sub-diffraction-limit observation can be achieved by measuring either the near-field distribution...
Still Fit Generalized Pareto Distributions? (2009)
In the literature of analyzing extremes, both generalized Pareto distribution and Pareto distribution are employed to infer the tail of a distribution with a known positive extreme value index....
Second-Harmonic Generation and Spectrum Modulation by Active Nonlinear Metamaterial (2009)
Wang, Zhiyu, Luo, Yu, Peng, Liang, Huangfu, Jiangtao, Jiang, Tao, Wang, Dongxing, ...
The nonlinear properties of a metamaterial sample composed of double-layer metallic patterns and voltage controllable diodes are experimentally investigated. Second harmonics and spectrum modulations...
Maximum likelihood estimation of extreme value index for irregular cases (2009)
A method in analyzing extremes is to fit a generalized Pareto distribution to the exceedances over a high threshold. By varying the threshold according to the sample size [Smith, R.L., 1987....
Effects of data dimension on empirical likelihood (2009)
Chen, Song Xi, Peng, Liang, Qin, Ying-Li
We evaluate the effects of data dimension on the asymptotic normality of the empirical likelihood ratio for high-dimensional data under a general multivariate model. Data dimension and dependence...
Maximum likelihood estimation of extreme value index for irregular cases (2009)
A method in analyzing extremes is to fit a generalized Pareto distribution to the exceedances over a high threshold. By varying the threshold according to the sample size [Smith, R.L., 1987....
Maximum likelihood estimation of extreme value index for irregular cases ∗ (2008)
Liang Peng, Yongcheng Qi, Chen Zhou
Abstract: A method in analyzing extremes is to fit a generalized Pareto distribution to the exceedances over a high threshold. By varying the threshold according to the sample size, [12] and [5]...
ESTIMATING THE FIRST AND SECOND ORDER PARAMETERS OF A HEAVY TAILED DISTRIBUTION (2008)
We suggest censored maximum likelihood estimators for the first and second order parameters of a heavy tailed distribution by incorporating the second order regular variation into the censored...
Conditional Variance Estimation in Heteroscedastic Regression Models (2008)
Lu-hung Chen, Ming-yen Cheng, Liang Peng
First, we propose a new method for estimating the conditional variance in het-eroscedasticity regression models. For heavy tailed innovations, this method is in general more efficient than either of...
Experimental Measurement of Lower and Upper Bounds of Concurrence for Mixed Quantum States (2008)
Niu, Xiao-Ling, Gong, Yan-Xiao, Li, Jian, Peng, Liang, Zhang, Cheng-Jie, Zhang, Yong-Sheng, ...
We experimentally measure the lower and upper bounds of concurrence for a set of two-qubit mixed quantum states using photonic systems. The measured concurrence bounds are in agreement with the...
Astrocyte–Neuron Interaction During One-trial Aversive Learning in the (2008)
Neonate Chick, Leif Hertz, Brona S. O’dowd, Stephen R. Robinson, ...
PENG, R. HUANG AND K.T. NG. Astrocyte–neuron interaction during one-trial aversive learning in the neonate chick. NEUROSCI BIOBEHAV REV 20(3)537–551,1996.—Duringtwo specific stages of the...
Linear-Optical Implementation of Perfect Discrimination between Single-bit Unitary Operations (2008)
Zhang, Pei, Peng, Liang, Wang, Zhi-Wei, Ren, Xi-Feng, Liu, Bi-Heng, Huang, Yun-Feng, ...
Discrimination of unitary operations is a fundamental quantum information processing task. Assisted with linear optical elements, we experimentally demonstrate perfect discrimination between...
Venture Capital and Sequential Investments (2008)
Dirk Bergemann, Ulrich Hege, Liang Peng
We analyze sequential investment decisions in an innovative project that depend on the investor’s information about the project failure risk and its potential …nal value. We consider the feedback...
The Performance Model of SilkRoad- A Multithreaded DSM System for Clusters (2007)
Liang Peng, Weng-fai Wong, Chung-kwong Yuen
Distributed Shared Memory (DSM) is a highly desirable programming model for cluster based computing. Even though a number of software DSMs have been developed with their performance evaluated, few of...
An adaptive optimal estimate of the tail index for MA(l) time series
Reducing variance in univariate smoothing (2007)
Cheng, Ming-Yen, Peng, Liang, Wu, Jyh-Shyang
A variance reduction technique in nonparametric smoothing is proposed: at each point of estimation, form a linear combination of a preliminary estimator evaluated at nearby points with the...
Confidence regions for high quantiles of a heavy tailed distribution (2006)
Estimating high quantiles plays an important role in the context of risk management. This involves extrapolation of an unknown distribution function. In this paper we propose three methods, namely,...
Confidence regions for high quantiles of a heavy tailed distribution (2006)
Estimating high quantiles plays an important role in the context of risk management. This involves extrapolation of an unknown distribution function. In this paper we propose three methods, namely,...
Multivariate Tail Copula: Modeling and Estimation (2006)
Klüppelberg, Claudia, Kuhn, Gabriel, Peng, Liang
In general, risk of an extreme outcome in financial markets can be expressed as a function of the tail copula of a high-dimensional vector after standardizing marginals. Hence it is of importance to...
Empirical Likelihodd Methods for an AR(1) process with ARCH(1) errors (2006)
Klüppelberg, Claudia, Peng, Liang
For an AR(1) process with ARCH(1) errors, we propose empirical likelihood tests for testing whether the sequence is strictly stationary but has infinite variance, or the sequence is an ARCH(1)...
Estimating Tail Dependence of Elliptical Distributions (2006)
Klüppelberg, Claudia, Kuhn, Gabriel, Peng, Liang
Recently there has been an increasing interest in applying elliptical distributions to risk management. Under weak conditions, Hult and Lindskog (2002) showed that a random vector with an elliptical...
Weighted least absolute deviations estimation for an AR(1) process with ARCH(1) errors (2005)
The weighted least absolute deviations estimator is studied for an AR(1) process with ARCH(1) errors ϵt. Unlike for the quasi maximum likelihood estimator, the estimator's, limiting...
Empirical-likelihood-based confidence interval for the mean with a heavy-tailed distribution (2004)
Empirical-likelihood-based confidence intervals for a mean were introduced by Owen [Biometrika 75 (1988) 237-249], where at least a finite second moment is required. This excludes some important...
Empirical-likelihood-based confidence interval for the mean with a heavy-tailed distribution (2004)
Empirical-likelihood-based confidence intervals for a mean were introduced by Owen [Biometrika 75 (1988) 237–249], where at least a finite second moment is required. This excludes some important...
Nonparametric regression under dependent errors with infinite variance (2004)
We consider local least absolute deviation (LLAD) estimation for trend functions of time series with heavy tails which are characterised via a symmetric stable law distribution. The setting includes...
Least absolute deviations estimation for ARCH and GARCH models (2003)
Hall & Yao (2003) showed that, for ARCH/GARCH, i.e. autoregressive conditional heteroscedastic/generalised autoregressive conditional heteroscedastic, models with heavy‐tailed errors,...
Hall, Peter, Peng, Liang, Tajvidi, Nader
A feature that distinguishes extreme-value contexts from more conventional statistical problems is that in the former we often wish to make predictions well beyond the range of the data. For example,...
Prediction and nonparametric estimation for time series with heavy tails (2002)
Hall, Peter, Peng, Liang, Yao, Qiwei
Motivated by prediction problems for time series with heavy-tailed marginal distributions, we consider methods based on `local least absolute deviations' for estimating a regression median from...
SilkRoad II: A MultiParadigm Runtime System for Cluster Computing (2002)
Liang Peng, Weng Fai Wong, Chung Kwong Yuen
A parallel programming paradigm dictates the way an application is to be expressed. It also restricts the algorithms that may be used in the application. Unfortunately, runtime systems for parallel...
Confidence intervals for the tail index (2001)
One of the best-known estimators for the tail index of a heavy-tailed distribution is the Hill estimator. In this paper, confidence intervals based on the asymptotic normal approximation of the Hill...
Thesis (M.S.)--University of Wisconsin--Milwaukee, 2001.
VRIJE UNIVERSITEIT BRUSSEL SCIENTIA (2001)
Vincere Tenebras, Ecole Des, Mines De Nantes, Salinas Caro, Victor Hugo Arroyo, Kristof De Vos, ...
I would like to thank and dedicate this work to Carla and Santiago because they are my spiritual support to do these things, and the most important beings in my life. to my father, Cristo, because...
Geluk, Jaap L., Peng, Liang, De Vries, Casper G.
Suppose X1,X2 are independent random variables satisfying a second-order regular variation condition on the tail-sum and a balance condition on the tails. In this paper we give a description of the...
The maturation of naive human CD4 T lymphocytes--[microform]. (1998)
Thesis (Ph. D.)--Université de Montréal, 1996.
A Dynamic Pricing Method in E-Commerce Based on PSO-trained Neural Network (1970)
Recently, dynamic pricing has been a common competitive maneuver in e-commerce. In many industries, firms adjust the product price dynamically by the current product inventory and the future demand...
Partial derivatives and confidence intervals of bivariate tail dependence functions (0000)
Bivariate extreme value theory was used to estimate a rare event (see de Haan and de Ronde [1998. Sea and wind: multivariate extremes at work. Extremes 1, 7Â45]). This procedure involves...
Do individual investors learn from their trading experience
This paper investigates whether individual investors adjust their stock trading according to their stock selection abilities, which can be inferred from their trading history. Fixed-effect panel...
A Bootstrap-based Method to Achieve Optimality in Estimating the Extreme-value Index
Estimators of the extreme-value index are based on a set of upper order statistics. We present an adaptive method to choose the number of order statistics involved in an optimal way, balancing...
Approximation by Penultimate Stable Laws
Liang Peng, H. Iglesias Pereira
In certain cases partial sums of i.i.d. random variables with finite variance are better approximated by a sequence of stable distributions with indices \alpha_n \to 2 than by a normal distribution....
The paper characterizes first and second order tail behavior of convolutions of i.i.d. heavy tailed random variables with support on the real line. The result is applied to the problem of risk...
Exploring Metropolitan Housing Price Volatility
This paper uses GARCH models and a panel VAR model to analyze possible time variation of the volatility of single-family home value appreciation and the interactions between the volatility and the...
Estimating House Price Indexes in the Presence of Seller Reservation Prices
We analyze a bias in transaction-based price indexes due to the presence of seller reservation prices. We develop a model in which the ratio of sellers' reservation prices to the market value affects...
A New Historical Database For The NYSE 1815 To 1925: Performance And Predictability
William N. Goetzmann, Roger G. Ibbotson, Liang Peng
In this paper, we collect individual stock prices for NYSE stocks over the period 1815 to 1925 and individual dividend data over the period 1825 to 1870. We use monthly price and dividend information...
The Bias of the RSR Estimator and the Accuracy of Some Alternatives
William N. Goetzmann, Liang Peng
This paper analyzes the implications of cross-sectional hetero- skedasticity in repeat sales regression (RSR). RSR estimators are essentially geometric averages of individual asset returns because of...
A New Approach of Valuing Illiquid Asset Portfolios
This paper proposes a new approach of valuing portfolios that contain illiquid assets. The approach has three major advantages. First, the estimators are arithmetic averages of individual asset...
This paper develops a real-time structural model of price formation, and uses it to investigate the dynamics of effective quotes and bid-ask spreads between consecutive trades. There is some evidence...
Building A Venture Capital Index
This paper builds a venture capital index from 1987 to 1999 that consists of 12,946 rounds of venture financing with 5,643 venture-backed firms. The paper uses two innovative techniques, a...
A standard assumption of market microstructure models is that traders process the information content of past trading activities instantly. In a more realistic setting, they need time to do so and...
Estimating Indices in the Presence of Seller Reservation Prices
Liang Peng, William N. Goetzmann
This paper documents the potential bias induced in an index of asset prices when sellers use reservation rules that may include some component of private value. We develop a model in which the...
A New Historical Database For The NYSE 1815 To 1925: Performance And Predictability
William N. Goetzmann, ROGER G. IBBOTSON, LIANG PENG
In this paper, we collect individual stock prices for NYSE stocks over the period 1815 to 1925 and individual dividend data over the period 1825 to 1870. We use monthly price and dividend information...
Do Individual Investors Learn from Their Trading Experience?
Liang Peng, Gina Nicolosi, Ning Zhu
This paper investigates whether individual investors adjust their stock trading according to their stock selection abilities, which can be inferred from their trading history. Fixed-effect panel...
Time Variation of Liquidity in the Private Real Estate Market: An Empirical Investigation
Jim Clayton, Greg MacKinnon, Liang Peng
This paper characterizes the behavior of and evaluates competing explanations for time variation in private real estate market liquidity documented in Fisher et al. (2003). In the first, sellers base...
Least absolute deviations estimation for ARCH and GARCH models
Hall & Yao (2003) showed that, for ARCH/GARCH, i.e. autoregressive conditional heteroscedastic/generalised autoregressive conditional heteroscedastic, models with heavy-tailed errors, the...
Weighted least absolute deviations estimation for an AR(1) process with ARCH(1) errors
The weighted least absolute deviations estimator is studied for an AR(1) process with ARCH(1) errors ϵ-sub-t. Unlike for the quasi maximum likelihood estimator, the estimator's, limiting...
Nonparametric regression under dependent errors with infinite variance
ARMA, fractional ARIMA, heavy tail, least absolute deviation estimation, long memory, median, stable distribution, time series,
The Bias of the RSR Estimator and the Accuracy of Some Alternatives
William N. Goetzmann, Liang Peng
This paper analyzes the implications of cross-sectional heteroskedasticity in repeat sales regression (RSR). RSR estimators are essentially geometric averages of individual asset returns because of...
Venture Capital and Sequential Investments
Dirk Bergemann, Ulrich Hege, Liang Peng
We analyze sequential investment decisions in an innovative project that depend on the investor's information about the project failure risk and its potential final value. We consider the feedback...
The Bias of the RSR Estimator and the Accuracy of Some Alternatives
William N. Goetzmann, Liang Peng
This paper analyzes the implications of cross-sectional heteroskedasticity in the repeat sales regression (RSR). RSR estimators are essentially geometric averages of individual asset returns because...
GMM Repeat Sales Price Indices
Illiquid assets are widely spread within the economy but their indices are difficult to measure. This paper proposes a Generalized Method of Moment (GMM) repeat sales regression for estimating...
CLAUDIA KLÜPPELBERG, GABRIEL KUHN, LIANG PENG
In general, the risk of joint extreme outcomes in financial markets can be expressed as a function of the tail dependence function of a high-dimensional vector after standardizing marginals. Hence,...
Chover-type laws of the iterated logarithm for weighted sums
In this paper, a Chover-type law of the iterated logarithm is established for the weighted sums of independent and identically distributed random variables with a distribution in the domain of...
Asymptotic expansions of densities of sums of random vectors without third moment
Asymptotic expansions of densities of the normalized sums of random vectors with at least finite third moment have been studied extensively (Normal Approximation and Asymptotic expansions. Wiley, New...
Estimating the mean of a heavy tailed distribution
For the estimation of the mean of a heavy tailed distribution with tail index -[alpha]
Semi-parametric estimation of long-range dependence index in infinite variance time series
Suppose our data {Xn} come from the model Xt=[summation operator]j=0[infinity]cjZt-j, where {Zn} are i.i.d. with a symmetric distribution function which lies in the domain of normal attraction of a...
An adaptive optimal estimate of the tail index for MA(l) time series
For samples of random variables with a regularly varying tail estimating the tail index has received much attention recently. For the proof of asymptotic normality of the tail index estimator...
Empirical likelihood based confidence intervals for copulas
Chen, Jian, Peng, Liang, Zhao, Yichuan
Copula as an effective way of modeling dependence has become more or less a standard tool in risk management, and a wide range of applications of copula models appear in the literature of economics,...
Bootstrap approximation of tail dependence function
For estimating a rare event via the multivariate extreme value theory, the so-called tail dependence function has to be investigated (see [L. de Haan, J. de Ronde, Sea and wind: Multivariate extremes...
Parametric tail copula estimation and model testing
De Haan, Laurens, Neves, Cláudia, Peng, Liang
Parametric models for tail copulas are being used for modeling tail dependence and maximum likelihood estimation is employed to estimate unknown parameters. However, two important questions seem...
Nonparametric estimation of the dependence function for a multivariate extreme value distribution
Zhang, Dabao, Wells, Martin T., Peng, Liang
Understanding and modeling dependence structures for multivariate extreme values are of interest in a number of application areas. One of the well-known approaches is to investigate the Pickands...
Simple and efficient improvements of multivariate local linear regression
This paper studies improvements of multivariate local linear regression. Two intuitively appealing variance reduction techniques are proposed. They both yield estimators that retain the same...
Venture Capital and Sequential Investments
Dirk Bergemann, Ulrich Hege, Liang Peng
We present a dynamic model of venture capital financing, described as a sequential investment problem with uncertain outcome. Each venture has a critical, but unknown threshold beyond which it...
Goodness-of-fit test for tail copulas modeled by elliptical copulas
Modeling and estimating a tail copula play an important role in forecasting rare events. Due to their easy simulation, elliptical copulas have been employed in risk management. Recently, Klppelberg,...
Do individual investors learn from their trading experience?
Nicolosi, Gina, Peng, Liang, Zhu, Ning
After analyzing retail investors' stock trades for potential learning behavior, we present evidence that individual investors learn from their trading experience. Initially, we question whether...
The Subprime Crisis and House Price Appreciation
William N. Goetzmann, Liang Peng, Jacqueline Yen
This paper argues that econometric analysis of housing price indexes before 2006 generated forecasts of future long-term price growth and low estimated probabilities of extreme price decreases. These...
Effects of data dimension on empirical likelihood
Song Xi Chen, Liang Peng, Ying-Li Qin
We evaluate the effects of data dimension on the asymptotic normality of the empirical likelihood ratio for high-dimensional data under a general multivariate model. Data dimension and dependence...
Partial derivatives and confidence intervals of bivariate tail dependence functions
Bivariate extreme value theory was used to estimate a rare event (see de Haan and de Ronde [1998. Sea and wind: multivariate extremes at work. Extremes 1, 745]). This procedure involves estimating...
Venture Capital and Sequential Investments
Dirk Bergemann, Ulrich Hege, Liang Peng
We present a dynamic model of venture capital financing, described as a sequential investment problem with uncertain outcome. Each venture has a critical, but unknown threshold beyond which it cannot...