浅析我国推出股指期货的功能与作用

股指期货作为一种新型的金融衍生工具即将在我国推出,必将成为我国证券市场发展的一个里程碑.文中介绍了股指期货的概念及特点,并分析了股指期货的功能及其作用.     

The econometrics of auctions with asymmetric anonymous bidders

We consider standard auction models when bidders’ identities are not-or are only partially-observed by the econometrician. We first adapt the definition of identifiability to a framework with anonymous bids and explore the extent to which anonymity reduces the possibility of identifying private value auction models. Second, in the asymmetric independent private value model which is nonparametrically identified, we generalize Guerre, Perrigne and Vuong’s estimation procedure [Optimal nonparametric estimation of first-price auctions, Econometrica 68 (2000) 525-574] and consider the asymptotic properties of our multi-step kernel-based estimator. Monte Carlo simulations illustrate the practical relevance of our estimation procedure in small data sets.     

Are there common values in first-price auctions? A tail-index nonparametric test

We develop a consistent nonparametric test of common values in first-price auctions and apply it to British Columbia Timber Sales data. The test is based on the behavior of the CDF of bids near the reserve price. We show that the curvature of the CDF is drastically different under private values (PV) and common values (CV). We then show that the problem of discriminating between PV and CV is equivalent to estimating the lower tail index of the bid distribution. Our approach admits unobserved auction heterogeneity of an arbitrary form. We develop a Hill (1975)-type tail index estimator and find the presence of common values in BC Timber Sales.     

Identification of first-price auctions with non-separable unobserved heterogeneity

We propose a novel methodology for identification of first-price auctions, when bidders’ private valuations are independent conditional on one-dimensional unobserved heterogeneity. We extend the existing literature ( and ) by allowing the unobserved heterogeneity to be non-separable from bidders’ valuations. Our central identifying assumption is that the distribution of bidder values is increasing in the state. When the state-space is finite, such monotonicity implies the full-rank condition needed for identification. Further, we extend our approach to the conditionally independent private values model of Li et al. (2000), as well as to unobserved heterogeneity settings in which the implicit reserve price or the cost of bidding varies across auctions.     

The method of simulated quantiles

We introduce the Method of Simulated Quantiles, or MSQ, an indirect inference method based on quantile matching that is useful for situations where the density function does not have a closed form and/or moments do not exist. Functions of theoretical quantiles, which depend on the parameters of the assumed probability law, are matched with the sample counterparts, which depend on the observations. Since the theoretical quantiles may not be available analytically, the optimization is based on simulations. We illustrate the method with the estimation of α$\alpha$-stable distributions. A thorough Monte Carlo study and an illustration to 22 financial indexes show the usefulness of MSQ.     

Nonparametric estimation and inference about the overlap of two distributions

This paper develops methodology for nonparametric estimation of a measure of the overlap of two distributions based on kernel estimation techniques. This quantity has been proposed as a measure of economic polarization between two groups, Anderson (2004) and Anderson et al. (2010). In ecology it has been used to measure the overlap of species. We give the asymptotic distribution theory of our estimator, which in some cases of practical relevance is nonstandard due to a boundary value problem. We also propose a method for conducting inference based on estimation of unknown quantities in the limiting distribution and show that our method yields consistent inference in all cases we consider. We investigate the finite sample properties of our methods by simulation methods. We give an application to the study of polarization within China in recent years using household survey data from two provinces taken in 1987 and 2001. We find a big increase in polarization between 1987 and 2001 according to monetary outcomes but less change in terms of living space.     

Pseudo-likelihood estimation and bootstrap inference for structural discrete Markov decision models

This paper analyzes the higher-order properties of the estimators based on the nested pseudo-likelihood (NPL) algorithm and the practical implementation of such estimators for parametric discrete Markov decision models. We derive the rate at which the NPL algorithm converges to the MLE and provide a theoretical explanation for the simulation results in Aguirregabiria and Mira [Aguirregabiria, V., Mira, P., 2002. Swapping the nested fixed point algorithm: A class of estimators for discrete Markov decision models. Econometrica 70, 1519–1543], in which iterating the NPL algorithm improves the accuracy of the estimator. We then propose a new NPL algorithm that can achieve quadratic convergence without fully solving the fixed point problem in every iteration and apply our estimation procedure to a finite mixture model. We also develop one-step NPL bootstrap procedures for discrete Markov decision models. The Monte Carlo simulation evidence based on a machine replacement model of Rust [Rust, J., 1987. Optimal replacement of GMC bus engines: An empirical model of Harold Zurcher. Econometrica 55, 999–1033] shows that the proposed one-step bootstrap test statistics and confidence intervals improve upon the first order asymptotics even with a relatively small number of iterations.     

Semi-nonparametric estimation of independently and identically repeated first-price auctions via an integrated simulated moments method

In this paper we propose to estimate the value distribution of independently and identically repeated first-price auctions directly via a semi-nonparametric integrated simulated moments sieve approach. Given a candidate value distribution function in a sieve space, we simulate bids according to the equilibrium bid function involved. We take the difference of the empirical characteristic functions of the actual and simulated bids as the moment function. The objective function is then the integral of the squared moment function over an interval. Minimizing this integral to the distribution functions in the sieve space involved and letting the sieve order increase to infinity with the sample size then yields a uniformly consistent semi-nonparametric estimator of the actual value distribution. Also, we propose an integrated moment test for the validity of the first-price auction model, and an data-driven method for the choice of the sieve order. Finally, we conduct a few numerical experiments to check the performance of our approach.     

Edgeworth expansions and normalizing transforms for inequality measures

Finite sample distributions of studentized inequality measures differ substantially from their asymptotic normal distribution in terms of location and skewness. We study these aspects formally by deriving the second-order expansion of the first and third cumulant of the studentized inequality measure. We state distribution-free expressions for the bias and skewness coefficients. In the second part we improve over first-order theory by deriving Edgeworth expansions and normalizing transforms. These normalizing transforms are designed to eliminate the second-order term in the distributional expansion of the studentized transform and converge to the Gaussian limit at rate O(n⁻¹)$O\left(n^{-1}\right)$. This leads to improved confidence intervals and applying a subsequent bootstrap leads to a further improvement to order O(n^−3/2)$O\left(n^{-3/2}\right)$. We illustrate our procedure with an application to regional inequality measurement in Côte d’Ivoire.     

The bull and bear market model of Huang and Day: Some extensions and new results

We develop a financial market model with interacting chartists and fundamentalists that embeds the famous bull and bear market model of Huang and Day as a special case. Their model is given by a one-dimensional continuous piecewise-linear map. Our model, on the other hand, is more flexible and is represented by a one-dimensional discontinuous piecewise-linear map. Nevertheless, we are able to provide a more or less complete analytical treatment of the model dynamics by characterizing its possible outcomes in parameter space. In addition, we show that quite different scenarios can trigger real-world phenomena such as bull and bear market dynamics and excess volatility.     

Non-parametric estimation of sequential english auctions

I propose an empirical strategy to identify and to estimate non-parametrically the distribution and the density of latent valuations from the winning bids at sequential oral, ascending-price (hereafter English) auctions within the independent private-values paradigm. I evaluate the asymptotic and finite-sample properties of my approach, and the estimation strategy is applied to daily data from a fish auction held in Grenaa, Denmark, between January 2, 2000 and March 31, 2004.     

Semiparametric identification and estimation in multi-object,English auctions

Within the independent private-values paradigm, we derive the data-generating process of winning bids for two different objects sold sequentially at English auction, assuming the valuations across objects for a particular bidder are potentially dependent. We demonstrate that, within the Archimedean family of copulas, the model is identified using only observed winning bids, and then propose a semiparametric estimation strategy to recover the joint distribution of valuations. We implement our methods using data from fish auctions held in Denmark and estimate whether bundling is expected-revenue enhancing.     

Risk aversion and asymmetry in procurement auctions: Identification,estimation and application to construction procurements

This article studies a model of asymmetric risk averse bidding within the independent private value paradigm. The inherent asymmetry in cost and risk aversion imposes an original restriction on the observed bid data, an exact equality which leads to the model semiparametric identification and estimation. The unobserved arguments of this equality need to be simulated in order to estimate the bidders’ Constant Relative Risk Aversion or Constant Absolute Risk Aversion parameters and their heterogeneous cost distributions. In the Los Angeles City Hall construction contracts offered between 1994 and 2003, the model and methodology help reveal that financial asymmetries affect the firms’ cost distribution, while experience influences their degree of risk aversion.