Two-stage stationary bootstrapping for bivariate average realized volatility matrix under market microstructure noise and asynchronicity

Under the two important modern financial market features of noise and non-synchronicity for multiple assets, for consistent estimators of the integrated covariations, we adopt the two-time scale average realized volatility matrix (ARVM) which is a matrix extension of the two-time scale realized volatilities of Zhang et al. (2005). An asymptotic normal theory is provided for the two-time scale ARVM and resulting realized covariations. The asymptotic normality is not directly applicable in practice to construct statistical methods owning to nuisance parameters. To bypass the nuisance parameter problem, two-stage stationary bootstrapping is proposed. We establish consistencies of the bootstrap distributions, and construct confidence intervals and hypothesis tests for the integrated covariance, regression coefficient and correlation coefficient. The validity of the stationary bootstrap for the high frequency heterogeneous returns is proved by showing that there exist parameters of the stationary bootstrap blocks so that the bootstrap consistencies hold. The proposed bootstrap methods extend the i.i.d. bootstrapping methods for realized covariations by Dovonon et al. (2013), that are confined to synchronous noise-free sampling. For high frequency noisy asynchronous samples, a Monte-Carlo experiment shows better finite sample performances of the proposed stationary bootstrap methods based on the two-time scale ARVM estimator than the wild blocks of blocks bootstrap methods of Hounyo (2017), based on pre-averaged truncated estimator.     

Empirical likelihood block bootstrapping

Monte Carlo evidence has made it clear that asymptotic tests based on generalized method of moments (GMM) estimation have disappointing size. The problem is exacerbated when the moment conditions are serially correlated. Several block bootstrap techniques have been proposed to correct the problem, including Hall and Horowitz (1996) and Inoue and Shintani (2006). We propose an empirical likelihood block bootstrap procedure to improve inference where models are characterized by nonlinear moment conditions that are serially correlated of possibly infinite order. Combining the ideas of Kitamura (1997) and Brown and Newey (2002), the parameters of a model are initially estimated by GMM which are then used to compute the empirical likelihood probability weights of the blocks of moment conditions. The probability weights serve as the multinomial distribution used in resampling. The first-order asymptotic validity of the proposed procedure is proven, and a series of Monte Carlo experiments show it may improve test sizes over conventional block bootstrapping.     

Stationary bootstrapping for common mean change detection in cross-sectionally dependent panels

Stationary bootstrapping is applied to a CUSUM test for common mean break detection in cross-sectionally correlated panel data. Asymptotic null distribution of the bootstrapped test is derived, which is the same as that of the original CUSUM test depending on cross-sectional correlation parameter. A bootstrap test using the CUSUM test with bootstrap critical values is proposed and its asymptotic validity is proved. Finite sample Monte-Carlo simulation shows that the proposed test has reasonable size while other existing tests have severe size distortion under cross-section correlation. The simulation also shows good power performance of the proposed test against non-cancelling mean changes. The simulation also shows that the theoretically justified stationary bootstrapping CUSUM test has comparable size and power relative to other, theoretically unjustified, moving block or tapered block bootstrapping CUSUM tests.     

Bootstrapping the process of model selection: AN econometric example

If a researcher has mined the data (i.e. selected an empirical model based on a series of trial estimates), inferences based on the final set of results are in general incorrect. This note treats the entire data mining process as an estimator and shows how a bootstrapping technique may improve the quality of inference. The method is applied to an empirical example on the deterrent effects of capital punishment.     

Subsampling vector autoregressive tests of linear constraints

This paper studies subsampling VAR tests of linear constraints as a way of finding approximations of their finite sample distributions that are valid regardless of the stochastic nature of the data generating processes for the tests. In computing the VAR tests with subsamples (i.e., blocks of consecutive time series), both the tests of the original form and the tests with the subsample OLS coefficient estimates centered at the full-sample estimates are used. Subsampling using the latter is called centered subsampling in this paper. It is shown that the subsamplings provide asymptotic distributions that are equivalent to the asymptotic distributions of the VAR tests. In addition, the tests using critical values from the subsamplings are shown to be consistent. The subsampling methods are applied to testing for causality. To choose the block sizes for subsample causality tests, the minimum volatility method, a new simulation-based calibration rule and a bootstrap-based calibration rule are used. Simulation results in this paper indicate that the centered subsampling using the simulation-based calibration rule for the block size is quite promising. It delivers stable empirical size and reasonably high-powered causality tests. Moreover, when the causality test has a chi-square distribution in the limit, the test using critical values from the centered subsampling has better size properties than the one using chi-square critical values. The centered subsampling using the bootstrap-based calibration rule for the block size also works well, but it is slightly inferior to that using the simulation-based calibration rule.     

Some Problems with the Ferrier/Hirschberg Bootstrap Idea

This paper demonstrates that the bootstrap procedure suggested by Ferrier and Hirschberg (1997) gives inconsistent estimates. A very simple example is given to illustrate the statistical issues underlying nonparametric efficiency measurement and the problems with the Ferrier/Hirschberg approach, and may serve as a primer on bootstrapping in nonparametric models of production processes.     

Premiums paid in block transactions

We document the premiums over market price paid in negotiated third-party purchases and negotiated repurchases of blocks of common stock. The blocks range from 1.5% to 44% of outstanding shares and the average premium is approximately 10%. There is no significant difference between the premiums paid by managers in block repurchases and the premiums paid by outsiders in block purchases. Repurchasing managers pay a premium that corresponds to the market value of control associated with the block.     

Typical lots for detached houses in residential blocks and lot shape analysis

The notion of shape distance between lots is the basis for further development of the economics of dealing with lot shapes in real estate. The distance between two lots is defined as the relative area of the set difference of two lots. Using this notion, a method for identifying typical lots in a residential block based on the shape distance matrix among all the lots in the block is proposed. The method is applied to 20 blocks in the Setagaya ward in Tokyo. Typical lots tend to be rectangular-type lots even in irregularly shaped blocks. This suggests that consumers prefer rectangular shapes when choosing residential lots. Moreover, rectangular blocks tend to contain typical rectangular lots that have a depth about half as long as the shorter edge of the block and two variations of width. This suggests that some lots were previously subdivided in half.     

黄河中游劣质粘土的激活研究

文章中尝试用磷酸对黄河中游劣质粘土进行激活处理,经过压实成型的试块,其强度较原土有很大提高,并且成型的试样具有了一定的耐水性。经过激活处理的粘土做成的石灰土试块较普通石灰土抗压强度有很大提高。红外及微观分析表明,磷酸能够改变土粒表面的羟基团,并且磷酸与土中的碳酸盐等生成肉丝状的磷酸钙晶体,分布在土粒的周围,胶结土壤。     

Financial bootstrapping and venture development in the software industry

Access to finance has been identified as a significant constraint on the development of technology-based businesses. Although important, institutional venture capital and business angel finance are used by only a small proportion of new and growing ventures. The role of bootstrapping – defined here as access to resources not owned or controlled by the entrepreneur – has been largely overlooked in studies of small firm financing. This paper redresses this omission by analysing the role and importance of bootstrapping in product development and business development in the independently-owned software industry. Results from two regions of the UK – Northern Ireland and South East England – are compared with equivalent data from the USA (Massachusetts). Overall, bootstrapping techniques are less extensively used in the Northern Ireland industry than in South East England, and in both regions bootstrapping is less common than in Massachusetts. This may account for the smaller employment size, growth profile and stronger service/consulting orientation of these firms. Moreover, there appear to be considerable variations in the use of bootstrapping. Larger firms tend to make more use of bootstrapping for product development, and consider it more important than do smaller firms, who more highly value business development-related bootstrapping. Small firms are also more likely to use and value cost-reducing bootstrapping techniques, whereas larger firms make more use of the exploitation of value-chain based relationships.     

Density Forecasts With Midas Models

We propose a parametric block wild bootstrap approach to compute density forecasts for various types of mixed‐data sampling (MIDAS) regressions. First, Monte Carlo simulations show that predictive densities for the various MIDAS models derived from the block wild bootstrap approach are more accurate in terms of coverage rates than predictive densities derived from either a residual‐based bootstrap approach or by drawing errors from a normal distribution. This result holds whether the data‐generating errors are normally independently distributed, serially correlated, heteroskedastic or a mixture of normal distributions. Second, we evaluate density forecasts for quarterly US real output growth in an empirical exercise, exploiting information from typical monthly and weekly series. We show that the block wild bootstrapping approach, applied to the various MIDAS regressions, produces predictive densities for US real output growth that are well calibrated. Moreover, relative accuracy, measured in terms of the logarithmic score, improves for the various MIDAS specifications as more information becomes available. Copyright © 2016 John Wiley & Sons, Ltd.     

Nonlinear Structural Equation Models with the Theory of Planned Behavior: Comparison of Multiple Group and Latent Product Term Analyses

Nonlinear relationships in structural equation analysis became moreinteresting for applied researchers since the implementation of nonlinearconstraints in software programs (i.e., LISREL). This article provides acomprehensive application of the expectancy × value part of the Theory of Planned Behavior (Ajzen, 1991) including interactions of latent variables.The main purpose of the study is to overcome limitations of similarprevious analyses of Baumgartner and Bagozzi (1995) and Yang Jonsson (1997,1998) with an empirical example from representative survey data. Nonlinearrelationships of the theories' constructs (Attitude toward the behavior, subjectivenorm and perceived behavioral control) are analyzed one upon another withmultiple group comparisons and latent interaction models. Results confirmthe strategy to use multiple group techniques for preliminary analyses(i.e., detection of an interaction effect). With latent interaction models thestrength and the significance of the interaction is estimated under controlfor random measurement error. Parameters, standard errors, andgoodness-of-fit statistics are compared between three estimationtechniques (ML, GLS and WLS). Multiple group analyses and latentinteraction modeling detect a significant interaction for perceivedbehavioral control but not for attitude toward the behavior and subjective norm. Variations of the estimators of the perceived behavioral controlsubmodel is proved by bootstrapping. Further model improvements andalternative model techniques are discussed in the final chapter.     

复合型居住街区规划研究——以台州为例

对居住小区规划模式进行分析,提出了复合型居住街区规划,结合台州实例论述复合型居住街区特征,进行了居住街区作为一个社会、经济、环境复合体的研究,探讨其可持续发展的意义。     

Optimal extended complete block designs for dependent observations

Optimal designs under general dependence structures are usually difficult to specify theoretically or find algorithmically. However, they can sometimes be found for a specific dependence structure and a particular parameter value. In this paper, a class of generalized binary block designs with t treatments and b blocks of size k>t is considered. Each block consists of h consecutive complete blocks and, at the end, an incomplete block of size k−ht (if k > ht). For a suitable number of blocks, a universally optimal design is found for a first-order stationary autoregressive process with positive correlations. Optimal generalized binary designs and balanced block designs are also considered. Some constructions for a universally optimal design are described. A negative dependence parameter, and some other dependence structures, are also considered.     

A neural network based reputation bootstrapping approach for service selection

With the concept of service-oriented computing becoming widely accepted in enterprise application integration, more and more computing resources are encapsulated as services and published online. Reputation mechanism has been studied to establish trust on prior unknown services. One of the limitations of current reputation mechanisms is that they cannot assess the reputation of newly deployed services as no record of their previous behaviours exists. Most of the current bootstrapping approaches merely assign default reputation values to newcomers. However, by this kind of methods, either newcomers or existing services will be favoured. In this paper, we present a novel reputation bootstrapping approach, where correlations between features and performance of existing services are learned through an artificial neural network (ANN) and they are then generalised to establish a tentative reputation when evaluating new and unknown services. Reputations of services published previously by the same provider are also incorporated for reputation bootstrapping if available. The proposed reputation bootstrapping approach is seamlessly embedded into an existing reputation model and implemented in the extended service-oriented architecture. Empirical studies of the proposed approach are shown at last.     

Polygonal designs with blocks of size k≤10

The use of polygonal designs is motivated by the desire to avoid the selection of contiguous units in a sample from an ordered finite population. However very little is known about polygonal designs that have block size 5 or more. We present new polygonal designs with blocks of sizes 5 through 10, including the first designs with block sizes 9 and 10. For block sizes 5 through 7, we identify, with one possible exception, all values for the number of varieties for which a polygonal design exists. Received January 2001     

城市中心历史街区多维度保护模式构建

历史街区是一个城市地方性文化集中展现的区域,随着经济的发展,城市建设与历史街区保护之间的矛盾日趋尖锐,历史街区保护是城市发展过程中需要解决的重要问题。文章在对城市中心历史街区现实状况分析的基础上,指出城市中心历史街区在土地利用、传统商业发展、地方性文化保护、街区保护和修缮方面存在的问题。依据文化遗产保护的真实性和完整性原则,提出了历史街区空间维度、时间维度、文化维度(TSC)"三维一体"的多维保护模式。以昆明市文明街历史街区为研究实例,将历史街区多维度的保护模式与文明街历史街区的保护实践相融合,探索文明街历史街区整体、活态保护的新思路和新方式。     

Optimality of block designs with variable block sizes and random block effects

We consider the simple block model with random block effects, the block effects having variance _b ² =²;, with ² the variance of the errors. It is assumed that the experimenter can vary the sizes of the blocks. The universal optimality of certain designs for all over all designs with the same number of blocks and the same number of observations is shown. It is of interest to note that if Balanced Incomplete Block Designs compete, then they perform equally well for =0 and for =, i.e. in the one way classification model and in the simple block model with fixed block effects, but they perform worse for every (0, ).The result is, however, theoretical in nature. It treats a situation which is not very likely to happen in practice. The interest lies in the fact that it provides a counterexample to a conjecture on optimality of designs in mixed models.     

城市街区空间结构低碳化的理论模型

通过分析城市空间结构的内涵,认为"街区"是居民日常出行最为集中的场所,也是形成城市空间结构的基本单元。认为应该从居民的出行需求出发,通过充分分析街区内各功能用地的可达性需求,来发现出行需求内向型的街区用地结构,并以此为指导,建设功能混合型的城市街区,使各功能用地与空间可达性最大效用耦合,从而减少通勤产生的碳排放。     

A note on connectedness of block designs

Summary We give a simple proof for the well known result that a block design (for an additive, fixed effects block model withv treatments inb blocks) is connected iff its ℰ-matrix has rankv-1.