Robust block bootstrap panel predictability tests*

This article develops two block bootstrap-based panel predictability test procedures that are valid under very general conditions. Some of the allowable features include cross-sectional dependence, heterogeneous predictive slopes, persistent predictors, and complex error dynamics, including cross-unit endogeneity. While the first test procedure tests if there is any predictability at all, the second procedure determines the units for which predictability holds in case of a rejection by the first. A weak unit root framework is adopted to allow persistent predictors, and a novel theory is developed to establish asymptotic validity of the proposed bootstrap. Simulations are used to evaluate the performance of our tests in small samples, and their implementation is illustrated through an empirical application to stock returns.     

Tail asymptotic of discounted aggregate claims with compound dependence under risky investment

This paper considers the tail asymptotic of discounted aggregate claims with compound dependence under risky investment. The price of risky investment is modeled by a geometric Lévy process, while claims are modeled by a one-sided linear process whose innovations further obeying a so-called upper tail asymptotic independence. When the innovations are heavy tailed, we derive some uniform asymptotic formulas. The results show that the linear dependence has significant impact on the tail asymptotic of discounted aggregate claims but the upper tail asymptotic independence is negligible.     

基于协高阶矩视角的沪港股市风险传染分析

金融风险传染(financial risk contagion)不仅是资产配置和套期保值决策中应该考虑的一个重要因素,而且直接关系着一国乃至全球金融体系的安全与稳定.运用协高阶矩(协偏度、协波动率、协峰度等)风险传染判定方法,实证检验了沪港通实施前后上海和香港两地股票市场间的风险传染状况.研究结果表明,沪港通政策实施后,上海股市向香港股市的第一类协偏度(均值→波动率)、协波动率、经调整的相关系数、协峰度等的风险传染统计量值依次变大,同样依据风险传染统计量值的大小,香港股市对上海股市的风险传染途径依次为协四阶矩(协波动率、协峰度)、第一类协偏度和经调整的相关系数,协高阶矩成为沪港股市间双向风险传染的主要途径;因资本净流动数额和投资者教育等因素,上海股市对香港市场的风险传染效应更强.     

基于Hawkes因子模型的股价共同跳跃研究

本文首先比较了三种目前主流的共跳检验方法：基于LM检验的共跳检验、BLT共跳检验和FHLL共跳检验，结果表明，三种方法在识别共跳数量上差距明显，但三者结果的重合部分基本属于市场暴涨暴跌行情，说明共跳识别对市场剧烈波动的聚集性较为敏感。基于跳跃、共跳存在的聚集性问题，本文将Hawkes过程引入跳跃和共跳的研究，构建了基于Hawkes过程的因子模型，结果显示，基于Hawkes因子模型的MJ统计量、CJ统计量和实证数据的拟合程度较好，表明因子模型能够更好地描述跳跃和共跳的聚集性。     

企业管理中人的激励问题探讨

人力资源已经成为企业发展的最关键因素。激励是否科学,直接关系到人力资源运用的好坏。目前,企业激励机制中还存在一些问题:如激励机制缺乏针对性和无差别化,领导层与下属缺乏沟通,激励方式单一,长期激励不足等。企业管理者要采用人性化的管理手段,激励要有针对性和差别性。企业对核心员工还可选择股权激励的方法。     

关于杜尔伯特蒙古族自治县农转牧情况及存在问题的调研报告

本文介绍了黑龙江省杜尔伯特蒙古族自治县农转牧发展情况、存在的问题及对策。     

利益冲突、声誉激励与股价发现有效性

构建了分析师两期荐股模型,解析分析师和投资者的利益冲突、分析师类型不确定性和基本面的不对称信息三者相互作用并影响股价发现有效性的作用机制． 分析结果表明: 关联分析师方的“激励扭曲效应”源于其受利益相关方干扰后进行策略性荐股谋取私利; 独立分析师方的“声誉激励效应”源于其受远期市场上“身份识别”困扰等利他动机进行策略性荐股; 激励扭曲效应、声誉激励效应与价值投资者的策略性解读偏差共同导致分析师信息发现加工效率受损和股票市场有效性下降; 这一作用机制并不依赖于非策略性市场参与者假设; 常见的分级荐股方式有助于约束分析师的声誉激励并降低跨期效率损失． 这些结论为完善分析师薪酬考核机制、强化特定时点信息披露、分析师声誉市场培育、建立长效追踪制度和引入适当的长期责任承担制度提供了理论支撑．     

基于顾客退货的闭环供应链运作绩效研究

为了探讨顾客退货情境下的供应链运作绩效问题,采用动态建模方法对产品正向物流和退货逆向物流为一体的闭环供应链系统进行研究,构建生产-分销-市场-退货-再处理-再销售等多个环节的系统运作模型.通过计算机仿真方法模拟不同情境下系统的动态行为规律,着重从产品生命周期视角探讨顾客退货对供应链系统运作绩效的影响;以系统总利润为指标,评估退货率、退货处理时间、产品价格衰减等因素的影响效应.研究结果表明,无论是对长生命周期产品还是短生命周期产品,退货率和产品价格衰减均是影响系统绩效的关键因素,高退货率和高价格衰减会显著削弱供应链整体的盈利能力,导致系统总利润大幅下滑.对于陷入高退货、高价格衰减困境的企业,设定相对较短的退货期限可以在一定程度上改善盈利情况;此外,当加快退货处理速度不会引起额外的成本投资时,快速的退货处理方式对企业更为有益,特别是对短生命周期产品而言,缩短退货环节的处理时间具有非常显著的经济价值.     

Portmanteau tests for linearity of stationary time series

This article considers the problem of testing for linearity of stationary time series. Portmanteau tests are discussed which are based on generalized correlations of residuals from a linear model (that is, autocorrelations and cross-correlations of different powers of the residuals). The finite-sample properties of the tests are assessed by means of Monte Carlo experiments. The tests are applied to 100 time series of stock returns.     

A semi-parametric method for estimating the beta coefficients of the hidden two-sided asset return jumps

ABSTRACT

We introduce a new methodology for estimating the parameters of a two-sided jump model, which aims at decomposing the daily stock return evolution into (unobservable) positive and negative jumps as well as Brownian noise. The parameters of interest are the jump beta coefficients which measure the influence of the market jumps on the stock returns, and are latent components. For this purpose, at first we use the Variance Gamma (VG) distribution which is frequently used in modeling financial time series and leads to the revelation of the hidden market jumps' distributions. Then, our method is based on the central moments of the stock returns for estimating the parameters of the model. It is proved that the proposed method provides always a solution in terms of the jump beta coefficients. We thus achieve a semi-parametric fit to the empirical data. The methodology itself serves as a criterion to test the fit of any sets of parameters to the empirical returns. The analysis is applied to NASDAQ and Google returns during the 2006–2008 period.