具有资本结构因子和交易成本的证券组合投资模型

在介绍经典的Harry Markowitz均值-方差投资组合模型的基础上,建立了含有资本结构因子和交易成本的证券组合最优化模型,在组合中不含有无风险证券和含有无风险证券的条件下,分别给出最优投资比例及有效边界,并讨论了资本结构因子与交易成本对有效边界的影响.     

摩擦市场中允许卖空的最优投资组合选择

资本市场的一个重要特征就是存在不确定因素,为了衡量其导致的风险,本文提出基于绝对偏差的新型函数,在一个存在摩擦的资本市场中构造均值-绝对离差(mean-absolute deviation,MAD)投资组合选择模型.该模型结构特殊性使其转化为线性规划问题,从而可利用单纯型法求解.实证分析比较了不同风险函数下投资组合的有效前沿,并验证了该方法的有效性.     

证券组合投资有效集及有效边界的确定的方法研究

证券组合投资有效集及有效边界是确定合理投资结构的关键。本文研究了证券组合投资风险函数及有效边界的凹性，提出了将求最小风险的干净人规划问题转化为线性规划问题，并根据其最优基及其灵敏度分析，分段确定有效边界的方法。这种方法使各段有效边界可直接由相应的数学表达式求得，计算量大大减少。     

资本结构作用下市场投资组合轨迹的研究

根据企业理财中投融资决策的互动机理 ,将资本结构与投资组合优化结合起来 ,在证券组合模型基础上 ,引入资本结构这一重要因素 ,研究了资本结构作用下市场投资组合点的轨迹 ,从而得出任一资本结构下所对应的市场投资组合     

模型不确定性条件下的Robust投资组合有效前沿与CAPM

本文提出了Robust投资组合有效前沿的概念,并研究了模型不确定性条件下的资本资产定价模型(CAPM)。研究发现,当市场上不存在无风险资产时,模型不确定性对风险资产投资比例的影响是非平等的,因此会导致投资组合的非分散化;而且此时的两基金分离定理以及零-βCAPM也不成立。但是当市场上存在无风险资产时,模型不确定性对风险资产投资比例的影响则是平等的,并且两基金分离定理仍然成立,因为任何Robust有效前沿组合都可以表示为市场组合与无风险资产的线性组合。而此时的CPAM仍然能够成立,只是在表达形式上增添了一个因子--不确定性因子;并且所有资产或资产组合的超额收益都可以分解为风险溢价与不确定性溢价两部分。     

商品金融化背景下商品期货的多样化收益研究

日益丰富的商品期货交易种类为传统投资组合的风险-收益结构提供了可行的改善路径,但同时商品期货的风险对冲功能也受到了商品金融化趋势的现实冲击。本文基于不同分布假设下的均值-方差张成检验方法探究引入商品期货改善传统投资组合的路径和程度,并在此基础上利用投资组合的样本期外滚动数据对商品期货的多样化收益进行多维绩效检验。研究发现：1.无论是否考虑资本市场现实中的交易制度约束,样本期内商品期货的加入都能够显著地改善传统投资组合选择的风险-收益结构;2.商品期货对投资组合有效边界的改善主要体现为风险分散效应,商品期货的加入不能为传统资产配置策略带来超额收益;3.引入商品期货能够有效地降低投资组合样本期外的标准差和尾部风险,高风险厌恶的投资者配置商品期货能够取得更高的等价性收益。本文研究结果表明,尽管大宗商品金融化趋势不可逆转,但将商品期货引入传统投资组合仍是推动中国资产配置策略优化升级的有效途径。     

代理证券相对有效性

分析了具有特定的期望收益率向量R与风险因子向量β截面关系的代理证券组合边界,进而研究了代理证券组合边界与有效证券组合边界的差异以及代理证券相对有效度。     

最优保险投资决策

2005年初我国对保险公司直接进入资本市场进行投资开始放开.如何选择最佳的投资策略就成为目前保险公司所面临的难题,而传统的投资模型的诸多不足使得它在实际应用中有很大局限性.讨论的模型克服了传统模型的不足.在该模型中,索赔是一个复合Poisson过程,保险公司可选择与投资期内的安全要求相一致的投资比例.应用最优控制原理求解模型得到了最优投资策略以及有效边界的解析形式,并讨论了承保收益和承保风险对投资策略与有效边界的影响.     

最优保险投资决策

2005年初我国对保险公司直接进入资本市场进行投资开始放开.如何选择最佳的投资策略就成为目前保险公司所面临的难题,而传统的投资模型的诸多不足使得它在实际应用中有很大局限性.讨论的模型克服了传统模型的不足.在该模型中,索赔是一个复合Poisson过程,保险公司可选择与投资期内的安全要求相一致的投资比例.应用最优控制原理求解模型得到了最优投资策略以及有效边界的解析形式,并讨论了承保收益和承保风险对投资策略与有效边界的影响.     

中国股票市场收益率的可预测性研究

构造了包括中国A股市场组合、行业组合、账面市值比组合和市值组合在内的31个投资组合,选取了8个预测因子(账面市值比、股利分配率、股息价格比、股息收益率、每股收益价格比、现金收益价格比、通货膨胀率、股票波动率),运用了可行拟广义最小二乘法对各因子对各投资组合收益率的可预测性进行了样本内和样本外检验.研究发现:1)中国股市收益率是可预测的,但是各投资组合收益率的可预测性在样本内、样本外、熊市和牛市均存在差异;2)绝大部分投资组合收益率的可预测性可由条件CAPM模型捕捉的时变系统风险溢价充分解释; 3)行业投资组合收益率的可预测性与行业集中度显著负相关,可由信息摩擦理论解释.     

A Theory of Macroprudential Policies in the Presence of Nominal Rigidities

We propose a theory of monetary policy and macroprudential interventions in financial markets. We focus on economies with nominal rigidities in goods and labor markets and subject to constraints on monetary policy, such as the zero lower bound or fixed exchange rates. We identify an aggregate demand externality that can be corrected by macroprudential interventions in financial markets. Ex post, the distribution of wealth across agents affects aggregate demand and output. Ex ante, however, these effects are not internalized in private financial decisions. We provide a simple formula for the required financial interventions that depends on a small number of measurable sufficient statistics. We also characterize optimal monetary policy. We extend our framework to incorporate pecuniary externalities, providing a unified approach to both externalities. Finally, we provide a number of applications which illustrate the relevance of our theory.     

The Nonparametric Identification of Treatment Effects in Duration Models

This paper analyzes the specification and identification of causal multivariate duration models. We focus on the case in which one duration concerns the point in time a treatment is initiated and we are interested in the effect of this treatment on some outcome duration. We define “no anticipation of treatment” and relate it to a common assumption in biostatistics. We show that (i) no anticipation and (ii) randomized treatment assignment can be imposed without restricting the observational data. We impose (i) but not (ii) and prove identification of models that impose some structure. We allow for dependent unobserved heterogeneity and we do not exploit exclusion restrictions on covariates. We provide results for both single‐spell and multiple‐spell data. The timing of events conveys useful information on the treatment effect.     

The Burden of Labour Costs in Mexico

Abstract. We analysed labour costs in Mexico and evaluated their impact in terms of firm performance. Using a new survey, we studied how firms chose to conduct a firing procedure (i.e. mandatory payment, negotiation, or legal dispute) and the actual costs derived from that decision. We found that firms that negotiate have, on average, lower costs. This may mean that workers subvaluate the legal benefits. Moreover, legal disputes may increase firing costs by 50 per cent. We contributed to the analysis of the impact of such costs on employment and found that, when firms negotiate or pay higher costs, this decreases the level of employment. We also analysed the impact of Social Benefits on employment using an industrial survey. We found that a 10 per cent increment in these benefits may have a negative long‐term impact of 9 per cent on the level of employment.     

Greasy Roads: The Impact of Bad Financial News on Road Traffic Accidents

We use evidence from a natural experiment in Greece to study the effect of the announcement of austerity measures on road traffic accidents (RTAs). We use daily RTA data from 2010 and 2011, during which a number of austerity measures were announced, including salary and pension cuts and an increase in direct and indirect taxes. We find that controlling for other factors potentially influencing RTAs, the number of RTAs increased significantly on the first two days following the announcements of austerity measures. We put forward some tentative suggestions for why this happens.     

Outsourcing vs. in-house production: a comparison of supply chain contracts with effort dependent demand

We analyze the effort and pricing decisions in a two facility supply chain in which one of the parties can exert costly effort to increase demand. We consider an outsourcing model in which the supplier makes the effort decision and an in-house production model in which the manufacturer decides on the effort level and we compare these two models with each other. We analyze and compare several contracts for decentralized supply chain models and we aim to find which contracts are best to use in different cases. We find the optimal contract parameters in each case and perform extensive computational testing to compare the efficiencies of these contracts. We also analyze the effect of the powers of the parties in the system and the effect of system parameters on the performances of the contracts and on the optimal values of the model variables such as price, effort and demand.     

The Effects of the Specialist Schools Education Policy on School and Post‐School Outcomes in England

We investigate the effects of the specialist schools policy, introduced in 1994 in England, on test scores and truancy for pupils during compulsory schooling. We also assess the effects on labour market status and post‐secondary test score performance. We use matching models and data from the Youth Cohort Surveys for pupils who left school in either 2002 or 2004. We find that the policy did raise test scores, as well as increase the probability of employment. The evidence on post‐secondary test scores is mixed insofar as the policy increased the number of A levels studied but reduced average points scores.     

The impact of R&D sources on new product development: Sources of funds and the diversity versus control of knowledge debate

We build on the knowledge-based view to study the relative impact of alternative R&D sources on innovation performance. We contrast two arguments that have created a debate in the literature: One is that diversity of knowledge is better for innovation, because the integration of a larger variety of knowledge helps create new products that can fulfill unmet customer needs; another is that control of knowledge is better, because the incentives and contextual system of the firm facilitate employees' experimentation, which supports the creation of new products. We provide one solution to this debate by arguing that the relative importance of diversity and control of knowledge on innovation depends on the sources of finance. Hence, we find that, in general, control of knowledge has a higher impact than diversity of knowledge on the sale of new products. We also find that alternative sources of finance moderate the relationships: internal funds strengthen the impact of R&D sources with more diversity of knowledge on the sale of new products, while external funds strengthen the impact of R&D sources with more control of knowledge on the sale of new products.     

Open-Innovation Effectiveness: When does the Macro Design of Alliance Portfolios Matter?

We determine the impact of the macro-design of a firm's alliance portfolio on its open-innovation effectiveness. Three elements of macro-design—international, technological, and partner diversity—are theorized to affect the breadth of knowledge sourcing, which is an important facet of open-innovation effectiveness. We test our hypotheses on a sample of 982 firm-years in the biotech industry. We find a U-shaped relationship between knowledge-sourcing breadth and international diversity. We also find that that technological diversity has no impact on knowledge-sourcing breadth. Furthermore, when seeking valuable knowledge, partner diversity is detrimental to knowledge-sourcing breadth.     

Learning How and Learning What: Effects of Tacit and Codified Knowledge on Performance Improvement Following Technology Adoption

This paper examines effects of tacit and codified knowledge on performance improvement as organizations gain experience with a new technology. We draw from knowledge management and learning curve research to predict improvement rate heterogeneity across organizations. We first note that the same technology can present opportunities for improvement along more than one dimension, such as efficiency and breadth of use. We compare improvement for two dimensions: one in which the acquisition of codified knowledge leads to improvement and another in which improvement requires tacit knowledge. We hypothesize that improvement rates across organizations will be more heterogeneous for dimensions of performance that rely on tacit knowledge than for those that rely on codified knowledge (H1), and that group membership stability predicts improvement rates for dimensions relying on tacit knowledge (H2). We further hypothesize that when performance relies on codified knowledge, later adopters should improve more quickly than earlier adopters (H3). All three hypotheses are supported in a study of 15 hospitals learning to use a new surgical technology. Implications for theory and practice are discussed.     

Epistemic Uncertainty in the Ranking and Categorization of Probabilistic Safety Assessment Model Elements: Issues and Findings

In this work, we study the effect of epistemic uncertainty in the ranking and categorization of elements of probabilistic safety assessment (PSA) models. We show that, while in a deterministic setting a PSA element belongs to a given category univocally, in the presence of epistemic uncertainty, a PSA element belongs to a given category only with a certain probability. We propose an approach to estimate these probabilities, showing that their knowledge allows to appreciate " the sensitivity of component categorizations to uncertainties in the parameter values " (U.S. NRC Regulatory Guide 1.174). We investigate the meaning and utilization of an assignment method based on the expected value of importance measures. We discuss the problem of evaluating changes in quality assurance, maintenance activities prioritization, etc. in the presence of epistemic uncertainty. We show that the inclusion of epistemic uncertainly in the evaluation makes it necessary to evaluate changes through their effect on PSA model parameters. We propose a categorization of parameters based on the Fussell-Vesely and differential importance (DIM) measures. In addition, issues in the calculation of the expected value of the joint importance measure are present when evaluating changes affecting groups of components. We illustrate that the problem can be solved using DIM. A numerical application to a case study concludes the work.