套期保值与企业价值的文献回顾

论文对套期保值与企业价值的理论和实证研究文献作了系统的回顾,全面地归纳和总结了企业套期保值的动因,套期保值同企业价值的关系以及企业利用衍生工具进行套期保值的各种机制。大部分的实证结果表明,套期保值在不同程度上提高了企业的价值。论文的贡献在于对已有的研究方法进行了稳健性分析,并提出进一步的研究方向,包括扩展研究企业套期保值的工具和套期保值的程度;不同套期保值机制及其组合;对实证模型的变量及其关系做进一步的研究和分析;以及将套期保值的成本和损益作为实证模型中的控制变量,以使模型更完整。     

略论中国经济的流动性过剩——基于经济学视角

在总结了目前理论界对流动性过剩的观点的基础上,分析了中国经济的流动性过剩的现状,并从货币的供给与需求的角度分析了其产生的根源,最后提出了治理中国经济流动性过剩问题的对策与建议。     

森林资源资产组合随机控制模型及决策

在界定了森林生态资产与森林资源资产组合概念的基础上,构建和模拟了基于随机控制理论的森林资源资产组合模型,为森林经营管理者提出了相应的结论和建议:森林经营管理者可以根据最优采伐量与木材价格、补偿价格、成本系数、税率、贴现率、生长率等参数之间的关系,获得在市场经济变动条件下的最优森林资产组合,以保证森林资产净收益的稳定增长。     

Transport infrastructure equities in mixed-asset portfolios: estimating risk with a Garch-Copula CVaR model

Transport infrastructure is an important subsector within infrastructure, but knowledge of its equities in terms of risk-return characteristics and contribution to portfolio performance is still limited. This study assesses the subsector individually and in a multi-asset, index-based portfolio. In doing so, we apply a t-Copula-based Conditional Value-at-Risk model to simulate risk and returns. Our findings reveal that the subsector has a relatively low dependency on other equities, performs like other alternative asset classes such as general real estate, and does not grant significant risk diversification benefits for mainstream institutional investors such as pension funds. Investors aiming for higher target returns may however assign substantial weights to transport infrastructure, supporting our conjecture that it does not share the same asset class characteristics as general infrastructure. By contrasting Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) scores for both the mean-variance framework and the t-Copula simulation, we further document the limitations of traditional VaR approaches. Hence, this study’s results support the use of risk assessment tools that incorporate non-normal distributions to represent multivariate dependence structures.     

Does it really pay to do better? Exploring the financial effects of changes in CSR ratings

Previous literature on the link between corporate social responsibility (CSR) and financial performance has focused mainly on the financial implications of a firm’s level of CSR without considering the potential effects on financial performance of variations in CSR rating. We try to fill this gap by studying whether variations in a firm’s CSR rating affect systematic risk, firm value, and portfolio performance. First, our results show that an increase in firms’ CSR efforts, as reflected by an increase in their CSR ratings, significantly reduces systematic risk. Second, a positive variation in CSR ratings significantly improves firm value. Finally, from a portfolio perspective, a strategy that consists of buying stocks that have experienced a CSR ratings increase and selling stocks that have experienced a CSR ratings decrease (or remain stable) leads to lower financial performance. Taken together, our findings provide new evidence and financial implications for firms and portfolio managers.     

Bayesian forecasting and portfolio decisions using dynamic dependent sparse factor models

We extend the recently introduced latent threshold dynamic models to include dependencies among the dynamic latent factors which underlie multivariate volatility. With an ability to induce time-varying sparsity in factor loadings, these models now also allow time-varying correlations among factors, which may be exploited in order to improve volatility forecasts. We couple multi-period, out-of-sample forecasting with portfolio analysis using standard and novel benchmark neutral portfolios. Detailed studies of stock index and FX time series include: multi-period, out-of-sample forecasting, statistical model comparisons, and portfolio performance testing using raw returns, risk-adjusted returns and portfolio volatility. We find uniform improvements on all measures relative to standard dynamic factor models. This is due to the parsimony of latent threshold models and their ability to exploit between-factor correlations so as to improve the characterization and prediction of volatility. These advances will be of interest to financial analysts, investors and practitioners, as well as to modeling researchers.     

基于偏度的多期证券投资组合模型研究

在考虑资产收益率分布中正的偏度水平前提下,以风险价值VaR为约束条件,并引入非线性交易费用、税收等市场摩擦因素,建立以累积偏度最大为目标函数的多期投资组合优化模型,用罚函数法和PSO算法结合求解此模型,并给出实证分析。考虑到在买卖资产风险时交易费用等对投资收益的影响,投资者应该在每一期都对其资产组合进行调整分析,确保在每一期的开始都建立起符合需要的最优资产组合,这对投资者的连续投资行为具有一定的指导意义。     

The Demand for Hedging and the Value of Hedging Opportunities

Hedging strategies typically assume that hedging is costless and that only one futures market exists. When these assumptions are dropped, the demand for hedging is shown to depend on basis risk, price risk, and the hedger's risk preference. The marginal and incremental value of hedging opportunities are computed for the general cases of one and two markets and applied to the specific case of Pennsylvania dairy input hedging.     

Measuring portfolio strategic performance using key performance indicators

It is difficult to find indicators for measuring the achievement of objectives during the progress of project portfolios. This article presents an approach for developing key strategic perfor‐mance indicators considering this limitation. The indicators proposed help measure the achievement of a portfolio's strategic objectives taking into account the realization of key benefits. This approach helps identify strategic interdependences between projects that the portfolio is composed of, facilitating the understanding of how the performance of a single project affects the overall performance of a portfolio. The key perfor‐mance indicators can also be used for monitoring the materialization of risks and opportunities influencing the strategic performance of a portfolio.     

房地产开发企业多项目管理研究综述

本文针对国内外研究学者在多项目管理领域的最新成果进行了概括性论述,分析了房地产开发企业多项目管理产生的背景、存在的问题以及解决方法,对多项目管理的研究具有较高的参考价值。