基金发展对证券市场均衡及资产价格的影响研究

基金的迅速发展使得传统的投资结构发生改变,很多投资者不再是直接持有证券,而是通过申购基金间接持有,投资者结构的改变使得传统资产定价模型的一些假设不再适用。本文正是基于此背景,研究基金投资者和基金经理之间的委托代理问题对资产价格的影响,通过理论分析得到两因素资产定价模型,并用我国A股市场的数据做了实证检验,从理论和实证两个角度都论证了投资者和基金经理之间的委托代理问题是资产定价中不可忽略的因素。     

风险内生的委托代理模型研究

证券投资基金的委托代理关系与一般的委托代理关系不同,在一般的委托代理关系中,产出的风险是外生的,而基金产出的风险是内生的,即风险是由基金管理人来选择的.在模型假设的背景下,在不考虑基金管理人的努力成本时,基金委托代理关系中不存在道德风险问题.如果考虑基金管理人的努力成本,当其行为不可观测时,基金投资者无法通过契约参数的变化来影响基金管理人的努力水平,但此时投资组合的风险水平将低于基金管理人行为可观测时的情况.实证研究证实了基金收益分享比例与基金管理人努力程度无关的模型推论.     

多期有限合伙制与公司制的道德风险和机制选择

本文基于委托代理理论和博弈论建立了有限合伙制与公司制下的多期道德风险模型,分析了委托人和代理人如何对这两种机制进行选择的问题.结论表明:两种机制下均存在道德风险问题,且在有限合伙制下因激励程度较高得到改善;两种机制相比较,公司制在特定条件下为博弈双方的最优选择,而有限合伙制只有在博弈双方地位不平等时才能达成.     

所有者结构与封闭式基金折价

委托代理理论认为所有者结构将对公司价值存在影响,分别为兴趣趋同效应和大股东侵占效应。这两种效应分别预言:大股东持股比例上升将增加/损害公司价值。在西方和中国股市的实证研究同时发现了这两种效应的存在。同时有理认认为:在美国的封闭式基金之间也存在大股东侵占效应,基金大股东持股越高,封闭式基金折价幅度越高。本文针对中国封闭式基金的理论和实证研究发现:在中国,横截面回归分析结果表明:当封闭式基金大股东持股比例越高,基金折价幅度越大。本文作者进一步指出:这种与美国实证研究类似的结果不是由于大股东侵占引起的,而是由于机构投资者等大股东主动选择的结果:机构投资者倾向于投资于折价幅度比较高的封闭式基金。     

多期有限合伙制与公司制的道德风险和机制选择北大核心CSCD

本文基于委托代理理论和博弈论建立了有限合伙制与公司制下的多期道德风险模型,分析了委托人和代理人如何对这两种机制进行选择的问题．结论表明：两种机制下均存在道德风险问题,且在有限合伙制下因激励程度较高得到改善;两种机制相比较,公司制在特定条件下为博弈双方的最优选择,而有限合伙制只有在博弈双方地位不平等时才能达成．     

隐性约束机制的设计研究

文章研究在多阶段动态博弈情况下隐蔽行为的隐性约束机制设计问题，用博弈论方法和信息经济学的委托-代理理论方法，建立多阶段委托-代理关系约束问题重复博弈的声誉模型，对隐蔽行为的隐性约束机制进行研究，证明了多阶段委托-代理关系中隐性约束机制的存在，给出了这种情况下的有效约束条件，隐性约束机制的设计方法以及其他结论。     

战略投资者与财务投资者投资行为比较:基于合作博弈Shapley值的分析

战略投资者和财务投资者是企业发展过程中两类非常重要的投资者,对两类投资者的投资行为当前有很多争论.通过将两类投资者的投资行为抽象为合作博弈中的结盟行为,利用合作博弈联盟分配中的Shapley值分析两类投资者应该获得的公平收益,并将其与按股份比例获得的收益进行比较.结论显示,战略投资者在实际中获得的收益要小于其公平收益,财务投资者则获得了公平收益;战略投资者总倾向转变为财务投资者,并在上市后退出.     

逆向信息和道德风险下的供应链线性激励契约研究

本文我们利用委托代理理论，研究了供应商和零售商之间的利益博弈．考察了两类不对称信息——逆向信息和道德风险并存下的供应链线性契约．通过把问题归结为一个二层规划问题，求解得到了相关结论：与道德风险下的线性契约[12]相比，两类不对称信息的存在，使得对零售商的激励变得更加复杂．通过数值试验，比较了线性甄别契约和线性混同契约，发现对于作为委托人的供应商而言，甄别契约比汇同契约更有效率．     

基金契约中代理问题存在性研究

基金投资与基金经理之间的关系是一种委托一代理关系，这种委托一代理关系集中体现在基金契约中。为了激励基金经理能按照最大化基金投资的效用行动，减少代理问题，人们设计了各种类型的基金契约。本以一个最常用的线性基金契约为例，讨论分析了其中代理问题的存在性。     

基于随机微分博弈的最优投资

研究存在模型风险的最优投资决策问题,将该问题刻画为投资者与自然之间的二人-零和随机微分博弈,其中自然是博弈的"虚拟"参与者.利用随机微分博弈分析方法,通过求解最优控制问题对应的HJBI(Hamilton-Jacobi-Bellman-Isaacs)方程,在完备市场和存在随机收益流的非完备市场模型下,都得到了投资者最优投资策略以及最优值函数的解析表达式.结果表明,在完备市场条件下,投资者的最优风险投资额为零,在非完备市场条件下最优投资策略将卖空风险资产,且卖空额随着随机收益流波动率的增大而增加,随风险资产波动率增大而减少.     

基金市场监管的进化博弈分析

通过对基金市场中基金管理者和市场监管者的行为分析,引入有限理性博弈概念,建立了一个基金市场监管的动态博弈模型,并应用进化博弈方法在模型求解和参数分析的基础提出了相关政策建议:1)市场监管的比例应稍超过某个临界值则可达到最优;2)应降低基金管理者对市场监管要求的临界值;3)应关注监管者对市场中违规基金数量比例预期的临界值,并适时的调整监管力度使得基金群体中违规的比例趋向于最小.     

基于半参数多元Copula-GARCH模型的开放式基金投资组合风险分析

利用Copula技术对我国开放式基金市场的投资组合进行了风险分析。为克服传统Copula模型对金融尾部数据刻画能力的不足,建立了半参数的多元Copula-GARCH模型,灵活地对各支基金的边缘分布进行拟合,刻画了开放式基金投资组合的相依结构。并利用基于Copula技术的蒙特卡洛模拟,对投资组合进行了VaR分析,结果证实了所建立模型的可行性和有效性。     

On minimizing drawdown risks of lifetime investments

Drawdown measures the decline of portfolio value from its historic high-water mark. In this paper, we study a lifetime investment problem aiming at minimizing the risk of drawdown occurrences. Under the Black–Scholes framework, we examine two financial market models: a market with two risky assets, and a market with a risk-free asset and a risky asset. Closed-form optimal trading strategies are derived under both models by utilizing a decomposition technique on the associated Hamilton–Jacobi–Bellman (HJB) equation. We show that it is optimal to minimize the portfolio variance when the fund value is at its historic high-water mark. Moreover, when the fund value drops, the proportion of wealth invested in the asset with a higher instantaneous rate of return should be increased. We find that the instantaneous return rate of the minimum lifetime drawdown probability (MLDP) portfolio is never less than the return rate of the minimum variance (MV) portfolio. This supports the practical use of drawdown-based performance measures in which the role of volatility is replaced by drawdown.     

一直在努力?——基金管理者买卖行为的有效性分析

通过构建收益缺口-基金的净资产收益与投资组合收益之差,探讨了我国证券市场中开放式基金管理者的买卖行为及其对基金业绩的影响.研究结果表明,在2004至2007年中,基金月收益缺口的均值显著大于零,表明基金管理者的努力总体上能增加基金的价值;投资者若模拟基金的股票构成进行投资,在熊市中,其平均回报小于基金的收益,但在牛市中,却显著地大于基金的收益,这一差异对配置型基金更明显.同时,基金收益缺口的大小与基金的类型和规模显著相关.     

Mean-variance optimization problems for an accumulation phase in a defined benefit plan

In this paper we deal with contribution rate and asset allocation strategies in a pre-retirement accumulation phase. We consider a single cohort of workers and investigate a retirement plan of a defined benefit type in which an accumulated fund is converted into a life annuity. Due to the random evolution of a mortality intensity, the future price of an annuity, and as a result, the liability of the fund, is uncertain. A manager has control over a contribution rate and an investment strategy and is concerned with covering the random claim. We consider two mean-variance optimization problems, which are quadratic control problems with an additional constraint on the expected value of the terminal surplus of the fund. This functional objectives can be related to the well-established financial theory of claim hedging. The financial market consists of a risk-free asset with a constant force of interest and a risky asset whose price is driven by a Lévy noise, whereas the evolution of a mortality intensity is described by a stochastic differential equation driven by a Brownian motion. Techniques from the stochastic control theory are applied in order to find optimal strategies.     

Approximation algorithms for supply chain planning and logistics problems with market choice

We propose generalizations of a broad class of traditional supply chain planning and logistics models that we call supply chain planning and logistics problems with market choice. Instead of the traditional setting, we are given a set of markets, each specified by a sequence of demands and associated with a revenue. Decisions are made in two stages. In the first stage, one chooses a subset of markets and rejects the others. Once that market choice is made, one needs to construct a minimum-cost production plan (set of facilities) to satisfy all of the demands of all the selected markets. The goal is to minimize the overall lost revenues of rejected markets and the production (facility opening and connection) costs. These models capture important aspects of demand shaping within supply chain planning and logistics models. We introduce a general algorithmic framework that leverages existing approximation results for the traditional models to obtain corresponding results for their counterpart models with market choice. More specifically, any LP-based α-approximation for the traditional model can be leveraged to a \frac11-e^-1/a{\frac{1}{1-e^{-1/\alpha}}} -approximation algorithm for the counterpart model with market choice. Our techniques are also potentially applicable to other covering problems.     

赎回风险约束的开放式基金管理费研究

从赎回风险的视角研究开放式基金的管理费.以赎回风险为内生变量构建了基金管理人的动态投资决策模型,利用动态优化的Bellman原理得到了最优管理费.进一步分析发现:一是基金管理费与基金管理人的投资能力正相关,即基金管理人的投资能力越强,收取的基金管理费越多;二是基金管理费与投资者的赎回率负相关,即投资者的赎回率越大,基金管理费越少.而且选取中国股票型开放式基金的数据构建VAR计量经济模型,检验基金管理人的投资能力与投资者的赎回风险对基金管理费的影响,实证结果支持理论模型的结论.     

Optimal dynamic asset allocation of pension fund in mortality and salary risks framework

In this paper, we consider the optimal dynamic asset allocation of pension fund with mortality risk and salary risk. The managers of the pension fund try to find the optimal investment policy (optimal asset allocation) to maximize the expected utility of terminal wealth. The market is a combination of financial market and insurance market. The financial market consists of three assets: cashes with stochastic interest rate, stocks and rolling bonds, while the insurance market consists of mortality risk and salary risk. These two non-hedging risks cause incompleteness of the market. By martingale method and dynamic programming principle we first derive the approximate optimal investment policy to overcome the difficulty, then investigate the efficiency of the approximation. Finally, we solve an optimal assets liabilities management(ALM) problem with mortality risk and salary risk under CRRA utility, and reveal the influence of these two risks on the optimal investment policy by numerical illustration.     

Three fuzzy goal programming models for index portfolios

Studies show that most actively managed mutual funds struggle to beat the market, driving an increase in the popularity of index investing. Index investing instruments, including index funds and Exchange-traded Funds, aim to track market performance. This study pursues both tracking error minimization and excess return maximization, two conflicting objectives, to construct an index portfolio. In the real-world financial environment, the desires and expectations of decision makers are generally imprecise. This study applies fuzzy theory to deal with imprecise objectives. This study represents minimizing tracking error and maximizing excess return as ‘fuzzy goals’ to improve traditional goal programming, which is suitable for handling multiple conflicting objectives, but subject to establishing crisp goals. Three fuzzy goal programming (FGP) models that track indexes are compared and discussed, and the results show that through certain membership functions and tracking models, an index tracking portfolio with a tracking error lower than the 0050 index fund, and a similar excess return to 0050 index fund can be constructed using additive type FGP. max-min type FGP underperforms the additive type FGP in index fund construction.     

Solving stochastic complementarity problems in energy market modeling using scenario reduction

In this paper, we analyze market equilibrium models with random aspects that lead to stochastic complementarity problems. While the models presented depict energy markets, the results are believed to be applicable to more general stochastic complementarity problems. The contribution is the development of new heuristic, scenario reduction approaches that iteratively work towards solving the full, extensive form, stochastic market model. The methods are tested on three representative models and supporting numerical results are provided as well as derived mathematical bounds.