不同事件下风险资本分阶段投资最优投资时机比较研究

在风险投资中,分阶段投资的投资时机选择问题是风险投资家决策的最大难点问题。首先通过构建虚拟现金流变量,使风险投资前、中、后阶段的分析纳入一个统一的框架;其次应用或有债权定价技术分析了基于一般事件的分阶段最优投资规则。并结合动态规划技术,应用跳跃—扩散过程刻划突发事件对分阶段投资项目现金流的影响路径,分析了基于突发事件的分阶段最优投资规则;最后,应用工程数学软件Matlab6.5对一般情况和突发事件下的投资时机进行了数值模拟和比较分析,得出了一些有益的研究结论。     

风险投资分段投资的单合同最优激励模型研究

针对风险投资分段投资存在的道德风险问题,运用委托代理理论,建立了单合同的风险投资家和风险企业家之间的最优激励模型,模型对单合同的最优激励报酬进行了优化,并给出了风险投资的最优合同安排和最优退出时机,使风险投资家和风险企业家博弈达到均衡状态.最后,给出了一个简单算例.     

基于双边逆向选择下的两阶段风险投资契约模型

从风险投资家的角度出发,考虑风险投资初始阶段和后续阶段创业企业家和风险投资家具有的不同私人信息,在委托一代理理论框架下构建了双边逆向选择下的投资和现金流权分配契约模型.研究发现,在混同一分离均衡下,高质量的风险投资家存在唯一的最优纯股权投资契约,且初始投资低于帕累托效率投资水平,高质量风险投资家的后续投资高于帕累托效率投资水平,造成这一结果的原因是高质量风险投资家付出的信号成本.而在混同一混同均衡下,存在唯一的最优纯股权投资契约,且初始投资和后续投资均高于帕累托效率投资水平,造成这一结果的原因是创业企业家为了降低风险投资家质量信息的不确定性带来的损失而采取的措施.研究结果为风险投资家在双边逆向选择下设计合理的投资契约提供了理论依据.     

基于股权——债权条件下风险投资的激励机制分析

运用博弈论中委托—代理理论对股权—债权条件下风险投资的激励机制进行了系统分析.根据风险投资家提供股权—债权与风险企业家提供股权融资的假设条件构造了一个基本博弈模型,并对模型进行了推广.研究发现:风险企业家的投资不仅有融资功能,而且还可以作为一种信号传递改变风险投资家的投资信念,使之对项目前景更乐观;扩展模型比基本模型更能改善风险企业家的投资行为,使之投入更多资金和给予风险投资家更高激励;此外,扩展模型更能消除股权—债权投资比例的相互替代性.     

创业企业控制权模式选择研究

创业企业家和风险投资家因为控制权模式不合理所导致的矛盾在我国普遍存在。为解决该问题,本文通过研究创业企业家与风险投资家在博弈过程中的控制权策略选择及由此决定的控制权模式,运用演化博弈理论中复制动态的方法分析发现:(1)创业企业家和风险投资家在选择是否争取控制权的博弈结果是联合控制或相机控制;(2)项目成功概率、风险投资家获取的剩余索取权增加时收敛于联合控制,反之则收敛于相机控制;当项目成功的概率大于50%时,固定收益减少收敛于联合控制,创业企业产出增加收敛于联合控制,反则收敛于相机控制。最后,通过CV Source数据库样本数据对模型结论进行了实证检验,检验结果与理论模型的主要结论相一致。研究结论对于指导我国创业企业控制权模式合理选择具有一定的实践意义。     

公平偏好下考虑互补效应的项目投资收益分配研究

决策者的公平偏好对项目投资合作的形成和推进有重要影响。本文从创业企业和风险投资家的双重道德风险出发,选取Nash谈判解为公平偏好参照点,构建创业企业具有公平偏好的项目投资委托代理模型,研究委托方和代理方的能力存在互补效应的情形下,公平偏好对项目收益分配及双方努力水平的影响。结果表明:项目收益的最优分配比例和双方的最高努力水平均与创业企业的公平偏好程度相关。在互补效应存在时,双方的努力水平不会随收益分配比例的变化呈现单调变化趋势。如果双方的能力互补程度较小,具有公平偏好的创业企业会以Nash谈判解为自己的收益下限,风险投资家需要向其让渡更多的项目收益才能实现有效激励;如果双方的能力互补程度较大,创业企业会将Nash谈判解作为自己的收益上限,风险投资家即使不给予其大于Nash谈判解的收益也可实现有效激励。     

风险资本的组合投资最优化模型研究

利用委托代理理论建立了风险资本的组合投资最优化模型,通过该模型给出了项目数和收益分配比例的最优解,并分析了组合投资的项目数和收益分配比例对风险投资家和企业家努力水平的影响。     

风险收益不对等条件下中国对外直接投资合作模式的优化

针对对外直接投资所面临的资金短缺、进展不顺利的问题,在风险分担理论的基础上构建中国政府、东道国政府和社会资本的投资合作模型。目的在于设计出足够吸引社会资本投入,且保证中国对外直接投资顺利开展的风险分担模式。并通过数值模拟风险分担比例和利润分享比例对投资时机和投资价值的影响,证明了中国政府与社会资本间存在最优的风险分担比例,以及东道国政府与社会资本存在最优利润分享比例。     

市场接纳不确定下短周期新产品产能投资研究 ——考虑竞争的投资时机与规模决策

新产品的市场接纳具有很大不确定性,传统投资理论并不适用于新产品投资。针对新产品投资中的产能投资,研究了垄断企业和有成本差异的竞争企业制定短周期新产品的产能投资时机与规模策略。给定企业“早”和“晚”两个投资时机可供选择,定义“早”投资时,企业只知道新产品市场规模的期望和方差;“晚”投资时,企业知道新产品真实的市场规模。垄断企业进入市场之前无法进行销售信息的收集,只会选择“早”投资或者不投资,给出其选择“早”投资的条件、最优产能投资规模及最大期望利润。有成本差异企业竞争的情形可以分为四种,分别给出四种情形下的最优产能投资规模及最大期望利润,并通过比较各情形下两企业的最大期望利润给出最优的产能投资时机策略。     

石油勘探项目分阶段投资的最优时机选择

针对一次性投资决策理论与方法在石油勘探项目分阶段投资决策中应用的局限性,运用实物期权中的序列投资决策理论与方法,假设勘探储量转让价格服从跳跃扩散过程,构建了石油勘探项目分阶段投资的最优时机选择模型,逆序求解得出各阶段最优投资时机临界值的解析表达式,在此基础上通过案例演算对比分析了一次性投资和分阶段投资的最优时机决策规则.研究结果表明:一次性投资下的最优时机临界值高于分阶段投资下的最优时机临界值,且各阶段的最优投资时机临界值随勘探进程的不断深入呈现逐渐下降的趋势.     

网络视频节目中羊群效应的影响研究

考虑累积观看节目用户量产生的羊群效应角度构建两阶段决策模型,得到节目最优定价策略和最优广告量策略。研究表明:收费模式中羊群效应对最优定价的影响特征与用户规模有关,并进一步导致免费模式中最优广告量减少。在收费模式羊群效应较高情况下,运营商能通过延长收费模式时间提高节目利润。还发现收费模式中羊群效应导致观看节目用户总规模增加,但收费模式对免费模式有挤兑效应。在免费模式中羊群效应较低情况下,只有收费模式中具有较高的羊群效应才能使节目总利润增加,否则总利润减少。     

Optimal production strategy under demand fluctuations: Technology versus capacity

This paper provides a comparative analysis of five possible production strategies for two kinds of flexibility investment, namely flexible technology and flexible capacity, under demand fluctuations. Each strategy is underpinned by a set of operations decisions on technology level, capacity amount, production quantity, and pricing. By evaluating each strategy, we show how market uncertainty, production cost structure, operations timing, and investment costing environment affect a firm’s strategic decisions. The results show that there is no sequential effect of the two flexibility investments. We also illustrate the different ways in which flexible technology and flexible capacity affect a firm’s profit under demand fluctuations. The results reveal that compared to no flexibility investment, flexible technology investment earns the same or a higher profit for a firm, whereas flexible capacity investment can be beneficial or harmful to a firm’s profit. Moreover, we prove that higher flexibility does not guarantee more profit. Depending on the situation, the optimal strategy can be any one of the five possible strategies. We also provide the optimality conditions for each strategy.     

Investment decisions in the rent-to-own industry in the absence of inventory

This study addresses the product investment decision faced by firms in the rent-to-own industry. In this setting, a customer arrives according to a random process and requests one unit of a product to rent (and eventually own should he/she choose to make all the required payments). At the time of request, if the product is available in inventory, the firm enters into a contractual agreement (by accepting the customer's offer) and rents the merchandise. More interesting and the case considered here, if the requested item is not in inventory, the firm must decide whether to purchase the item in order to rent it out or to simply reject the request. The customer's offer specifies the desired maximum contract length and the payment frequency—from which the firm determines the fixed periodic payment charged. The firm makes its investment decision based on the characteristics of the offer as well as those of the product (eg, initial and resale values, useful life and carrying costs) in essence performing a complicated cost benefit analysis. An extension is also considered whereby instead of simply rejecting the request the firm can adjust the required payment amount. Dynamic programming techniques are used to address the problem and to solve for the firm's optimal decision.     

Step by step. The benefits of stage-based R&D licensing contracts

We examine how a licensor can optimally design licensing contracts for multi-phase R&D projects when he does not know the licensee’s project valuation, leading to adverse selection, and cannot enforce the licensee’s effort level, resulting in moral hazard. We focus on the effect of the phased nature typical of such projects, and compare single-phase and multi-phase contracts. We determine the optimal values for the upfront payment, milestone payments and royalties, and the optimal timing for outlicensing. Including multiple milestones and accompanying payments can be an effective way of discriminating between licensees holding different valuations, without having to manipulate the royalty rate, which induces licensees to invest less, resulting in lower project values and socially suboptimal solutions. Interestingly, we also find that multiple milestone payments are beneficial even when the licensor is risk-averse, contrary to standard contract theory results, which recommend that only an upfront payment should be used. In terms of licensing timing, we show that the optimal time depends on the licensor’s risk aversion, the characteristics of the licensee and the project value.     

A generalized real option pricing method of R&D investments: jump diffusion and external competition

ABSTRACT

Numerous studies have assessed Research and Development (R&D) investment using the real option pricing approach. This paper proposes a more general real option pricing method that both considers the specificity of R&D investment (such as uncertainty) and the R&D investment opportunity of a business in a market environment with external competitors. Specifically, we adopt a jump diffusion model to evaluate R&D investments that incorporate the uncertainties of these activities. The model values a pioneer's R&D investment opportunity allowing the chance that competitors may enter the market and the project value may vary with time. By construction and analysis of the model, we then analyse the optimal timing to realize profit on an investment. Overall, this model should facilitate a more comprehensive evaluation for R&D investments.     

Earnouts in mergers and acquisitions: A game-theoretic option pricing approach

This paper presents a valuation approach for merger and acquisition (M&A) deals employing contingent earnouts. It is argued that these transactions have option-like features, and the paper uses a game-theoretic option approach to model the value of such claims. More specifically, the paper examines the impact of uncertainty on the optimal timing of M&A using earnouts, and it also investigates the impact of uncertainty on the terms of the earnout. Optimal earnout and initial payment combinations are endogenously derived from the model, and testable hypotheses are developed. The theoretical contribution of this paper is a dynamic decision-making model of the invest-to-learn option generated upon investment in an acquisition. The paper also offers practical implications for the design of acquisitions employing earnouts.     

Uncertainty and stepwise investment

We analyze the optimal investment strategy of a firm that can complete a project either in one stage at a single freely chosen time point or in incremental steps at distinct time points. The presence of economies of scale gives rise to the following trade-off: lumpy investment has a lower total cost, but stepwise investment gives more flexibility by letting the firm choose the timing individually for each stage. Our main question is how uncertainty in market development affects this trade-off. The answer is unambiguous and in contrast with a conventional real-options intuition: higher uncertainty makes the single-stage investment more attractive relative to the more flexible stepwise investment strategy.     

Optimal exercise of jointly held real options: A Nash bargaining approach with value diversion

This paper provides a two-stage decision framework in which two or more parties exercise a jointly held real option. We show that a single party’s timing decision is always socially efficient if it precedes bargaining on the terms of sharing. However, if the sharing rule is agreed before the exercise timing decision is made, then socially optimal timing is attained only if there is a cash payment element in the division of surplus. If the party that chooses the exercise timing can divert value from the project, then the first-best outcome may not be possible at all and the second-best outcome may be implemented using a contract that is generally not optimal in the former cases. Our framework contributes to the understanding of a range of empirical regularities in corporate and entrepreneurial finance.     

Optimal Investment and Dividend Strategy in the Discrete Sparre Andersen Risk Model

In the discrete-time Sparre Andersen risk model with investments and dividend payments, the company controls the dividend payments and the proportions of venture investments in order to maximize the cumulative expected discounted dividends prior to ruin. The paper gets the algorithm of the optimal dividend strategy by analyzing a Hamilton-Jacobi-Bellman equation and transforming the value function. Furthermore, the existence of the optimal solution of the transformation function is proved by using compression mapping and fixed point principle. In order to make the calculation easier, this paper also proposes an innovative random simulation method for the optimal strategy, and proves that the simulation result is the consistent estimate of the real value. Finally, the random simulation method in the Matlab is used for numerical analysis in an example, which shows the innovative simulation method is a very good and helpful method for making dividend payment and investment decisions.