【摘要】：風(fēng)險(xiǎn)投資能促進(jìn)技術(shù)創(chuàng)新和經(jīng)濟(jì)發(fā)展，風(fēng)險(xiǎn)投資退出主要有四種方式：首次公開發(fā)行、兼并與收購(gòu)、回購(gòu)和清算，我國(guó)創(chuàng)業(yè)板上市門檻較高，首次公開發(fā)行費(fèi)用昂貴；由于信息不對(duì)稱普遍存在，企業(yè)兼并或收購(gòu)的方式，將會(huì)導(dǎo)致風(fēng)險(xiǎn)企業(yè)或項(xiàng)目的價(jià)值被低估，從而使得風(fēng)險(xiǎn)投資項(xiàng)目的真實(shí)價(jià)值無法得到有效揭示，風(fēng)險(xiǎn)資本難以順利退出，市場(chǎng)效率低下；由于風(fēng)險(xiǎn)企業(yè)資金問題，回購(gòu)的也存在難度；清算只有是在風(fēng)險(xiǎn)企業(yè)破產(chǎn)時(shí)才選用的手段。以上這些退出方式雖各有優(yōu)點(diǎn)但均難以實(shí)現(xiàn)風(fēng)險(xiǎn)投資者的資本價(jià)值最大化，解決該問題的核心在于揭示不對(duì)稱信息下風(fēng)險(xiǎn)投資退出交易中風(fēng)險(xiǎn)企業(yè)或項(xiàng)目的真實(shí)價(jià)值，促使投資到風(fēng)險(xiǎn)企業(yè)的資本實(shí)現(xiàn)價(jià)值最大，風(fēng)險(xiǎn)投資順利退出，達(dá)到風(fēng)險(xiǎn)投資的資本增值與循環(huán)使用的目的。 因?yàn)榕馁u本質(zhì)上是一種非對(duì)稱信息情況下配置資源的有效手段和價(jià)值揭示機(jī)制，拍賣理論能夠解決物品的價(jià)值最大化和資源配置最優(yōu)化題，進(jìn)而規(guī)避風(fēng)險(xiǎn)投資退出時(shí)由于不對(duì)稱信息所導(dǎo)致的道德風(fēng)險(xiǎn)和逆向選擇問題。本文站在拍賣方的視角，建立了兩種風(fēng)險(xiǎn)投資股權(quán)退出的多屬性拍賣機(jī)制數(shù)學(xué)模型——統(tǒng)一價(jià)格拍賣模型和歧視價(jià)格拍賣模型，使風(fēng)險(xiǎn)投資股權(quán)價(jià)值實(shí)現(xiàn)最大化。在建立拍賣模型之前，由于風(fēng)險(xiǎn)投資退出股權(quán)存在諸如價(jià)格、交割時(shí)間、競(jìng)標(biāo)人聲譽(yù)、支付條件、增值服務(wù)等多種屬性，本文運(yùn)用多效用理論，分兩個(gè)階段篩選拍賣系統(tǒng)競(jìng)標(biāo)人，在第一階段運(yùn)用多效用理論進(jìn)行綜合打分淘汰一些低質(zhì)量投標(biāo)人，在第二階段就切換到最重要的價(jià)格屬性上按單屬性物品進(jìn)行拍賣，并按照風(fēng)險(xiǎn)投資股權(quán)退出拍賣的最重要屬性——價(jià)格屬性將拍賣分為統(tǒng)一價(jià)格拍賣和歧視性價(jià)格拍賣，在此基礎(chǔ)上建立相應(yīng)的數(shù)學(xué)模型。 針對(duì)風(fēng)險(xiǎn)投資股權(quán)退出關(guān)聯(lián)價(jià)值拍賣的特性，如投標(biāo)人的智能行為、相互學(xué)習(xí)、信息傳遞等一系列行為，以及投標(biāo)人競(jìng)價(jià)策略，本文多主體系統(tǒng)引入拍賣機(jī)制來解決股權(quán)拍賣價(jià)值最大化和資源配置問題。假定這些智能的主體（Agent）就是買方投標(biāo)人,在開放、動(dòng)態(tài)的多主體系統(tǒng)中，自利主體具有自身的目標(biāo)和偏好,通過觀察、協(xié)商與推理，來確定采取什么樣的報(bào)價(jià)行為策略。單主體往往不能獨(dú)立完成目標(biāo)，需要其它主體的參與和幫助，即需要通過多個(gè)主體合力來共同解決優(yōu)化報(bào)價(jià)問題。根據(jù)拍賣理論的顯示原理，當(dāng)競(jìng)標(biāo)者采取說真話的策略時(shí)候，對(duì)自己是最優(yōu)策略，對(duì)拍賣者也是期望收益最大，拍賣系統(tǒng)將達(dá)到一個(gè)均衡。但是在風(fēng)險(xiǎn)投資股權(quán)退出關(guān)聯(lián)價(jià)值拍賣情況下，要使具有有限理性的競(jìng)標(biāo)者在排除任何噪音干擾情況下說真話很難，于是運(yùn)用智能算法的學(xué)習(xí)優(yōu)化機(jī)制可以使競(jìng)標(biāo)者在不斷隨著智能群體得優(yōu)化達(dá)到最優(yōu)解，拍賣系統(tǒng)達(dá)到均衡，從而使風(fēng)險(xiǎn)投資股權(quán)退出的拍賣者期望收益最大。本文運(yùn)用粒子群算法（PSO）優(yōu)化風(fēng)險(xiǎn)投資股權(quán)退出時(shí)統(tǒng)一價(jià)格拍賣數(shù)學(xué)模型的競(jìng)標(biāo)者報(bào)價(jià)策略，運(yùn)用遺傳算法(GA)優(yōu)化風(fēng)險(xiǎn)投資股權(quán)退出時(shí)歧視性價(jià)格拍賣模型的競(jìng)標(biāo)者報(bào)價(jià)策略。 基于關(guān)聯(lián)價(jià)值拍賣系統(tǒng)的模型和競(jìng)標(biāo)人的報(bào)價(jià)策略可以看作是一個(gè)動(dòng)態(tài)的優(yōu)化復(fù)雜系統(tǒng)，傳統(tǒng)的數(shù)學(xué)方法和實(shí)驗(yàn)方法很難對(duì)其求解，本文運(yùn)用復(fù)雜系統(tǒng)的方法——多主體仿真方法解決復(fù)雜拍賣系統(tǒng)的報(bào)價(jià)優(yōu)化和拍賣者期望最大化問題。多主體建模仿真是一種非常靈活的建模仿真技術(shù)，本質(zhì)特征是采用多主體視角建立系統(tǒng)的概念模型。本文正是基于多主體視角描述風(fēng)險(xiǎn)投資股權(quán)退出拍賣，，在拍賣競(jìng)標(biāo)過程中，各投標(biāo)人是基于關(guān)聯(lián)價(jià)值的拍賣競(jìng)標(biāo)，由于競(jìng)標(biāo)前各主體之間即現(xiàn)實(shí)中的競(jìng)標(biāo)人的思想和行為具有復(fù)雜性，他們有智能性、適應(yīng)性、學(xué)習(xí)性和交互性，主體之間必然有噪音形式的信息溝通渠道，主體間會(huì)獲取部分他人投標(biāo)信息，以爭(zhēng)取自己利益最大化，這種復(fù)雜的選擇過程滿足多主體的特征和屬性。因此，本文選用多主體仿真平臺(tái)Netlogo對(duì)各主體報(bào)價(jià)策略和股權(quán)退出統(tǒng)一價(jià)格拍賣模型以及歧視價(jià)格拍賣模型進(jìn)行仿真驗(yàn)證。本文的拍賣系統(tǒng)主要流程是實(shí)際系統(tǒng)→概念模型→仿真模型→仿真結(jié)果→結(jié)論，最后用結(jié)論來驗(yàn)證和修正風(fēng)險(xiǎn)投資股權(quán)退出拍賣模型的正確性和合理性。
[Abstract]:Venture capital can promote technological innovation and economic development. There are four main ways of venture capital withdrawal: first open issue, merger and acquisition, repurchase and liquidation. The threshold of the gem is high, and the initial public issue is expensive. Because of the widespread existence of information asymmetry, the enterprise merger or acquisition will lead to the risk enterprises. Or the value of the project is underestimated, which makes the real value of the venture capital project can not be effectively revealed, the venture capital is difficult to smooth out, the market efficiency is low; because of the venture capital problem, the repurchase is also difficult; liquidation is only the means to choose when the venture enterprise is bankrupt. It is difficult to realize the maximization of capital value of venture investors. The core of the problem is to reveal the real value of venture enterprises or projects under asymmetric information, and to make the capital realize the maximum value of the venture capital, the venture capital is successfully withdrawn and the capital appreciation of the venture capital is achieved. The purpose of recycling.
Because auction is essentially an effective means and value disclosure mechanism to allocate resources under asymmetric information, auction theory can solve the problem of maximizing the value of goods and optimizing the allocation of resources, and then evade the moral hazard and adverse selection caused by asymmetric information when venture capital exit. In the view of the square, two kinds of mathematical model of the multi attribute auction mechanism of the venture capital equity withdrawal - the unified price auction model and the discriminatory price auction model are established to maximize the equity value of the venture capital. In this paper, we use the multi utility theory and use the multi utility theory to select the bidder in the auction system in two stages. In the first stage, the multi utility theory is used for comprehensive scoring to eliminate some low quality bidder. In the second stage, a single attribute item is auctioned on the most important price attribute, and the risk is put in accordance with the risk. The most important attribute of the equity withdrawal from the auction, the price attribute, divides the auction into a unified price auction and a discriminatory price auction, on the basis of which a corresponding mathematical model is established.
In view of the characteristics of the equity auction of venture capital, such as the intelligent behavior of the bidder, the mutual learning, the information transmission, and the bidding strategy of the bidder, the multi-agent system introduces the auction mechanism to solve the problem of the maximization of the value of the equity auction and the allocation of resources. It is assumed that the main body of the intelligence (Agent) is to buy. The bidder, in the open, dynamic multi-agent system, the self-interest body has its own goals and preferences, through observation, negotiation and reasoning, to determine what kind of bidding behavior strategy. The single subject can not accomplish the goal independently, and need the participation and help of other subjects, that is to say, we need to jointly solve the advantages through multiple main forces. According to the theory of auction theory, when the bidder adopts the strategy of telling the truth, it is the best strategy for the bidder, and the auctioneer is also expected to get the maximum benefit, and the auction system will reach a balance. But in the case of the venture capital stock withdrawal from the associated value auction, the competitor with limited rationality should be excluded. In the case of noise interference, it is difficult to say the truth, so using the learning optimization mechanism of intelligent algorithm can make the bidder achieve the optimal solution with the optimization of the intelligent group, the auction system reaches the equilibrium, which makes the auctioneer with the venture capital stock exit expect the maximum benefit. This paper uses the particle swarm optimization (PSO) to optimize the venture capital stock. The bidding strategy of the bidder is unified by the mathematical model of the price auction, and the genetic algorithm (GA) is used to optimize the bidding strategy of the bidders in the discriminatory price auction model when the risk investment is withdrawn.
The model based on the associated value auction system and the bidding strategy of the bidder can be considered as a dynamic and complex system. The traditional mathematical methods and experimental methods are difficult to solve. In this paper, the method of complex system is used to solve the optimization of the quotation of complex auction system and the maximization of the expectation of the auctioneer. Multi subject modeling and simulation is a very flexible modeling and simulation technology. The essential feature is to establish the conceptual model of the system by multi-agent perspective. In this paper, it is based on the multi-agent perspective to describe the exit auction of risk investment. In the auction bidding process, the bidder is the auction bidding based on the associated value, due to the pre bidding owners. The thought and behavior of the bidders in reality are complex. They have intelligence, adaptability, learning and interactivity. There must be a noise form of information communication channel between the subjects. The subject will get some other people's bidding information so as to maximize their own interests. This complex selection process meets the characteristics of many subjects. Therefore, in this paper, the multi-agent simulation platform Netlogo is used to verify the bidding strategy of each subject, the unified price auction model and the discriminatory price auction model. The main flow of the auction system is the actual system, the conceptual model, the simulation model, the simulation result and the conclusion. Finally, the conclusion is used to verify and verify the results. It is correct and reasonable to modify the venture capital withdrawal auction model.
【學(xué)位授予單位】：武漢大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2012
【分類號(hào)】：TP18;F832.51;F724.59

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