Valuation and Optimization of Venture Capital Deals Portfolio Based on Risk Approach

نوع: Type: thesis

مقطع: Segment: PHD

عنوان: Title: Valuation and Optimization of Venture Capital Deals Portfolio Based on Risk Approach

ارائه دهنده: Provider: Mohammad Reza Valaei

اساتید راهنما: Supervisors: Dr Vahid Khodakarmi

اساتید مشاور: Advisory Professors:

اساتید ممتحن یا داور: Examining professors or referees: Dr. Fariborz Jolai, Dr. Nafiseh Soleymani, Dr. Maryam Ashrafi

زمان و تاریخ ارائه: Time and date of presentation: 2023July 22 ، 10:30 am

مکان ارائه: Place of presentation: Amphitheatert,Faculty of Engineering

چکیده: Abstract: Decisions of venture capitalists (VC) have always been accompanied by many risks and uncertainties, such as extreme ambiguity, the lack of sufficient data, and the effect of various technical and non-technical factors, which have increased the complexity and reduced the efficiency of conventional decision-making methods. By using the Sequential Researchs method and presenting three problems (with related solutions), this research will help venture capitalists to choose their projects. The three problems include how to estimate the probability of failure (default rate) of startups in different time frames, how to valuate startups in different contractual terms, and how to choose the portfolio of VCs. In this regard, according to the importance of the concept of risk, risks are classified into three types: soft, hard, and scenario factors. In the one hand, Soft factors have been evaluated through multi-stage Bayesian Network modeling by determining the default rate of each startup, but on the other hand, hard factors have been evaluated using probability distribution functions, and scenario factors have been evaluated by using the real options method. In this research, by separating the risk factors, the valuation of the startups is determined without using the risk-adjusted discount rate and the probability distribution of Net Present Value of startups with the contractual terms is determined. In the next part, we developed three multi-objective mathematical models with financial and non-financial indicators to consider, selection of startups and contractual conditions such as call options, the liquidity preference , the right of participation and the dependence between the selection of projects and contractual terms. In order to solve the presented mathematical models, due to the NP-Hard complexity, the meta-heuristic algorithms approach has been used. Finally, the two approaches of portfolio selection based on the "right tail of the NPV probability distribution function" and the "utility function" is compared, and it is found that the "utility function" approach provides better results in the range of 40-70% failure probability of each startup.

فایل: ّFile: Download فایل