Bachelorarbeit, 2013
23 Seiten, Note: 2,0
1. Introduction
2. Literature Review
2.1 Measuring the financial performance of VCFs
2.2 MCDM methodologies and their application on the Venture Capital System
2.2.1 Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)
2.2.2 Modified TOPSIS with objective weights
3. Methodology
3.1 Modified TOPSIS with objective weights
3.2 Choice of Financial Performance Indicators (FPIs)
3.2.1 Profitability
3.2.2 Asset management
3.2.3 Liquidity
3.2.4 Debt management
4. Testing the methodology
4.1 Application
4.2 Results
4.3 Discussion
5. Conclusion
The primary objective of this thesis is to develop an objective, simple, and effective measurement tool for evaluating the relative corporate financial performance of Venture Capital Firms (VCFs). By employing a modified TOPSIS approach with objective weights (mTOPSISow), the research aims to establish a performance ranking of VCFs and determine the influence of specific financial indicators.
2.2.1 Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)
TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is a technique for MCDM and performance analysis of alternatives. Given a set of criteria and a set of alternatives a decision matrix can be generated. Furthermore, the decision maker has to determine the importance of each criterion (weights). However, after a few calculations the Euclidean distances from a Positive Ideal Solution and Negative Ideal Solution are aggregated to form a performance indicator (Similarity to Best Condition). For each alternative this measure is between 0 and 1. A high Similarity to Best Condition (SBC) is preferable. We equate the word “solution” with the word “performance” because every set of solutions is a set of performance entries.
Again, the advantage of this method lies in its simplicity, effectiveness and flexibility concerning the design of problems (i.e. criteria for performance and/or efficiency) (Hwang and Yoon, 1981). Moreover, the decision maker can simply and effectively interpret and visualize performance origins (e.g. with radar charts).
Various advancements and adaptions of TOPSIS methodology have been developed during recent years (Abo-Sinna and Amer; 2005; Chen, 2000; Deng et al., 2000). An application in the field of finance is common (Arslan and Cunkas; 2012; Aydogan, 2011; Zhang et al., 2011). Moreover, Behzadian et al. (2012) show that the approach is widely used in business-related areas. Still, some problems arise, for example weights for criteria are given with subjective influence by the decision maker. Even with AHP (Analytic Hierarchy Process) pairwise comparisons of criteria do not diminish the subjective influence to the utmost satisfaction (Saaty, 1990). Olsen (2004) discusses various attempts that have been undertaken to determine objective weights for TOPSIS.
1. Introduction: Outlines the importance of Venture Capital for technology commercialization and identifies the need for an objective, multi-criteria measurement tool to evaluate VCF financial performance.
2. Literature Review: Discusses existing procedures for measuring VCF performance, reviews MCDM methodologies, and introduces the TOPSIS approach and its modified version with objective weights.
3. Methodology: Explains the mathematical steps of mTOPSISow, the integration of Spearman's rank correlation, and justifies the selection of specific Financial Performance Indicators.
4. Testing the methodology: Details the practical application of the mTOPSISow model to a sample of five German VCFs, providing results, rankings, and a discussion of the impacts of chosen financial ratios.
5. Conclusion: Summarizes the study’s findings regarding the performance of the examined VCFs and suggests directions for future research, including larger sample sizes and the integration of non-financial indicators.
Venture Capital Firm, Financial Performance Indicator, TOPSIS, Multi-Criteria Decision Making, MCDM, Statistical Dependence, mTOPSISow, Corporate Financial Performance, Performance Ranking, Objective Weights, Entropy Concept, Spearman's Rank Correlation, Financial Ratios, Technology Commercialization, Business Engineering.
The research focuses on investigating the relative corporate financial performance of Venture Capital Firms (VCFs) using a structured, quantitative analytical approach.
Key themes include the application of Multi-Criteria Decision Making (MCDM), objective performance evaluation, the use of financial ratios, and the comparative analysis of German Venture Capital Firms.
The goal is to develop and apply a modified TOPSIS methodology with objective weights to rank VCFs accurately and identify which financial metrics most heavily influence their performance.
The study utilizes the "modified TOPSIS with objective weights" (mTOPSISow) methodology combined with Spearman's rank correlation to derive objective performance rankings.
The main body covers a literature review of VCF performance measurement, the technical description of mTOPSISow, the selection of specific Financial Performance Indicators (ROE, Asset Turnover, etc.), and the empirical testing of the methodology on real-world data.
The work is characterized by terms such as Venture Capital Firm, TOPSIS, Multi-Criteria Decision Making, objective weights, and Financial Performance Indicators.
It is preferred because it eliminates subjective bias in the weighting of criteria, which is a common shortcoming in traditional performance evaluation methods used for VCFs.
The model integrates Return on Equity (ROE), Asset Turnover (AT), Current Ratio (CR), and a transformed Debt-to-Equity Ratio (DER').
The case study reveals a significant performance discrepancy among the five examined German VCFs, with only one firm identified as high-performing relative to the others.
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