Masterarbeit, 2021
77 Seiten, Note: 8.1/10
CHAPTER 1: INTRODUCTION
1.1 Venture Capital
1.2 Index
1.3 Mutual Funds
1.4 Venture Capital Index background
1.4.1 Thomson Reuters Post Venture Capital Index (PVCINDX)
1.4.2 Thomson Reuters Research & VC index (TRVCINX)
1.5 Relevance
1.6 Research Objectives
1.7 Research Question
1.8 Summary
CHAPTER 2: LITERATURE REVIEW
2.1 Venture Capital returns
2.2 Mutual Fund Performance
2.2.1 The Sharpe Ratio
2.2.2 Jensen’s Alpha
2.3 The efficient market hypothesis
2.4 Hypotheses
CHAPTER 3: METHODOLOGY
3.1 Research Design
3.2 Data sources
3.3 Methodology
3.3.1 The Sharpe Ratio
3.3.2 Jensen’s Alpha
CHAPTER 4: RESULTS & DISCUSSIONS
4.1 Absolute Performance:
4.2 Sharpe findings:
4.2.1 Monthly Sharpe Ratio findings
4.2.2 Annual Sharpe Ratio findings
4.3 CAPM & Jensen’s Alpha findings:
4.3.1 Thomson Reuters Venture Capital Index (TRVCINX) Regression findings
4.3.2 Thomson Reuters Post Venture Capital Index (PVCINDX) Regression findings
4.3.3 Macroeconomic impact on VC Index Regression findings
4.4 Hypothesis discussion
4.4.1 H1: The Venture Capital indices gross returns will exhibit lesser Sharpe ratio’s than the Market benchmarks
4.4.2 H2: The Venture Capital indices net returns will exhibit lesser Sharpe ratio’s than the Market benchmarks
4.4.3 H3: The Venture Capital indices gross returns will exhibit no positive alpha when regressed against Market Benchmarks returns
4.4.4 H4: The Venture Capital indices net returns will exhibit no positive alpha when regressed against Market Benchmarks returns
CHAPTER 5: CONCLUSIONS, DISCUSSIONS AND RECOMMENDATIONS
This study aims to critically examine the performance of publicly traded Venture Capital (VC) indices to determine if they provide more attractive risk-adjusted returns compared to broad market indices, effectively addressing a gap in existing literature regarding their efficacy.
1.4.2 Thomson Reuters Research & VC index (TRVCINX)
The TRVCINX aims to track the Thomson Reuters VC research index in turn the former index construction methodology will be discussed before diving into how the VC index aims to track it and or emulate its risk/return characteristics.
The Thomson Reuters VC research index is constructed using TR’s extensive VC and Private equity (PE) data base. Concretely the research index looks at over 22,000 venture backed firms, for which a wide variety of variables are gathered. Of relevance are post and pre money valuation dat. Where post money refers to the valuation of the firm after a funding event and pre money refers to the valuation of the firm prior to a funding event The resulting data is then cleaned of any duplicates and invalid entries. It is of note that while every round is accounted for only initial exit values are the values of interest. For companies which reach their initial public offering (IPO) post offer value is used as the valuation metric. Where post offer value refers to the value of the firm after its IPO rather similarly to a post money valuation for private firms. (Thomson Reuters (Refinitv), 2019a)
In order to adjust for any missing acquisition values a linear regression is run across the entire data set while index returns are restated every 8 months using the newly available historical return data. In turn the return data set is ever expanding. However, this approach allow is insufficient as it does not account for missing valuation rounds. (Thomson Reuters (Refinitv), 2019a)
CHAPTER 1: INTRODUCTION: Provides the research background, defines the Venture Capital indices under study, and outlines the core research question.
CHAPTER 2: LITERATURE REVIEW: Reviews existing studies on VC returns, mutual fund performance, performance metrics, and the efficient market hypothesis.
CHAPTER 3: METHODOLOGY: Details the research design, data sources from DataStream and CRSP, and the mathematical implementation of the Sharpe ratio and Jensen's Alpha.
CHAPTER 4: RESULTS & DISCUSSIONS: Presents the empirical findings on index performance and provides a critical discussion of the results against the formulated hypotheses.
CHAPTER 5: CONCLUSIONS, DISCUSSIONS AND RECOMMENDATIONS: Synthesizes the core findings, addresses the limitations of the sample size, and makes suggestions for future empirical research.
Venture Capital, Index Performance, Sharpe Ratio, Jensen's Alpha, Mutual Funds, Efficiency, Market Benchmarks, TRVCINX, PVCINDX, Risk-Adjusted Returns, Private Equity, Performance Attribution, Financial Econometrics, Regression Analysis, Portfolio Management.
This thesis examines the financial performance of publicly traded Venture Capital (VC) indices, specifically exploring whether these instruments can provide competitive risk-adjusted returns compared to traditional market benchmarks.
The study focuses on two particular indices managed by Thomson Reuters (Refinitiv): the Thomson Reuters Venture Capital Index (TRVCINX) and the Post Venture Capital Index (PVCINDX).
The central research question is whether risk-adjusted returns of Venture Capital indices exceed those of broad market index benchmarks.
The analysis utilizes the Sharpe Ratio for measuring risk-adjusted returns and Jensen's Alpha (based on the Capital Asset Pricing Model) to evaluate performance relative to a market benchmark.
The main body covers a comprehensive literature review of VC and mutual fund performance, a detailed methodology for data collection and transformation, and an empirical analysis of regression results under various economic conditions.
The key themes revolve around Venture Capital, index performance, risk-adjusted metrics like the Sharpe Ratio and Jensen's Alpha, and the evaluation of effective portfolio management.
The empirical analysis reveals divergent outcomes: the TRVCINX demonstrates persistent outperformance of market benchmarks, while the PVCINDX exhibits significant underperformance throughout the observed period.
Yes, the inclusion of management and expense fees generally had a moderating effect on the returns; however, it did not change the relative performance rankings, as the TRVCINX's outperformance persisted even on a net-of-fee basis.
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