This research investigates the presence and impact of cognitive biases on the investment choices of venture capitalists, with a particular focus on identifying which biases significantly affect their decision-making processes.

A survey questionnaire was designed and administered to a sample of 93 venture capitalists in Hong Kong and Singapore, drawn from diverse backgrounds and experiences within the investment industry.

The survey instrument was designed to elicit responses related to cognitive biases and funding decisions. To achieve the research objectives, the study employed multiple linear regression analysis to quantitatively assess the relationships between various cognitive biases and investment decisions. One-way Analysis of Variance (NOVA) was performed to assess the differences between different groups based on their investment experience, the type of fund they work for and past investment performance. The analysis aimed to confirm or refute the hypothesis that certain cognitive biases significantly influence venture capitalists' investment choices.

My research shows that most venture capitalists are susceptible to representativeness, anchoring and adjustment, endowment, similarity bias, and herd behavior. However, investors do not seem to exhibit confirmation, mental accounting, availability, outcome, regret behavior, and local bias. In addition, my research confirms that investors who exhibit confirmation bias, representativeness, anchoring and adjustment, outcome, and local bias tend to invest more than non-biased investors. Conversely, investors who exhibit endowment effect, tend to invest less than non-biased investors.

In terms of moderating effects, my results suggest that years of experience have no significant effect on investment decisions. When comparing across different types of venture capital funds, my results suggest that corporate venture capital funds tend to invest more than other funds when mental accounting or endowment is observed, while they seem to invest less when representativeness is at play. Government venture capital funds seem to invest more than other funds when subject to representativeness, but invest less when mental accounting, availability bias, or endowment effect are observed.

Finally, my study seems to confirm that venture capitalists with historically high investment performance tend to invest more than poor performers when local bias is present, and to invest less when endowment effect is observed.

The findings of this study offer valuable insights into the cognitive processes behind investment decisions in the venture capital industry. Understanding the presence and impact of cognitive biases in this context has practical implications for both venture capitalists and entrepreneurs seeking funding. By shedding light on the specific biases that influence venture capitalists, this research contributes to a deeper comprehension of decision-making processes within the venture capital sector.

Ultimately, this thesis provides a foundation for further research in behavioral finance and investment decision-making, emphasizing the importance of addressing cognitive biases in the pursuit of better-informed and more rational investment choices in the dynamic and high-stakes world of venture capital.