CRIEFF Discussion Paper Number 0206

Investor Conduct Towards New High Technology Firms: UK Evidence on How Risk is Managed

Gavin C Reid

Abstract

This paper uses statistical analysis to characterise ‘industry practice’, in terms of concordance of investors concerning appropriate practice. The evidence was gathered by field work methods in 2000-01, and refers to the practices of twenty UK venture capital investors, who accounted for the bulk of funds allocated to high technology investments in the UK. This paper has two parts: general and detailed statistical analysis. 1) In the first part, the main finding is of a coherent (and generally statistically significant picture) of investor conduct towards high-technology companies. Thus it is found that investors assign risk premia and expected values, and use risk classes. They adopt relatively short time horizons, but follow quite sophisticated procedures in investment appraisal. For example, they use sensitivity analysis, cash flow prediction, financial modelling, and decision trees. However, they miss out in some sophisticated areas of technical analysis, including Value at Risk (VaR), and simulation methods (including Monte Carlo methods). 2) The second part of the paper focuses on risk, factors influencing it, and innovation. Its aim is to discover if there is a kind of ‘industry standard’ or consensus about what is most important to investors in the high technology area. Largely, that turned out to be the case. The UK venture capitalists are agreed on what are high-risk and low-risk investments. They also agree on what are the key commercial factors affecting risk. However, when it comes to non-commercial factors, this consensus starts to crumble. Finally, so far as features of innovation are concerned, industry consensus starts to break down entirely. Thus, there do remain important areas in which investor practice is opaque. Therefore, there remains a need for further research into investor practice in the UK.

Key Words
Venture Capital, Risk Management, High-Technology, Fieldwork
JEL Classifications
G24, D81, L84, M21, L21

Gavin C. Reid
University of St Andrews

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