This body of work addresses a gap in financial and economic theories related to assets that are typically associated with high uncertainty. Specifically, this thesis provides some foundational work towards a new way to quantify and explain how high-risk high-reward activities, such as exploration, impact value creation within firms (e.d., R&D intensive small firms and oil and gas production and exploration firms). The novelty of the approach outlined in this thesis is that-unlike classical economic approaches- it is independent of assumptions about the mechanisms that governs the underlying assets and it provides a statistical model that is able to more accurately predict the frequency and size of large fluctuations. A data-driven approach is proposed, which provides an accurate model for the behaviour of high-risk high-reward assets related to exploration activities using probability theory and statistics. This results in a statistically significant description of this behaviour without making assumptions about the type of dynamics that lead to these movements (e.g., normal random walk) or an exact account of how the individual factors that contribute to value behave. A more accurate model of value creation associated with exploration activities will provide managers with better tools to support decision making, especially in entrepreneurial firms who must manage R&D in an environment characterized by limited resources.
|Award date||19 Jun 2014|
|Place of Publication||Enschede|
|Publication status||Published - 19 Jun 2014|