MERGER AND ACQUISITION PRICING USING AGENT BASED MODELLING
NIPUN AGARWAL, PAUL KWAN, DAVID PAULABSTRACT. Merger & Acquisition pricing utilises traditional financial models like Discount Cash flow analysis and industry multiples. These methods do not consider behaviour finance biases, for example, prospect theory (Kahneman and Tversky 1979). This paper analyses merger & acquisition pricing using behavioural bias of risk aversion (acquiring company behavioural trait) and optimism (target company trait). It then extends the study to include loss aversion from prospect theory, differences in the way humans view gains and losses based on low or high probability based on cumulative prospect theory, and finally the certainty effect (where humans prefer certain outcome to probabilistic outcomes). All these factors have an impact on merger & acquisition pricing for potential deals as acquiring and target companies behave differently and such impacts are not considered by traditional finance models. Results show that as loss aversion reduces, the positive impact of risk taking and optimism behaviours improve. Also, probabilistic gains and losses can have a positive impact, but certainty has the greatest impact. Humans prefer certain outcomes and acquirers and target company behaviours are more effective in such conditions with increasing utility for both parties under such circumstances. However, in the multiple acquirer setting, competition between the acquirer significantly increases the utility, and the loss aversion co-efficient works in the opposite direction as the perceptive difference between gains and losses decreases.
JEL codes: G34; L11
Keywords: price; mergers and acquisitions (M&A); agent-based modeling
How to cite: Agarwal, Nipun, Paul Kwan, and David Paul (2018). “Merger and Acquisition Pricing Using Agent Based Modelling,” Economics, Management, and Financial Markets 13(1): 84–99.
Received 14 November 2017 • Received in revised form 11 December 2017
Accepted 12 December 2017 • Available online 5 January 2018
doi:10.22381/EMFM13120184