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Quantifying the concerns of Dimon and Buffett with data and computation

Matthew Oldham

Journal of Economic Dynamics and Control, 2020, vol. 113, issue C

Abstract: Despite considerable efforts, the determinants of firm growth and financial market volatility have not been definitively identified, yet sets of stylized facts – most notably power-law distributions – relating to firm size and market returns suggest both evolve as part of a complex system. This scenario implies that a positive feedback loop between firms and investors exists and may be responsible for prejudicing the way management allocates their resources, with firm, and economic, growth adversely affected. Further, there are growing real-world concerns that the management of publicly listed firms is becoming too concerned with the movement of their firm's share price, which is adversely influencing resource allocation decisions. A related concern is that agents, in general, within financial markets are placing a disproportionate focus on short-term factors. To investigate the ramifications of the proposed feedback loop on firm growth and market volatility, this paper implements a novel agent-based artificial stock market where management can consider the movements of their firm's endogenously determined share price when allocating resources between sales and margin growth. The results highlight an inferior outcome regarding firm growth, and various other financial metrics, if management is overly concerned with share price movements. The growth of the firms (and market) is also affected by the mixture of the investor classes initiated due to the divergent levels of volatility they create. Additionally, the model presents insights into how and why the extent to which agents consider past outcomes in their decision-making process becomes influential. Notably, the model's results emulate an extensive set of global micro-level firm data. By providing significant insights on the effects of the stock market on management decision-making and its ramifications for firm growth, this paper provides crucial insights into the mechanisms responsible for inefficient behavior by market participants.

Keywords: Agent-based modeling; Artificial stock markets; Complex adaptive systems; Efficient markets; Agency theory (search for similar items in EconPapers)
JEL-codes: C88 G12 G17 L10 L20 (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1016/j.jedc.2020.103864

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Journal of Economic Dynamics and Control is currently edited by J. Bullard, C. Chiarella, H. Dawid, C. H. Hommes, P. Klein and C. Otrok

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