MULTI-AGENT BASED MODELING APPLIED TO PORTFOLIO SELECTION IN THE DOOM-LOOP OF SOVEREIGN DEBT CONTEXT*

• Main Authors: Paulo Sérgio Rosa, Ivan Ricardo Gartner, Célia Ghedini Ralha
• Format: Article
• Language: English
• Published: Sociedade Brasileira de Pesquisa Operacional 2019-05-01
• Series: Pesquisa Operacional
• Subjects: portfolio selection; agent-based model; sovereign debt; doom-loop; systemic risk
• Online Access: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382019000100003&lng=en&tlng=en

ABSTRACT This study explores the self-fulfilling dynamic between sovereign debt risk and rational choices of neutral, risk-seeking and risk-averse investors, with implications to the systemic risk emergence. The agent-based model parameterization includes investment strategy (randomly selected assets, stock exchange participation, economic segment, and technical analysis), portfolio rebalance period, and stop gain/loss option. We use Brazilian markets data from 2006 to 2017 to simulate stochastic distributions of investments by a set of 3,000 agents in both stages of model verification and validation (robustness check). Using the Capital Asset Pricing Model, we confirmed our proposition that the optimal rational risk attitude (less risk appetite) constitutes a trigger for the self-fulfilling dynamic, having its foundation on government securities yield and in the debt dynamics. This finding is contrary to the equity premium puzzle in the Brazilian case. The findings have implications to policymakers regarding systemic risk issues, among other public policies.