Understanding Financial Market States Using an Artificial Double Auction Market

Abstract

The ultimate value of theories describing the fundamental mechanisms behind asset prices in financial systems is reflected in the capacity of such theories to understand these systems. Although the models that explain the various states of financial markets offer substantial evidence from the fields of finance, mathematics, and even physics, previous theories that attempt to address the complexities of financial markets in full have been inadequate. We propose an artificial double auction market as an agent-based model to study the origin of complex states in financial markets by characterizing important parameters with an investment strategy that can cover the dynamics of the financial market. The investment strategies of chartist traders in response to new market information should reduce market stability based on the price fluctuations of risky assets. However, fundamentalist traders strategically submit orders based on fundamental value and, thereby stabilize the market. We construct a continuous double auction market and find that the market is controlled by the proportion of chartists, Pc. We show that mimicking the real state of financial markets, which emerges in real financial systems, is given within the range Pc = 0.40 to Pc = 0.85; however, we show that mimicking the efficient market hypothesis state can be generated with values less than Pc = 0.40. In particular, we observe that mimicking a market collapse state is created with values greater than Pc = 0.85, at which point a liquidity shortage occurs, and the phase transition behavior is described at Pc = 0.85.

Auctions for buying back groundwater for environmental purposes: Which design performs better?

“…The agents interact with the system and other agents based on a set of rules (Tesfatsion, 2003). The ABM approach has been used to explore different aspects of auction mechanism design in many sectors, including finance (Yim et al, 2016); energy (Anatolitis & Welisch, 2017); fisheries (Iftekhar & Tisdell, 2012); and conservation services procurement (Hailu & Schilizzi, 2004;Iftekhar & Tisdell, 2016). However, little research has been devoted to understanding the performance of water buyback auctions using ABM.…”