Analyzing the Influences of Passive Investment Strategies on Financial Markets via Agent-Based Modeling

2008 ◽  
pp. 224-238 ◽  
Author(s):  
Hiroshi Takahashi ◽  
Satoru Takahashi ◽  
Takao Terano
Keyword(s):  
Asset Pricing ◽  
Financial Markets ◽  
Financial Market ◽  
Investment Strategy ◽  
Agent Based Modeling ◽  
Investment Strategies ◽  
Agent Based Model ◽  
Efficient Market ◽  
Agent Based ◽  
Price Fluctuations

This chapter develops an agent-based model to analyze microscopic and macroscopic links between investor behaviors and price fluctuations in a financial market. This analysis focuses on the effects of Passive Investment Strategy in a financial market. From the extensive analyses, we have found that (1) Passive Investment Strategy is valid in a realistic efficient market, however, it could have bad influences such as instability of market and inadequate asset pricing deviations, and (2) under certain assumptions, Passive Investment Strategy and Active Investment Strategy could coexist in a Financial Market.

AN ANALYSIS OF THE INFLUENCE OF DISPERSION OF VALUATIONS ON FINANCIAL MARKETS THROUGH AGENT-BASED MODELING

2012 ◽  
Vol 11 (01) ◽  
pp. 143-166 ◽  
Author(s):  
HIROSHI TAKAHASHI
Keyword(s):  
Financial Markets ◽  
Financial Constraints ◽  
Investment Strategy ◽  
Agent Based Modeling ◽  
Investment Strategies ◽  
Market Prices ◽  
Agent Based ◽  
Short Sale Constraints ◽  
Short Sale ◽  
Fundamental Values

This research analyzes the influence of dispersion of valuations on financial markets, taking several aspects of real financial market into consideration (such as financial constraints, investment strategies and so on). As a result of intensive experiments in the market, we made the following findings: (1) Dispersion of fundamentalists' valuations has little effect on the market when financial constraints are absent; (2) When financial constraints — such as short-sale constraints — are introduced, certain situations arise in which deviations from fundamental values become larger, according to the level of the dispersion of valuations; (3) A passive investment strategy, as is consistent with traditional financial theory, is valid even when the introduction of financial constraints causes market prices to deviate significantly from fundamental values. These results contribute to clarifying the mechanism of price fluctuations in financial markets and are notable from both academic and practical view points.

Agent-Based Modeling Bridges Theory of Behavioral Finance and Financial Markets

2010 ◽  
pp. 134-155
Author(s):  
Hiroshi Takahashi ◽  
Takao Terano
Keyword(s):  
Decision Making ◽  
Asset Pricing ◽  
Financial Market ◽  
Behavioral Finance ◽  
Investment Strategy ◽  
Agent Based Modeling ◽  
Agent Based Models ◽  
Agent Based ◽  
Micro Level ◽  
Fundamental Values

This chapter describes advances of agent-based models to financial market analyses based on our recent research. We have developed several agent-based models to analyze microscopic and macroscopic links between investor behaviors and price fluctuations in a financial market. The models are characterized by the methodology that analyzes the relations among micro-level decision making rules of the agents and macro-level social behaviors via computer simulations. In this chapter, we report the outline of recent results of our analysis. From the extensive analyses, we have found that (1) investors’ overconfidence behaviors plays various roles in a financial market, (2) overconfident investors emerge in a bottom-up fashion in the market, (3) they contribute to the efficient trades in the market, which adequately reflects fundamental values, (4) the passive investment strategy is valid in a realistic efficient market, however, it could have bad influences such as instability of market and inadequate asset pricing deviations, and (5) under certain assumptions, the passive investment strategy and active investment strategy could coexist in a financial market.

scholarly journals An Analysis of the Influence of Fundamental Values' Estimation Accuracy on Financial Markets

2010 ◽  
Vol 2010 ◽  
pp. 1-17 ◽  
Author(s):  
Hiroshi Takahashi
Keyword(s):  
Financial Markets ◽  
Financial Market ◽  
Asset Management ◽  
Forecast Accuracy ◽  
Investment Strategy ◽  
Estimation Accuracy ◽  
Price Fluctuations ◽  
Passive Management ◽  
Passive Investors ◽  
Fundamental Values

This research analyzed the influence of the differences in the forecast accuracy of fundamental values on the financial market. As a result of intensive experiments in the market, we made the following interesting findings: (1) improvements in forecast accuracy of fundamentalists can contribute to an increase in the number of fundamentalists; (2) certain situations might occur, according to the level of forecast accuracy of fundamentalists, in which fundamentalists and passive management coexist, or in which fundamentalists die out of the market, and furthermore; (3) where a variety of investors exist in the market, improvements in the forecast accuracy could increase the number of fundamentalists more than the number of investors that employ passive investment strategy. These results contribute to clarifying the mechanism of price fluctuations in financial markets and also indicate one of the factors for the low ratio of passive investors in asset management business.

scholarly journals Toward a better understanding of team decision processes: combining laboratory experiments with agent-based modeling

2021 ◽  
Author(s):  
Iris Lorscheid ◽  
Matthias Meyer
Keyword(s):  
Laboratory Experiment ◽  
Mixed Method ◽  
Agent Based Modeling ◽  
Decision Processes ◽  
Mixed Method Research ◽  
Team Cognition ◽  
Agent Based Model ◽  
Agent Based ◽  
Individual Level ◽  
Team Decision

AbstractDespite advances in the field, we still know little about the socio-cognitive processes of team decisions, particularly their emergence from an individual level and transition to a team level. This study investigates team decision processes by using an agent-based model to conceptualize team decisions as an emergent property. It uses a mixed-method research design with a laboratory experiment providing qualitative and quantitative input for the model’s construction, as well as data for an output validation of the model. First, the laboratory experiment generates data about individual and team cognition structures. Then, the agent-based model is used as a computational testbed to contrast several processes of team decision making, representing potential, simplified mechanisms of how a team decision emerges. The increasing overall fit of the simulation and empirical results indicates that the modeled decision processes can at least partly explain the observed team decisions. Overall, we contribute to the current literature by presenting an innovative mixed-method approach that opens and exposes the black box of team decision processes beyond well-known static attributes.

Agent-based economic models and econometrics

2012 ◽  
Vol 27 (2) ◽  
pp. 187-219 ◽  
Author(s):  
Shu-Heng Chen ◽  
Chia-Ling Chang ◽  
Ye-Rong Du
Keyword(s):  
Financial Markets ◽  
Agent Based Modeling ◽  
Computational Finance ◽  
Agent Based ◽  
Second Stage ◽  
The Past ◽  
Stage Development ◽  
Three Stages ◽  
The One ◽  
Two Stages

AbstractThis paper reviews the development of agent-based (computational) economics (ACE) from an econometrics viewpoint. The review comprises three stages, characterizing the past, the present, and the future of this development. The first two stages can be interpreted as an attempt to build the econometric foundation of ACE, and, through that, enrich its empirical content. The second stage may then invoke a reverse reflection on the possible agent-based foundation of econometrics. While ACE modeling has been applied to different branches of economics, the one, and probably the only one, which is able to provide evidence of this three-stage development is finance or financial economics. We will, therefore, focus our review only on the literature of agent-based computational finance, or, more specifically, the agent-based modeling of financial markets.

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