Disposition effect and multi-asset market dynamics

2019 ◽  
Vol 11 (2) ◽  
pp. 144-164
Author(s):  
Heba M. Ezzat
Keyword(s):  
Asset Pricing ◽  
Financial Markets ◽  
Switching Behavior ◽  
Asset Markets ◽  
Disposition Effect ◽  
Stylized Facts ◽  
Content Type ◽  
Agent Based ◽  
Multiple Assets ◽  
Pricing Dynamics

Purpose Asset pricing dynamics in a multi-asset framework when investors’ trading exhibits the disposition effect is studied. The purpose of this paper is to explore asset pricing dynamics and the switching behavior among multiple assets. Design/methodology/approach The dynamics of complex financial markets can be best explored by following agent-based modeling approach. The artificial financial market is populated with traders following two heterogeneous trading strategies: the technical and the fundamental trading rules. By simulation, the switching behavior among multiple assets is investigated. Findings The proposed framework can explain important stylized facts in financial time series, such as random walk price dynamics, bubbles and crashes, fat-tailed return distributions, absence of autocorrelation in raw returns, persistent long memory of volatility, excess volatility, volatility clustering and power-law tails. In addition, asset returns possess fractal structure and self-similarity features; though the switching behavior is only allowed among the asset markets. Practical implications The model demonstrates stylized facts of most real financial markets. Thereafter, the proposed model can serve as a testbed for policy makers, scholars and investors. Originality/value To the best of knowledge, no research has been conducted to introduce the disposition effect to a multi-asset agent-based model.

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.

scholarly journals Behavioral agent-based framework for interacting financial markets

2020 ◽  
Vol 5 (2) ◽  
pp. 94-115
Author(s):  
Heba M. Ezzat
Keyword(s):  
Financial Markets ◽  
Trading Strategy ◽  
Past Performance ◽  
Time Step ◽  
Monetary Policies ◽  
Content Type ◽  
Agent Based ◽  
Market Makers ◽  
Novel Approach ◽  
Excess Volatility

Purpose This paper aims at developing a behavioral agent-based model for interacting financial markets. Additionally, the effect of imposing Tobin taxes on market dynamics is explored. Design/methodology/approach The agent-based approach is followed to capture the highly complex, dynamic nature of financial markets. The model represents the interaction between two different financial markets located in two countries. The artificial markets are populated with heterogeneous, boundedly rational agents. There are two types of agents populating the markets; market makers and traders. Each time step, traders decide on which market to participate in and which trading strategy to follow. Traders can follow technical trading strategy, fundamental trading strategy or abstain from trading. The time-varying weight of each trading strategy depends on the current and past performance of this strategy. However, technical traders are loss-averse, where losses are perceived twice the equivalent gains. Market makers settle asset prices according to the net submitted orders. Findings The proposed framework can replicate important stylized facts observed empirically such as bubbles and crashes, excess volatility, clustered volatility, power-law tails, persistent autocorrelation in absolute returns and fractal structure. Practical implications Artificial models linking micro to macro behavior facilitate exploring the effect of different fiscal and monetary policies. The results of imposing Tobin taxes indicate that a small levy may raise government revenues without causing market distortion or instability. Originality/value This paper proposes a novel approach to explore the effect of loss aversion on the decision-making process in interacting financial markets framework.

scholarly journals Traders’ Networks of Interactions and Structural Properties of Financial Markets: An Agent-Based Approach

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Linda Ponta ◽  
Silvano Cincotti
Keyword(s):  
Stock Market ◽  
Financial Markets ◽  
Market Maker ◽  
Clearing House ◽  
Stylized Facts ◽  
Risky Assets ◽  
Agent Based ◽  
Price Process ◽  
Different Types ◽  
Artificial Stock Market

An information-based multiasset artificial stock market characterized by different types of stocks and populated by heterogeneous agents is presented and studied so as to determine the influences of agents’ networks on the market’s structure. Agents are organized in networks that are responsible for the formation of the sentiments of the agents. In the market, agents trade risky assets in exchange for cash and share their sentiments by means of interactions that are determined by sparsely connected graphs. A central market maker (clearing house mechanism) determines the price process for each stock at the intersection of the demand and the supply curves. A set of market’s structure indicators based on the main single-assets and multiassets stylized facts have been defined, in order to study the effects of the agents’ networks. Results point out an intrinsic structural resilience of the stock market. In fact, the network is necessary in order to archive the ability to reproduce the main stylized facts, but also the market has some characteristics that are independent from the network and depend on the finiteness of traders’ wealth.

scholarly journals Loss Aversion, Adaptive Beliefs, and Asset Pricing Dynamics

2015 ◽  
Vol 2015 ◽  
pp. 1-18 ◽  
Author(s):  
Kamal Samy Selim ◽  
Ahmed Okasha ◽  
Heba M. Ezzat
Keyword(s):  
Asset Pricing ◽  
Financial Market ◽  
Power Law ◽  
Loss Aversion ◽  
Asset Price ◽  
Belief System ◽  
Past Performance ◽  
Agent Based ◽  
Pricing Dynamics ◽  
Evolutionary Fitness

We study asset pricing dynamics in artificial financial markets model. The financial market is populated with agents following two heterogeneous trading beliefs, the technical and the fundamental prediction rules. Agents switch between trading rules with respect to their past performance. The agents are loss averse over asset price fluctuations. Loss aversion behaviour depends on the past performance of the trading strategies in terms of an evolutionary fitness measure. We propose a novel application of the prospect theory to agent-based modelling, and by simulation, the effect of evolutionary fitness measure on adaptive belief system is investigated. For comparison, we study pricing dynamics of a financial market populated with chartists perceive losses and gains symmetrically. One of our contributions is validating the agent-based models using real financial data of the Egyptian Stock Exchange. We find that our framework can explain important stylized facts in financial time series, such as random walk price behaviour, bubbles and crashes, fat-tailed return distributions, power-law tails in the distribution of returns, excess volatility, volatility clustering, the absence of autocorrelation in raw returns, and the power-law autocorrelations in absolute returns. In addition to this, we find that loss aversion improves market quality and market stability.

Do farmers exhibit disposition effect? Evidence from grain markets

2014 ◽  
Vol 40 (5) ◽  
pp. 487-505 ◽  
Author(s):  
Fabio L. Mattos ◽  
Stefanie A. Fryza
Keyword(s):  
Financial Markets ◽  
Reference Price ◽  
Marketing Strategies ◽  
Disposition Effect ◽  
Complete Understanding ◽  
Content Type ◽  
Agricultural Industry ◽  
Grain Markets ◽  
Grain Marketing ◽  
Early Farmers

Purpose – The purpose of this paper is to explore the existence of disposition effect among Canadian wheat farmers when marketing their grain. This study examines the question of whether farmers wait too long to price their grain or whether they price it too soon. Design/methodology/approach – The disposition effect is a common behavior documented in financial markets, and reflects the notion that investors tend to hold losing positions too long and close winning positions too fast. This idea can also be applied to grain marketing, exploring whether farmers sell their grain more readily when prices are “high” and wait longer when prices are “low.” Based on the approach by Odean (1998), marketing strategies of 15,564 farmers between 2003/2004 and 2008/2009 are examined. Findings – Results support the existence of disposition effect in marketing decisions. Farmers seem to be eager to sell when prices offered by contracts are above their reference price and wait longer to sell when prices offered by contracts are below their reference price. There is no clear evidence that farmers might consistently benefit from this behavior. On the other hand, it is not clear whether this behavior can be costly to farmers. Originality/value – Exploring the existence of disposition effect is relevant because this behavior can affect performance. If grain is sold too early, farmers can miss opportunities to sell at higher prices later. If grain is held too long, prices can go down and farmers will end up selling at lower prices. This study uses unique data to perform the first analysis of the disposition effect in the agricultural industry, and its findings can provide new insights and move us toward a more complete understanding of decision making in this industry.

scholarly journals Agent-based risk management – a regulatory approach to financial markets

2015 ◽  
Vol 42 (5) ◽  
pp. 780-820 ◽  
Author(s):  
Thomas Theobald
Keyword(s):  
Financial Markets ◽  
Behavioral Model ◽  
Capital Requirements ◽  
Regulatory Framework ◽  
Market Model ◽  
Content Type ◽  
Agent Based ◽  
No Arbitrage ◽  
Market Participants ◽  
Regulatory Approach

Purpose – The purpose of this paper is to provide market risk calculation for an equity-based trading portfolio. Instead of relying on the purely stochastic internal model method which banks currently apply in line with the Basel regulatory requirements, the author also propose including alternative price mechanisms from the financial literature in the regulatory framework. Design/methodology/approach – For this purpose, a financial market model with heterogeneous agents is developed, capturing the realistic feature that parts of the investors do not follow the assumption of no arbitrage, but are motivated by behavioral heuristics instead. Findings – Although both the standard stochastic and the behavioral model are restricted to a calibration including the last 250 trading days, the latter is able to capitalize possible turbulence on financial markets and likewise the well-known phenomenon of excess volatility – even if the last 250 days reflect a non-turbulent market. Practical implications – Thus, including agent-based models in the regulatory framework could create better capital requirements with respect to their level and counter-cyclicality. Originality/value – This in turn could reduce the extent to which bubbles arise, since market participants would have to anticipate comprehensively the costs of such bubbles bursting. Furthermore, a key ratio is deduced from the agent-based construction to lower the influence of speculative derivatives.

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