Modeling an Artificial Stock Market
نویسندگان
چکیده
This chapter presents an artificial stock market created to analyze market dynamics from the behavior of investors. It argues that information—delivered by financial intermediaries as rating agencies and considered as cognitive institution—directs the decisions of investors who are heterogeneous agents endowed with capabilities of learning in a changing environment. The objective is to demonstrate that information influences market dynamics as it allows the coordination of the decisions of investment in the same direction: information is a focal point for investors and contributes to generate a speculative dynamic on the market.
منابع مشابه
Stock Market Modeling Using Artificial Neural Network and Comparison with Classical Linear Models
Stock market plays an important role in the world economy. Stock market customers are interested in predicting the stock market general index price, since their income depends on this financial factor; Therefore, a reliable forecast in stock market can be extremely profitable for stockholders. Stock market prediction for financial markets has been one of the main challenges in forecasting finan...
متن کاملAn Analysis of Existing Artificial Stock Market Models for Representing Bombay Stock Exchange (bse)
The goal of agent-based modeling of stock markets is to enrich our understanding of fundamental processes that appear in a market. Artificial stock markets are models of financial markets used to study and understand market dynamics. Agent Based Artificial Stock Markets can be seen as any market model in which prices are formed endogenously as a result of participants’ interaction. There are va...
متن کاملModeling Stock Market Exchange Prices Using Artificial Neural Network: A Study of Amman Stock Exchange
Stock market represents an essential part of the economy in the Middle East, it is significant for shareholders and investors to estimate the stock price and select the best trading opportunity accurately in advance. This paper utilizes artificial neural network in the modeling of stock market exchange prices. The network was trained using supervised learning. Simulation was conducted for seven...
متن کاملModeling Stock Market Volatility Using Univariate GARCH Models: Evidence from Bangladesh
This paper investigates the nature of volatility characteristics of stock returns in the Bangladesh stock markets employing daily all share price index return data of Dhaka Stock Exchange (DSE) and Chittagong Stock Exchange (CSE) from 02 January 1993 to 27 January 2013 and 01 January 2004 to 20 August 2015 respectively. Furthermore, the study explores the adequate volatility model for the stoc...
متن کاملModeling Stock Market Based on Genetic Cellular Automata
An artificial stock market is established with the modeling method and ideas of cellular automata. Cells are used to represent stockholders, who have the capability of self-teaching and are affected by the investing history of the neighboring ones. The neighborhood relationship among the stockholders is the expanded Von Neumann relationship, and the interaction among them is realized through se...
متن کاملForecasting Stock Market Using Wavelet Transforms and Neural Networks: An integrated system based on Fuzzy Genetic algorithm (Case study of price index of Tehran Stock Exchange)
The jamor purpose of the present research is to predict the total stock market index of Tehran Stock Exchange, using a combined method of Wavelet transforms, Fuzzy genetics, and neural network in order to predict the active participations of finance market as well as macro decision makers.To do so, first the prediction was made by neural network, then a series of price index was decomposed by w...
متن کامل