Loan Rate Pricing of SME Financing based on Agent-based Computational Finance Approach

2009 ◽  
Vol 29 (12) ◽  
pp. 9-14 ◽  
Author(s):  
Xiong XIONG ◽  
Cui GUO ◽  
Wei ZHANG ◽  
Yong-jie ZHANG
Keyword(s):  
Computational Finance ◽  
Agent Based ◽  
Loan Rate ◽  
Sme Financing

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.

scholarly journals Investor Sentiment and IPOs Anomalies: An Agent-Based Computational Finance

2017 ◽  
Vol 13 (12) ◽  
Author(s):  
Zhenwei Lv ◽  
Gaofeng Zou ◽  
Qiyuan Cheng ◽  
John Edmunds ◽  
Xiaopeng Zhai
Keyword(s):  
Investor Sentiment ◽  
Computational Finance ◽  
Agent Based

Application of Modeling and Simulation Based on Agent

2015 ◽  
Vol 740 ◽  
pp. 939-942
Author(s):  
Yan Hua Shao
Keyword(s):  
Modeling And Simulation ◽  
Adaptive System ◽  
Complex Adaptive System ◽  
Computational Finance ◽  
Competitive Behavior ◽  
Agent Based ◽  
Applied Model ◽  
Simulation Based ◽  
Complex Adaptive ◽  
Evolution Modeling

In order to solve the limitation of the research about enterprise evolution modeling and simulation, the idea of applying complex adaptive system theory and agent-based computational finance method to the enterprise research was proposed. Secondly, an applied model of Agent-based enterprise evolution was built. Finally, the simulation program of enterprise evolution based on swarm was built, which simulate the dynamic competitive behavior and evolvement of enterprise, the result of the simulation was analyzed.

CROSS-MARKET FINANCIAL RISK ANALYSIS: AN AGENT-BASED COMPUTATIONAL FINANCE

2011 ◽  
Vol 10 (03) ◽  
pp. 563-584 ◽  
Author(s):  
XIONG XIONG ◽  
MEI WEN ◽  
WEI ZHANG ◽  
YONG JIE ZHANG
Keyword(s):  
Stock Market ◽  
Futures Market ◽  
Market Volatility ◽  
Computational Finance ◽  
Future Market ◽  
Investment Strategies ◽  
Chinese Stock Market ◽  
Stock Market Volatility ◽  
Agent Based ◽  
Index Futures

Using the method of agent-based computational finance, this paper designs ten experiments to examine the impacts of the index futures market, typical investment strategies, and different trading mechanisms on the volatility of the Chinese stock market, taking into account the behavior of investors. We have the following results. First, the volatility of the stock market decreases with the index future market and cross-market arbitrageurs. Second, different investment strategies have different effects on stock market volatility. In many cases, both market-imitating and stop-loss strategies can increase stock market volatility. Third, the mechanism of price limits for the index futures market can help to stabilize the fluctuation of the stock market.

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