Study Of Futures Price Dynamics Based On Heterogeneous Traders

Commodity futures market is one of the most important sections in national financial system, and it has great influence on international commodity pricing system. As our country's market economy develops, the need for servicing national economy and forming influenced'China price'become more and more important. In theory, commodity price moves based on related spot price and is restricted to underlying asset price. But empirical evidence demonstrates that underlying asset price cannot explain commodity futures price volatility at all. One of the questions is the homogeneity and rationality assumption about traders in financial market. This paper does research about this question, and it is aimed to perfect futures price formation theory, deeply understand the rules of futures price volatility, and provide reference to market administrators.This paper firstly review the literature about'bounded rationality'and'futures price formation theory'. Then this paper perceives the cause of futures price volatility from the rational and heterogeneous trader point. Trader's behavior governs the market price dynamics. So the central question is to understand traders in market. This paper comment agent-based financial simulation market research. Based on this work, exploring futures price dynamics from trader's micro-behavior is proposed. This paper constructs an agent-based model of a futures market to explore the characters of commodity futures markets price dynamics.First start analyzing the notion'rationality'and'bounded rationality'in economics and social science, then using four dimensions, include'belief','risk preference','confidence degree'and'time horizon'to characterize heterogeneous traders and summarize the representative trading strategies in market to form'market belief set'. Classifying present learning models used in agent-based models to describe beliefs evolutionary process according psychology evidence attain the claim that constructing an individual and social learning with local information learning model is a better choice for futures market context. Based on psychology research and behavior finance theory, this paper improve the SBL model through adding imitation machine into model to describe herd behavior and construct futures market trader belief learning model?FTBL model. After this work, this paper moves on to analyze the futures market trading-machine, including price determination machine, marginal requirement, etc. This paper constructs artificial futures market with heterogeneous traders—HT-AFM model and designs the timing of the model according trading process in real futures market. In HT-AFM model, as trader's learning and adaptive process, market price constantly evaluates. The market price is generated by seal-bid machine.This paper use parameter and non-parameter statistics approach to testify'stylized facts'of commodity futures price and the results are compared with ones generated by HT-AFM to calibrate the model and to prove the efficiency of the model. With real spot market price as exogenous information, the model simulation can generate most of the stylized facts. At last, this paper proves the relationship between herd behavior and price volatility using Granger causal test, and analyzes the relationship between individual learning and social learning.