Risk Assessment,Transmission And Early-warning System In Agricultural Futures Market: Based On Price Bubble Detection Model

Since the beginning of the 21 st century,Chinese commodity futures markets have been developing rapidly with a growing number of futures contracts,trading volume and participation rate.From the perspective of trading volume,Chinese futures market has become the largest one in the world.Agricultural futures contracts are the earliestestablished and most actively-traded ones,thus playing an important role in Chinese futures market.During the last decade,Chinese agricultural commodity prices were highly volatile and risky.Large price volatility in agricultural products has been a potential threat to national food security and macroeconomic development.Hence,it is of practical importance to assess the historical price risk,to investigate the price transmission mechanism and set up a risk early-warning system for Chinese agricultural futures market.Currently,the significant feature of Chinese agricultural futures market is the occasionally-happened price bubble events and the associated extreme price risk.Thus,this paper aims to propose a new method to assess and study the bubble risk in Chinese agricultural futures market,based on price bubble theory and detection model.And it develops an analytical framework to study three aspects of risk analysis: risk assessment,risk transmission and risk early-warning.For risk assessment,it creates three risk indicators to assess the historical risk level based on bubble detection results,providing a basis to study the risk transmission mechanism and the risk early-warning system.For risk transmission,it distinguishes “bubble period” and “non-bubble period” based on bubble detection results,and further investigates the price transmission mechanism during “bubble-period” and “none-bubble period”.For risk early-warning,this paper further develops an early-warning system based on real-time bubble detection model.Below,we briefly summarize the main findings and conclusions in this paper.First,it proposes a new method for risk assessment in agricultural futures market based on bubble detection model,and empirically assesses the historical risk level in Chinese and international agricultural futures markets during the period 2006-2014.(1)Based on the bubble detection results,it creates three risk indices,namely bubble length,bubble frequency and bubble strength,to empirically study the historical risk for 10 major commodities traded in Chinese futures market during the period 2006-2010.Results show that 10 commodities can be categorized into 3 risk groups(high,medium and low),and each group has common risk feature within the group.Those results provide meaningful implication for risk management issues in practice.(2)It compares the risk difference between Chinese and international agricultural commodity market.Based on the risk indices,it shows that Chinese market and international market have “double difference”: the historical risk level differs both across markets and across commodities(Chinese high self-sufficiency commodities versus low self-sufficiency commodities).Then,we explain the difference from the perspective of domestic government intervention.China's special price-support policies and trade limits potentially resulted in the different price distributions in domestic and international markets.(3)It investigates the macroeconomic determinants of price bubble across markets.This paper proposes a new “two-step” method,which first measures the extend of price bubbles across markets,and then analyze its macroeconomic determinants using a Zeroinflated Poisson Model.Results show that economic growth,money supply and inflation have positive effects on bubble occurrences,while interest rates have a negative effect.Through simulations,it finds that the effects of macroeconomic factors on commodity price bubbles are asymmetric and complex.Second,it investigates the risk transmission relationship between Chinese agricultural futures market and spot market during “bubble period” and “nonebubble period”.Taking soybean as an example,it first studies the mean spillover effect and volatility spillover effect during “none-bubble period” in 2008-2014.VAR-BEKK-GARCH models show that there are bidirectional mean spillover effects and volatility spillover effects between Chinese agricultural futures market and spot market during “none-bubble period”.Then,it further develops a cointegration model for mild explosive regressors to study the price transmission relationship during “bubble period” in 2007-2008.Results show that(a)both futures price and spot price sequences in Chinese soybean market are mildly explosive during the “bubble period”;(b)soybean futures price and spot price are cointegrated during the bubble period in 2007-2008,and spot price tends to move more aggressively than futures price.It implies that,during 2008 world food crisis,food shortage information in the international market triggered larger panic and speculative trading in Chinese spot market.To the extent that avoiding price bubbles is seen as desirable,this finding seems to be a significant challenge for both policy-makers and market participants to reduce the probabilities of serious bubble events in Chinese agricultural spot market.Third,it builds up a risk early-warning system for Chinese agricultural futures market.Based on the double-recursive regression and right-tail unit root test,this paper develops a real-time bubble detection model for agricultural futures market.Then it shows the good property to use the real-time bubble detection model as risk early-warning system in agricultural futures market.Due to the ex anti detection procedure,risk earlywarning system can be built with appropriate setting of risk waring standard,response mechanism and application procedure.At last,it applies the risk early-warning system to Chinese cotton futures market.The results indicate that it is a feasible and flexible tool to build the risk early-warning system based on the real-time bubble detection model in Chinese agricultural futures market.The main contribution of this dissertation can be summarized as following: it proposes a new method to assess and study bubble risk in Chinese agricultural futures market based on right-tail bubble detection model,and develops a research framework covering risk assessment,risk transmission and risk early-warning with an application in Chinese agricultural futures market during the period 2006-2014.