Choosing crop rotations under uncertainty: A multi-period dynamic portfolio optimization approach

科研成果详情

题名	Choosing crop rotations under uncertainty: A multi-period dynamic portfolio optimization approach
作者	Lee，Geoffrey; Bao，Chenming; Langrene，Nicolas; Zhu，Zili
发表日期	2015
会议录名称	Proceedings - 21st International Congress on Modelling and Simulation, MODSIM 2015
页码	1084-1090
摘要	To achieve good crop yields, farmers are aware of the importance of good rainfall during the growing season. However, their choice of crop to plant may not necessarily be the optimal choice when climate uncertainty exists. Indeed, current cropping allocations may be driven more by historical trends and tradition than by the future forecasts of climate scenarios and commodity prices. In a digital agricultural future, farmers may instead use information on crop yields and water usage to make cropping decisions each year that optimize their cash flow under the uncertainty of climate conditions and commodity prices. In this paper, we apply dynamic portfolio optimization techniques to the development of a simulation-based numerical method for making dynamic optimal cropping decisions. This method relies on a backwards recursive approach developed to solve the American option pricing problem. At each time step backwards from the end of the decision time period, the optimal expected future cash flow, or the so-called continuation function, is determined by using the Least Squares Monte Carlo method. As an example, we use a representative farm in Australia with four paddocks that can grow wheat, rice, barley and canola, and we also regard the corresponding commodity prices as stochastic variables. We compute the optimal crop rotations each year under different rainfall scenarios that maximise the expected utility over a fixed time period of 20 years. We evaluate the performance of the dynamic cropping strategies by comparing the expected value and standard deviation of future cash flows against those generated from static cropping strategies.
关键词	Approximate stochastic dynamic programming Crop rotation Least-squares Monte Carlo Portfolio optimization Rainfall
URL	查看来源
语种	英语English
Scopus入藏号	2-s2.0-85080897261
引用统计
文献类型	会议论文
条目标识符	https://repository.uic.edu.cn/handle/39GCC9TT/9659
专题	个人在本单位外知识产出
作者单位	Digitial Productivity Flagship,CSIRO,
推荐引用方式 GB/T 7714	Lee，Geoffrey,Bao，Chenming,Langrene，Nicolaset al. Choosing crop rotations under uncertainty: A multi-period dynamic portfolio optimization approach[C], 2015: 1084-1090.