摘要
提出了一种基于最小二乘法的长周期实物期权精确估值迭代模拟算法,并通过一个商用通信卫星在轨服务投资决策的算例对该算法的实现进行了说明.算法将一个需要一次进行大量运算的问题转变为一个需要进行多次运算但每次运算的计算量相对较小的问题,能够很好地解决在缺乏并行计算的条件下大量模拟运算所面临的计算资源瓶颈问题,不仅能够得到较为精确的实物期权价值的点估计值和区间估计值,也便于推导最优的投资策略.
Long-maturity is an marked character of real options, which makes it difficult to accurately estimate the value of real options by Monte Carlo simulation. This thesis puts forward an iterating algorithm based on least squares Monte Carlo simulation for accurate evaluation of long-maturity real options and demonstrates the resolving process by taking the decision-making of on-orbit upgrading of commercial communication satellites as a numerical example, the method transforms the question which requires heavy computation all at once into the question which requires many times of low-workload computation and thus overcomes well the bottleneck of computing resource confronted when intensified simulation is needed but the concurrent computing environment is not available. By the method posed by this thesis it is able to obtain the accurate point estimation and interval estimation of the value of real options with long-maturity, and also convenient to dram the optimal investment rules.
出处
《数学的实践与认识》
CSCD
北大核心
2013年第7期22-31,共10页
Mathematics in Practice and Theory
关键词
最小二乘法
长周期
实物期权
迭代
least squares
long-maturity
real options
iterating
