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清华大学学报(自然科学版)  2017, Vol. 57 Issue (4): 351-356    DOI: 10.16511/j.cnki.qhdxxb.2017.25.003
  水利水电工程 本期目录 | 过刊浏览 | 高级检索 |
基于集市型水权交易模型的报价行为
郑航1, 陈奔1, 林木2
1. 清华大学 水利水电工程系, 北京 100084;
2. 中央财经大学 统计与数学学院, 北京 100081
Bidding behavior in an optimal water trading model
ZHENG Hang1, CHEN Ben1, LIN Mu2
1. Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China;
2. School of Statistics and Mathematics, Central University of Finance and Economics, Beijing 100081, China
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摘要 水权交易是水资源使用权通过市场机制进行优化配置的重要方式,是水权制度建设的落脚点。该文以源于澳大利亚的集市型水权交易实践为基础,构建了水权交易的数学模型,对集市中交易者的报价行为进行了分析和研究。首先,基于交易风险和收益平衡,计算市场中交易者的综合收益,得出了集市型交易模式下参与者的最优报价策略,给出了报价策略与用水效益及预期报价的函数关系;其次,通过对比拆分订单报价的策略性行为对交易者综合收益的影响,分析了该报价行为的可行性和合理性,发现“拆单”可以有效利用市场机制,实现个人收益最大化;最后,通过求解买家博弈的均衡报价,发现增加信息披露有利于交易者报价更加接近其对水权的真实估价,提升了市场价格发现的有效性。模型分析和结论对中国水权交易制度建设提供了一定的参考。
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郑航
陈奔
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关键词 水权交易集市报价行为信息    
Abstract:China is developing its water rights drawing system based on water trading which is an important method to optimize allocations through the market mechanism. This article describes the mathematical model for pooled water trading and analyzes trader bidding behavior in the market. The trader income is also calculated based on balancing the trading risk and benefit. The best bidding strategy is selected to give the optimal income. Split bidding was also analyzed to show that split bidding increases the trader income. Furthermore, the effect of information transparency was also studied by solving for the game equilibrium between buyers with the result showing that increasing information disclosure improves the price discovery effectiveness in the market.
Key wordswater trading    market    bidding behavior    information
收稿日期: 2016-03-28      出版日期: 2017-04-15
ZTFLH:  F407.9  
引用本文:   
郑航, 陈奔, 林木. 基于集市型水权交易模型的报价行为[J]. 清华大学学报(自然科学版), 2017, 57(4): 351-356.
ZHENG Hang, CHEN Ben, LIN Mu. Bidding behavior in an optimal water trading model. Journal of Tsinghua University(Science and Technology), 2017, 57(4): 351-356.
链接本文:  
http://jst.tsinghuajournals.com/CN/10.16511/j.cnki.qhdxxb.2017.25.003  或          http://jst.tsinghuajournals.com/CN/Y2017/V57/I4/351
  表1 集市交易数据
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