中国是全球最大的棉花生产国和消费国，棉花产业的稳定发展对于保障国家农业经济安全、维护纺织品产业链稳定以及满足战略物资需求具有至关重要的战略意义。然而，棉花市场长期遭受价格剧烈波动的困扰，棉花价格的剧烈波动不仅直接挫伤棉农的种植积极性，引发种植面积的周期性调整，还加剧了产业链上下游企业的经营风险。为应对棉花价格剧烈波动带来的严峻挑战，中国正积极探索棉花“价格保险+期货”这一新型风险管理工具。该工具通过结合价格保险的风险转移功能和期货市场的套期保值功能，开创了市场化风险管理的新路径，既能有效减轻政府的财政负担，又能提升风险管理的效率与精准度。但值得关注的是，尽管棉花“价格保险+期货”已试点运行多年，其推广过程中仍面临三大核心障碍：一是运行机理不明确与保险公司定位模糊；二是价格指数设计缺乏科学性与标准化；三是财政补贴的不可持续与保费补贴比例失衡。上述问题构成“风险分散失效-赔付精准不足-推广动力缺失”的恶性循环，其破解亟需重点解决三个关键问题：一是如何科学界定保险公司作为“风险承担主体”的权责边界，构建有效的风险对冲策略？二是如何设计融合区域特征的价格指数，提高赔付的精准度？三是如何建立差异化的最优保费补贴模型，平衡财政可持续性与区域公平性？鉴于此，本文通过分析上述三大障碍的内在机理，系统性地提出优化路径，为棉花“价格保险+期货”从“局部试点”迈向“全面推广”提供坚实的理论支撑。

本文以蛛网理论、制度变迁理论、期货套期保值理论、农业保险相关理论、福利经济学理论、农户行为理论为支撑，针对棉花“价格保险+期货”现存问题，构建“提出问题——分析问题——优化设计”的逻辑框架，运用案例分析法、时间序列分析法、多时点DID回归模型、实地调研法、专家访谈法、效用最大化模型、亚式期权定价模型与蒙特卡洛模拟等方法，深入探索棉花“价格保险+期货”的运行机理、价格指数设定机理和财政补贴机理，对此进行了系统性优化设计。明确保险公司作为“风险承担主体”的核心定位，构建目标价格动态调整与结算价格科学测算的理论依据，并推导财政补贴最优比例模型。在此基础上，基于新疆、山东等四大棉花产区现货与期货价格数据，量化分析区域间的保险纯保费与期货再保险费差异，对优化设计后的棉花“价格保险+期货”进行效果验证。主要研究结论如下：

第一，价格保险通过风险转移与经济补偿功能分散市场波动风险，期货市场则依托价格发现功能形成风险评估基准，通过套期保值功能构建风险对冲通道。棉花“价格保险+期货”结合价格保险和期货市场两者的优势，能够更有效地管理棉花价格风险，提升风险管理效率。基于新疆、山东等主产区试点数据的实证结果表明，棉花“价格保险+期货”试点显著提升棉农收入（平均增幅29.4%），并呈现风险规避、生产激励与信贷促进三重效应。然而，当前棉花“价格保险+期货”试点陷入“运行机理不明确与保险公司定位模糊”的困境，对此，提出重构保险公司在风险管理中的角色，明确其“风险承担主体”的核心定位。通过创新采用“选择性风险自留+部分风险转移”的混合策略，选择非比例再保险精准量化风险敞口以平衡盈利与风险控制。

第二，目标价格的科学设定基于马克思的平均利润理论，采用近三个年度的省级历史现货日均价进行构建，确保价格指数反映生产成本与市场均衡，使目标价格更加符合棉农的收益预期。同时，结合棉花生产周期特点，确定了科学合理的结算价格采价期。在内地棉区，宜采用当年9月至12月的省级现货市场均价作为结算价格；在新疆地区，由于棉花收获期较晚，延至次年1月，覆盖完整交售期，有效降低基差风险。此外，关于价格指数的设定主体，建立了“政府监管+保险公司设定”组合模式，解决了政府主导模式的价格刚性和保险公司自主设定的道德风险问题。

第三，财政补贴在棉花“价格保险+期货”的作用是纠正市场失灵、降低供需双方成本。与棉花目标价格政策相比，棉花“价格保险+期货”在保障棉农收益的同时，能够通过期货市场套期保值功能，降低财政补贴成本，提升财政资金的使用效率。供给侧补贴通过降低保险公司的运营成本，能够有效扩大保险市场规模，提升棉农的消费者剩余，但保险公司的利润并未显著增加，补贴资金主要通过保费折扣惠及棉农；而需求侧补贴则通过直接降低棉农的投保成本，显著提升棉农的参保意愿，增加保险需求，同时保险公司的生产者剩余也有所增加，社会总福利得到提升。通过构建效用最大化模型，测算棉花“价格保险+期货”的最优补贴额度应为保险公司愿意接受的最低保费与棉农愿意支付的最高保费之差。

第四，优化设计的核心内容涵盖了运行机理、价格指数及财政补贴三大方面。运用新疆、山东、湖北和甘肃四个主要棉花产区的棉花现货与期货价格数据，对优化设计后的棉花“价格保险+期货”进行了效果验证。首先，价格指数优化的效果验证。基于现货市场价格赔付的纯保费显著低于基于期货市场价格赔付的纯保费，表明价格指数优化设计在降低基差风险方面具有显著效果，从而使得保险赔付更加精准。其次，运行机理优化的效果验证。保险公司基于现货市场为棉农提供价格指数保险，将棉花价格下降幅度超过棉花价格保险保费部分的超赔率风险转移至期货公司，再保险费率低于价格指数保险费率。保险公司既承担场外期权对冲风险，也保留盈利机会，提高了风险管理的效率和效果。验证了保险公司角色从“风险全部自留”和“风险中介”转型为“风险承担主体”，能够通过“选择性风险自留+部分风险转移”策略平衡盈利与风险控制。最后，以新疆为例，充分考虑棉农的实际支付意愿以及保险公司的合理利润空间，测算出棉花“价格保险+期货”的最优财政保费补贴额为155.92亿元，其中新疆自治区与兵团分别补贴103.06亿元和48.87亿元。

基于上述结论，本文提出以下对策建议：一是建立科学动态的风险转移比例确定机制，鼓励保险公司合理自留风险。二是构建省级棉花价格监测与预警平台，确保价格指数准确反映市场实际情况。三是优化财政补贴结构与比例，并建立财政补贴效果评估体系。四是构建棉花“价格保险+期货”优化设计的试点示范区，并开展动态评估。

China is the world's largest cotton producer and consumer, and the stable development of the cotton industry is of vital strategic significance to ensure the national agricultural economic security, maintain the stability of the textile industry chain and meet the needs of strategic materials. However, the cotton market has been plagued by sharp price fluctuations for a long time, and the sharp fluctuations in cotton prices not only directly hurt the enthusiasm of cotton farmers, but also led to the cyclical adjustment of planting area, and also intensified the business risks of upstream and downstream enterprises in the industrial chain. In order to cope with the severe challenges brought by the sharp fluctuations in cotton prices, China is actively exploring the new risk management tool of cotton "price insurance + futures". By combining the risk transfer function of price insurance with the hedging function of futures market, this tool creates a new path of market-oriented risk management, which can not only effectively reduce the financial burden of the government, but also improve the efficiency and accuracy of risk management. However, it is worth noting that although the cotton "price insurance + futures" has been piloted for many years, it still faces three core obstacles in the promotion process: first, the operation mechanism is unclear and the insurance company's positioning is fuzzy; Second, the design of price index lacks scientificity and standardization; Third, the unsustainability of financial subsidies and the imbalance of premium subsidies. The above problems constitute a vicious circle of "risk dispersion failure - lack of compensation accuracy - lack of promotion power", and its solution needs to focus on solving three key problems: First, how to scientifically define the rights and responsibilities boundary of insurance companies as "risk bearing subjects", and build effective risk hedging strategies? Second, how to design the price index that integrates regional characteristics to improve the accuracy of compensation? Third, how to establish a differentiated optimal premium subsidy model to balance fiscal sustainability and regional equity? In view of this, by analyzing the internal mechanism of the above three obstacles, this thesis systematically proposes an optimization path to provide a solid theoretical support for cotton "price insurance + futures" from "local pilot" to "comprehensive promotion".

Based on cobweb theory, institutional change theory, futures hedging theory, agricultural insurance related theory, welfare economics theory, and farmer behavior theory, this thesis constructs a logical framework of "raising questions -- analyzing problems -- optimizing design" for the existing problems of cotton "price insurance + futures". Using case analysis, time series analysis, multi-time point DID regression model, field research method, expert interview method, utility maximization model, Asian option pricing model and Monte Carlo simulation, the operation mechanism of cotton "price insurance + futures", price index setting mechanism and financial subsidy mechanism were deeply explored, and systematic optimization design was carried out. Clarify the core positioning of insurance companies as "risk bearing subjects", build the theoretical basis for dynamic adjustment of target prices and scientific calculation of settlement prices, and deduce the optimal proportion model of financial subsidies. On this basis, based on the spot and futures price data of four cotton producing areas such as Xinjiang and Shandong, the differences between insurance net premium and futures repremium between regions were quantitatively analyzed, and the effect of the optimized design of cotton "price insurance + futures" was verified. The main conclusions are as follows:

First, price insurance disperses the risk of market fluctuation through the function of risk transfer and economic compensation, while the futures market relies on the function of price discovery to form a risk assessment benchmark and builds a risk hedging channel through the function of hedging. Combining the advantages of price insurance and futures market, "price insurance + futures" can manage cotton price risk more effectively and improve the efficiency of risk management. Empirical results based on pilot data in Xinjiang, Shandong and other major producing areas show that the cotton "price insurance + futures" pilot significantly increased cotton farmers' income (an average increase of 29.4%), and showed a triple effect of risk avoidance, production incentives and credit promotion. However, the current cotton "price insurance + futures" pilot has fallen into the dilemma of "unclear operating mechanism and ambiguous positioning of insurance companies". In this regard, it is proposed to reconstruct the role of insurance companies in risk management and clarify their core positioning of "risk bearing subject". Through innovation, the mixed strategy of "selective risk retention + partial risk transfer" is adopted to choose non-proportional reinsurance to accurately quantify risk exposure to balance profit and risk control.

Second, the scientific setting of the target price is based on Marx's average profit theory, and the provincial historical average daily price of the past three years is used to construct the price index to ensure that the production cost and market equilibrium are reflected, so that the target price is more in line with the income expectations of cotton farmers. At the same time, according to the characteristics of cotton production cycle, a scientific and reasonable settlement price period was determined. In mainland cotton areas, it is advisable to use the average price of the provincial spot market from September to December of the year as the settlement price; In Xinjiang, due to the late cotton harvesting period, it is extended to January of the following year to cover the complete delivery period, effectively reducing the basis risk. In addition, regarding the setting body of the price index, a combination model of "government supervision + insurance company setting" has been established to solve the price rigidity of the government-led model and the moral hazard of the insurance company's independent setting.

Third, the role of financial subsidies in cotton "price insurance + futures" is to correct market failures and reduce the cost of both supply and demand. Compared with the cotton target price policy, the cotton "price insurance + futures" can reduce the cost of financial subsidies and improve the efficiency of financial funds through the hedging function of the futures market while protecting the income of cotton farmers. By reducing the operating costs of insurance companies, supply-side subsidies can effectively expand the scale of the insurance market and increase the consumer surplus of cotton farmers, but the profits of insurance companies have not increased significantly, and the subsidy funds mainly benefit cotton farmers through premium discounts. By directly reducing the insurance cost of cotton farmers, demand-side subsidies significantly increase the willingness of cotton farmers to participate in insurance and increase the insurance demand. At the same time, the producer surplus of insurance companies also increases, and the total social welfare is improved. By constructing a utility maximization model, it is estimated that the optimal subsidy amount of "price insurance + futures" for cotton is the difference between the minimum premium that insurance companies are willing to accept and the maximum premium that cotton farmers are willing to pay.

Fourth, the core content of optimal design covers three aspects: operation mechanism, price index and financial subsidies. Using the cotton spot and futures price data of four major cotton producing areas in Xinjiang, Shandong, Hubei and Gansu, the effect of the optimized design of cotton "price insurance + futures" was verified. First, the effect of price index optimization is verified. The net premium paid based on spot market price is significantly lower than the net premium paid based on futures market price, indicating that the optimal design of price index has a significant effect on reducing the basis risk, so as to make the insurance payout more accurate. Secondly, the effect of operation mechanism optimization is verified. The insurance company provides price index insurance for cotton farmers based on the spot market, and transfers the excess risk of cotton price decline exceeding the premium part of cotton price insurance to the futures company, and the reinsurance rate is lower than the price index insurance rate. Insurance companies not only bear the risk of OTC option hedging, but also retain the profit opportunity, which improves the efficiency and effect of risk management. It is verified that the role of insurance companies has been transformed from "total risk retention" and "risk intermediary" to "risk bearing subject", which can balance profit and risk control through the strategy of "selective risk retention + partial risk transfer". Finally, taking Xinjiang as an example, fully considering the actual willingness of cotton farmers to pay and the reasonable profit margin of insurance companies, the optimal financial premium subsidy of cotton "price insurance + futures" is estimated to be 15.592 billion yuan, of which the Xinjiang Autonomous Region and the XPCC subsidize 10.306 billion yuan and 4.887 billion yuan respectively.

Based on the above conclusions, this thesis puts forward the following countermeasures and suggestions: First, establish a scientific and dynamic risk transfer ratio determination mechanism to encourage insurance companies to retain risks reasonably. The second is to build a provincial cotton price monitoring and early warning platform to ensure that the price index accurately reflects the actual market situation. The third is to optimize the structure and proportion of financial subsidies, and establish a financial subsidy effect evaluation system. The fourth is to build a pilot demonstration area for the optimization design of cotton "price insurance + futures" and carry out dynamic evaluation.

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