基于互信息优化的Option-Critic算法

时序抽象作为分层强化学习的重要研究内容,允许分层强化学习智能体在不同的时间尺度上学习策略,可以有效解决深度强化学习难以处理的稀疏奖励问题。如何端到端地学习到优秀的时序抽象策略一直是分层强化学习研究面临的挑战。Option-Critic(OC)框架在Option框架的基础上,通过策略梯度理论,可以有效解决此问题。然而,在策略学习过程中,OC框架会出现Option内部策略动作分布变得十分相似的退化问题。该退化问题影响了OC框架的实验性能,导致Option的可解释性变差。为了解决上述问题,引入互信息知识作为内部奖励,并提出基于互信息优化的Option-Critic算法(Option-Critic Algorithm with Mutual Information Optimization,MIOOC)。MIOOC算法结合了近端策略Option-Critic(Proximal Policy Option-Critic,PPOC)算法,可以保证下层策略的多样性。为了验证算法的有效性,把MIOOC算法和几种常见的强化学习方法在连续实验环境中进行对比实验。实验结果表明,MIOOC算法可以加快模型学习速度,实验性能更优,Option内部策略更有区分度。

Modeling the Spatio-Temporal Dynamics of Local Context for a Contextualized Diffusion of Agroecological Intensification Options in Niger

Spatio-temporal variability and dynamics in Sahelian agro-pastoral zones make each local situation a special case. These specificities must be considered to guide the dissemination of agricultural options with a view to sustainable development. The territorial scale of municipalities is not sufficient for this necessary contextualization;the scale of the “village terroir” seems to be a better option. This is the hypothesis we put forward in the framework of the Global Collaboration for Resilient Food Systems program (CRFS), i.e. local context is spatially defined by village terroir. The study is based on data collected through participatory mapping and surveys in “village terroirs” in three regions of Niger (Maradi, Dosso and Tillabéri). Then the links between farm managers and their cultivated land, as well as the spatio-temporal dynamics of local context are analyzed. This study provides evidence of the existence and functional usefulness of the village terroir for farmers, their land management and their activities. It demonstrates the usefulness of contextualizing agricultural options at this scale. Their analysis elucidates the links between “terroirs village” and the specific functioning of the agrosocio-ecosystems acting on each of them, thus laying the systemic and geographical foundations for a model of the spatio- temporal dynamics of “village terroirs”. This initial work has opened up new perspectives in modeling and sustainable development.

Research on Value Evaluation Method of Investment Project Based on Fuzzy Composite Real Options

Venture capital investments are characterized by high input,high yield,and high risk.Due to the complexity of the market environment,stage-by-stage investment is becoming increasingly important.Traditional evaluation methods like comparison,proportion,maturity,internal rate of return,scenario analysis,decision trees,and net present value cannot fully consider the uncertainty and stage characteristics of the project.The fuzzy real options method addresses this by combining real option theory,fuzzy number theory,and composite option theory to provide a more accurate and objective evaluation of Public-Private Partnership(PPP)projects.It effectively considers the interaction of options and the ambiguity of project parameters,making it a valuable tool for project evaluation in the context of venture capital investment.

Upside and downside correlated jump risk premia of currency options and expected returns

This research explores upside and downside jumps in the dynamic processes of three rates:domestic interest rates,foreign interest rates,and exchange rates.To fill the gap between the asymmetric jump in the currency market and the current models,a correlated asymmetric jump model is proposed to capture the co-movement of the correlated jump risks for the three rates and identify the correlated jump risk premia.The likelihood ratio test results show that the new model performs best in 1-,3-,6-,and 12-month maturities.The in-and out-of-sample test results indicate that the new model can capture more risk factors with relatively small pricing errors.Finally,the risk factors captured by the new model can explain the exchange rate fluctuations for various economic events.

Intelligent option portfolio model with perspective of shadow price and risk‑free profit

Since Markowitz proposed modern portfolio theory,portfolio optimization has been being a classic topic in financial engineering.Although it is generally accepted that options help to improve the market,there is still an improvement for the portrayal of their unique properties in portfolio problems.In this paper,an intelligent option portfolio model is developed that allows selling options contracts to earn option fees and considers the high leverage of options in the market.Deep learning methods are used to predict the forward price of the underlying asset,making the model smarter.It can find an optimal option portfolio that maximizes the final wealth among the call and put options with multiple strike prices.We use the duality theory to analyze the marginal contribution of initial assets,risk tolerance limit,and portfolio leverage limit for the final wealth.The leverage limit of the option portfolio has a significant impact on the return.To satisfy the investors with different risk preferences,we also give the conditions for the option portfolio to gain a risk-free return and replace the Conditional Value-at-Risk.Numerical experiments demonstrate that the intelligent option portfolio model obtains a satisfactory out-of-sample return,which is significantly positively correlated with the volatility of the underlying asset and negatively correlated with the forecast error of the forward price.The risk-free option model is effective in achieving the goal of no drawdown and gaining satisfactory returns.Investors can adjust the balance point between returns and risks according to their risk preference.

Valuing options to renew at future market value:the case of commercial property leases

In this study,we develop and empirically test a valuation model for a commonly encountered option in office leases:a tenant’s option to renew at future market rent(a fair market value)with lease termination as the maturity date.The model integrates decision analysis with real options analysis and market risk with private risks.“Option value”is defined as the private value of the option to either party pre-contract,while“option price”assumes a fair agreement between transacting parties and can be positive(rental premium paid)or negative(rental discount offered).Without manifest expectations,an analysis of a sample of office leases supports the model’s logic with price estimates in a practical range.The tenants’option price/value is shown to have a negative relationship with the original/renewal lease term;conversely,the landlords’option value is positively related to the original/renewal term.Comparative analyses show that transaction costs have a positive effect on tenants’option value and on prices,while vacancy costs and the vacancy period are both positively related to the landlords’option value and negatively related to price.Market rent is found to have a negative relationship with option price.Overall,this study provides a theoretical analysis and empirical tests of the value of a real option that allows option holders to renew/extend their contracts at a fair market value.

Pricing European Options Based on a Logarithmic Truncated t-Distribution

The t-distribution has a “fat tail” feature, which is more suitable than the normal probability density function to describe the distribution characteristics of return on assets. The difficulty of using t-distribution to price European options is that a fat tail can lead to a deviation in one integral required for option pricing. We use a distribution called logarithmic truncated t-distribution to price European options. A risk neutral valuation method was used to obtain a European option pricing model with logarithmic truncated t-distribution.

A novel stochastic modeling framework for coal production and logistics through options pricing analysis

We propose a novel stochastic modeling framework for coal production and logistics using option pricing theory.The problem of valuing the inherent real optionality a coal producer has when mining and processing thermal coal is modelled as pricing spread options of three assets under the stochastic volatility model.We derive a three-dimensional Fast Fourier Transform(“FFT”)lower bound approximation to value the inherent real optionality and for robustness check,we compare the semi-analytical pricing accuracy with the Monte Carlo simulation.Model parameters are estimated from the historical monthly data,and stochastic volatility parameters are obtained by matching the Kurtosis of the low-ash diff data to the Kurtosis of the stochastic volatility process which is assumed to follow Cox–Ingersoll–Ross(“CIR”)model.

Decarbonization options of the iron and steelmaking industry based on a three-dimensional analysis

Decarbonization is a critical issue for peaking CO_(2) emissions of energy-intensive industries,such as the iron and steel industry.The decarbonization options of China’s ironmaking and steelmaking sector were discussed based on a systematic three-dimensional low-carbon analysis from the aspects of resource utilization(Y),energy utilization(Q),and energy cleanliness which is evaluated by a process general emission factor(PGEF)on all the related processes,including the current blast furnace(BF)-basic oxygen furnace(BOF)integrated process and the specific sub-processes,as well as the electric arc furnace(EAF)process,typical direct reduction(DR)process,and smelting reduction(SR)process.The study indicates that the three-dimensional aspects,particularly the energy structure,should be comprehensively considered to quantitatively evaluate the decarbonization road map based on novel technologies or processes.Promoting scrap utilization(improvement of Y)and the substitution of carbon-based energy(improvement of PGEF)in particular is critical.In terms of process scale,promoting the development of the scrap-based EAF or DR-EAF process is highly encouraged because of their lower PGEF.The three-dimensional method is expected to extend to other processes or industries,such as the cement production and thermal electricity generation industries.

Investment Promotion for Development Zones in China:Underlying Rationale and Policy Options

Development zones(DZs)have emerged as a significant policy initiative for promoting regional coordination and facilitating resources allocation.They serve as an organizational framework for fostering industrial agglomeration and driving high-quality development.DZs attract and accommodate resource factors,firms,and projects,thereby functioning as a central catalyst for economic growth.This study utilizes data collected at the“DZ,City and Countrycountry”levels through manual compilation,textual analysis,and innovation measurement.It aims to empirically examine the theoretical rationale and practical preferences for promoting business and investment in China’s DZs.This study considers several factors such as industry attribute,firm attribute,agglomeration theory,and industrial chain layout.Based on our research findings,DZs exhibit distinct preferences.First,industry attribute:DZs align with both national and regional strategic planning and adhere to the industrial endowments of the respective areas.Second,firm attribute:DZs prioritize attracting firms that are productive and innovative,and have an international presence,rather than those that primarily contribute to taxes and job creation.Third,DZs are guided by the agglomeration theory,which suggests that they prefer firms that generate strong agglomeration externalities.Lastly,DZs also consider the industrial chain layout,aiming to attract firms that not only align with their existing industrial strengths but also extend to the upstream and downstream supply chain links.These conclusions are substantiated by the performance of robustness test.The success of DZs in China can be attributed to the five key principles:Adherence to national and regional strategic planning,prioritizing the actual industrial foundation,incorporating the theory of agglomeration externalities,strengthening corporate competitiveness,and expanding industrial chains.

The Contribution Margin due to a Limiting Factor in the Presence of Several Sales Options: Actuality Is Not Always As It Appears at the Beginning of the Analysis

The analysis of company data useful for economic decisions,if not interpreted in an overall view of the company situation,can lead to wrong conclusions.This is the case when a company has to choose between several sales options for one or more products in the presence of a limiting factor.The continuation of the investigation often denies the initial analysis.Not everything is as it appears,therefore,at the beginning of the deepening of the data useful for economic decisions.As it is well known,the choices of profitability concerning the planning of the sale of company products take place,at least in the majority of cases,through the determination of the contribution margin,i.e.the profitability margin connected to the individual goods/services sold by the companies(selling price net of variable costs).The contribution margin can be determined with four objectives:(1)Determination of the yield of the single product,net of variable costs only.In this case,the margin defines unitary,from net product yield to unitary contribution margin.(2)Determination of the return on total sales of an individual product,net of variable costs.In this hypothesis,reference is made to the first level(or gross)contribution margin.(3)Determination of the ability of the individual product to contribute to the coverage of fixed costs common to the company.This margin is determined net of special product variable and fixed costs.This aggregate is defined as a Level II(or semi-gross)margin.(4)Determination of the useful value in the planning choices in case of presence of scarce productive factors.In this case,it must identify the so-called unitary margin for low factor.Here we will only deal with the problem of the use of the contribution margin in the presence of rare factors.To complete the analysis,below are some very brief considerations regarding,respectively,the unitary,level I,and level II contribution margin in order to better understand where the problem of the most convenient choice of income is located in the event of the presence of rare production factors,especially in an environment characterized by a plurality of sales options.

基于前景理论框架和Heston模型的行为期权定价

行为期权定价是当前国际金融领域的热门研究主题之一。虽然随机波动率模型已成为国际衍生品定价领域的标准模型,但该模型对短到期期权(尤其是虚值期权)的定价仍不准确,其原因之一是传统的期权定价方法忽略了现实市场中的非理性心理和行为因素。针对上述问题,本文运用前景理论期权定价框架,引入价值函数来刻画投资者面对收益与损失的前景价值判断,引入决策权重函数来修正Heston随机波动率模型刻画的资产价格路径的概率密度函数,将期权合约签订与交割的现金流视为分散的心理账户情形,在市场均衡条件下推导出Heston模型下欧氏行为期权的定价公式。上证50ETF期权的实证结果表明:考虑了前景理论的Heston随机波动率模型,能显著地提升短到期虚值期权的定价准确度;参数校正结果发现,定价性能的提升要归因于Heston模型中纳入的表征非理性心理与情绪的行为参数;相对而言,投资者对实值期权的风险态度偏中性,因此行为参数对其定价精度的提升有限。

基于主题讲座的“化学与社会进步”课程设计

本着“厚基础、宽口径、高素质、强能力、重创新”的本科人才培养理念和卓越教师的培养目标,结合陕西师范大学发展战略目标和“双一流”建设要求,作为一门面向全校师生开设的通识教育选修课程,为了更好地达成“化学与社会进步”课程的目标任务,即“以适应社会经济发展需求和适应学生个体发展需求为导向,培养和造就卓越教师和专门人才”,同时为了破解具有不同学科背景和化学基础的学生同堂听课的困局以期打造高效课堂,本课程采用的教学策略是不使用现成的范本教材,而是定位于“在科普基础上的主题讲座”,通过一系列的教学设计充分发挥课堂教学的功能。

可变风险溢价结构下跳扩散模型的期权定价

风险溢价结构是真实测度与风险中性测度间的纽带,能够帮助提取投资者的风险偏好特征。本文针对跳扩散模型构建了灵活的风险溢价形式,允许期权市场隐含信息参与校准跳跃风险的市场价格,进而研究存在跳跃情形下的期权定价,并探索市场风险溢价结构。数值分析和实证研究表明,可变风险溢价结构有助于准确刻画市场定价核曲线,且市场风险溢价结构具有明显的时变特征,跳跃风险溢价能够较好解释隐含波动率曲面。此外,跳扩散模型的可变风险溢价结构在样本内外都具有明显的期权定价优势。考虑了不同样本长度、定价方法、定价区间以及期权产品后,以上结论均是稳健的。本研究有助于系统了解不同市场风险溢价结构与定价规律,有利于深入探索跳跃风险溢价补偿机制。

机器人使用与创业选择

以人工智能、机器人为代表的自动化技术进步,对劳动力市场结构影响持续深化,不仅表现在传统受雇工作形态,还表现在企业创业选择和决策方面。文章基于国家层面自动化程度不断加深的背景,使用2011—2017年全球创业观察(GEM)创业活动数据和国际机器人联合会(IFR)国家层面机器人数据,研究机器人使用对创业活动的影响及可能机制。研究结果表明,机器人使用对创业活动具有显著促进作用。按照创业动机划分机会型创业活动和生存型创业活动发现,机器人使用增加显著促进了机会型创业活动。该结论在控制内生性和考虑不同衡量指标下依然稳健。文章进一步从市场进入障碍、人力资本效应两个维度考察机器人使用对创业活动的影响机制。机制分析发现,机器人使用通过简化企业生产程序,降低企业市场进入障碍,提高人力资本水平进而促进企业创业活动实现。异质性分析表明,机器人使用对创业活动促进作用在OECD国家幅度更大,机器人使用显著增加了中年群体、女性群体以及中低受教育水平群体机会型创业活动概率,机器人使用有利于缩小不同群体间的创业差距。文章研究为促进我国机器人应用深化以及机会型创业活动实现提供了一定的参考意义。

突发疫情下考虑供应中断风险的制造商采购策略研究

突如其来的新冠肺炎疫情给我国人民的生命安全与经济活动带来了巨大的影响,供应链作为经济活动的重要组成部分,不可避免地遭受了冲击,如何应对供应链中断风险是企业面临的重要挑战。论文研究供应链中断风险情况下制造商采购策略,通过引入期权契约,构建不同情形下由低价不可靠的主供应商、高价可靠的后备供应商和风险规避制造商组成的采购模型,并得出以下结论:市场需求和采购价格是影响制造商最优采购量的重要因素,其中当主供应商出现中断时,其可靠性也是影响制造商采购的因素;当市场需求,主供应商的可靠性和成本等影响因素变化时,制造商对主供应商的最优采购决策、对供应链中断应急策略的选择都将发生变化;当且仅当主供应商的供应价格小于制造商向市场销售该产品销售价格和自身制造成本之差时制造商的最优采购量随着期权执行价格增加而增加。

基于“分解-重组-预测-集成”模式的Heston期权定价模型

精准合理地期权定价对于改善市场流动性、优化投资者结构、稳定金融市场拥有重要意义。本文提出了一种结合“分解-重组-预测-集成”思想的Heston期权定价模型,该模型利用Heston模型进行初始定价,通过自适应噪声完全集合经验模态分解(CEEMDAN)对定价误差进行分解与重构,获得高频项、低频项及趋势项,然后使用门控循环单元(GRU)估计高频项及低频项,使用差分整合移动平均自回归(ARIMA)估计趋势项,所有估计值集成汇总得到定价误差估计值,最后使用定价误差估计值对Heston模型的初始定价结果进行修正后获得最终定价结果。使用华夏上证50ETF、华泰柏瑞沪深300ETF和嘉实沪深300ETF期权数据验证模型,实证结果显示,在模型结构更加简单的基础上,本文提出模型的精度普遍优于基准模型。

强制与选择:涉案企业合规整改边界之厘定——公私法规范融贯的视角

专项合规与全面合规适用模糊、司法监督与企业自治边界冲突,二者均反映出涉案企业合规整改的边界具有模糊性。平衡企业合规与企业自治需要从公私法规范融贯的视角出发,划定涉案企业合规整改的边界。厘定边界的法理依据在于涉案企业合规的理论涵摄范围与企业自治规范的法定框架限定。明确企业事务控制权的配置、企业经营业务的范围、企业自治规范的制定应当属于涉案企业合规整改选择性事项,赋予企业就该类事项提出异议的权利。

2024年我国政府债务管理政策选择的思考

2023年我国政府债务管理政策较好地支持了宏观经济增长目标的实现。国债和地方政府专项债券预算发行额增加,2023年底我国增发了1万亿元的国债,还决定提前下达2024年部分地方政府新增债务限额;10月中央决定实施地方政府债务一揽子化解方案,开始发行相应的再融资券;2023年下半年地方政府投融资平台城投债发行规模有所减少。从2024年我国经济社会发展所面临的复杂严峻的国内外形势看,政府债务政策在总额管理、结构优化、债券发行、绩效管理、风险控制、体制改革等方面,需要进行有效的政策选择,以实现国家宏观政策目标。

PPP项目事前补偿与双边期权补偿的价值模型比较研究

针对PPP项目补偿受制于项目收益不确定问题,首先在收益确定假设下运用净现值方法确定项目特许权价值,以构建事前补偿的价值模型;然后基于项目收益不确定性,借鉴股票期权对风险转移方法,引入双边期权补偿的概念,并构建双边期权补偿的价值模型;最后对这两种补偿模型运用数值分析方法进行仿真比较研究。结果表明:当项目收益确定或不确定性较低时,PPP项目适合采取事前补偿;当项目收益不确定性较高时,PPP项目适合采取双边期权补偿。