Exploring the Relationship Between Patent Forward Citation and Stock Return Rate Using Empirical Data of China Stock Market

A novel indicator called price-citation was proposed.Based on the company integrated patent database of China listed companies of common stocks(A-shares)with the stock price and the stock return rate data,more than two thousand of A-shares from 2017 to 2020 were selected.The effect of the traditional patent forward citation and the price-citation for discriminating the stock return rate was thoroughly analyzed via ANOVA.The A-shares of forward citation counts above the average showed higher stock return rate means than the A-shares having patents but receiving no forward citations.The price-citation,combining both the financial and patent attributes,defined as the multiplication of the current stock price and the currently receiving forward citation count,showed its excellence in discriminating the stock return rate.The A-shares of higher price-citation showed significantly higher stock return rate means while the A-shares of lower price-citation showed significantly lowest stock return rate means.The price-citation effect had not been changed by COVID-19 though COVID-19 affected the social and economic environment to a considerable extent in 2020.

Effective Return Rate Prediction of Blockchain Financial Products Using Machine Learning

In recent times,financial globalization has drastically increased in different ways to improve the quality of services with advanced resources.The successful applications of bitcoin Blockchain(BC)techniques enable the stockholders to worry about the return and risk of financial products.The stockholders focused on the prediction of return rate and risk rate of financial products.Therefore,an automatic return rate bitcoin prediction model becomes essential for BC financial products.The newly designed machine learning(ML)and deep learning(DL)approaches pave the way for return rate predictive method.This study introduces a novel Jellyfish search optimization based extreme learning machine with autoencoder(JSO-ELMAE)for return rate prediction of BC financial products.The presented JSO-ELMAE model designs a new ELMAE model for predicting the return rate of financial products.Besides,the JSO algorithm is exploited to tune the parameters related to the ELMAE model which in turn boosts the classification results.The application of JSO technique assists in optimal parameter adjustment of the ELMAE model to predict the bitcoin return rates.The experimental validation of the JSO-ELMAE model was executed and the outcomes are inspected in many aspects.The experimental values demonstrated the enhanced performance of the JSO-ELMAE model over recent state of art approaches with minimal RMSE of 0.1562.

Optimization of Pension Asset Portfolio in Nigeria with Contributors’ Specified Return Rate

This work focuses on the optimization of investment contributions of pension asset with a view to improving contributors’ participation in achieving better return on investment (RoI) of their funds. We viewed some new regulations on Nigeria’s Contributory Pension Scheme” (CPS) from amended legislation of 2014, some of which are yet to be implemented when their regulations are approved. A mathematical model involving 5 variables, 5 inequality constraints covering regulatory limitations and limitation on scarce resource known as Asset Under Management (AUM), suggested and mathematically shown to be possible through “maximization of return irrespective of risk” while obeying all regulatory controls as our constraints optimized. Optimized portfolio using MatLab shows that the portfolio representing AES 2013 portfolio with a deficit growth of 15.75 m representing 3.27% less than the portfolio’s full growth potential within defined assumptions would have been averted if contributors actually set their targets and investment managers optimize from forecasts of future prices using trend analysis.

Exploring Patent Effects on Higher Stock Price and Stock Return Rate-A Study in China Stock Market

Based on the valid patent data and stock price data of China A-shares,the patent effects of four patent species including the invention publication,the invention grant,the utility model grant,and the design grant,on the stock price and the stock return rate were analyzed via analysis of variance(ANOVA).It was proved that the A-shares having new patents of any patent species shown the higher stock price mean and the higher stock return rate mean than those A-shares having no new patents did.The A-shares having new design grants were found to show the highest stock price mean among the A-shares having new patents of any patent species.The A-shares in the group of top 25%patent count of either the invention publication or the invention grant shown the highest stock return rates mean than those A-shares in other groups of less patent count did.The invention grant,following the general concept,showed its excellent patent effect.The design grant,beyond the expectation,also showed patent effects on the higher stock price and the higher stock return rate.The finding would improve the state of the art in the patent valuation and the listing company evaluation.

Does the Shanghai-Hong Kong Stock Connect Program Enhance the Abnormal Rate of Return and Transaction Volatility of the Underlying Stocks:A Quasi-Natural Experimental Design

Shanghai-Hong Kong Stock Connect Program,which is a new starting point for the opening up of the mainland capital market,still has many uncertainties.Research on the benefits and market volatility of such policies can provide investors with time to invest in such policies,fluctuations in the underlying stocks of the Chinese stock market,and decision support for the formulation and revision of relevant policies.This paper studies whether there is significant abnormal rate of return in the selected stocks which are in the Shanghai Stock Connect Program within the specified period,the excess return gap between the stocks which are in the program and which are not in the program,and the impact of the Shanghai Stock Connect Program on the volatility of the relevant stocks.Based on the CAPM model and the Fama-French 3-factor model,this paper uses t test to study the significance of the abnormal rate of return.By establishing a difference-in-difference(DID)model,the regression of the abnormal rate of return is tested,and the sample volatility is analyzed according to the influence of the fund transaction.The study found that the stocks in the program have significant abnormal rate of returns during the window period.The Shanghai Stock Connect has brought about a huge change in transaction amount,and policy makers need to improve related and similar policies.

Return to sport following toe phalanx fractures:A systematic review

BACKGROUND Evidence-based guidance on return to sport following toe phalanx fractures is limited.AIM To systemically review all studies recording return to sport following toe phalanx fractures(both acute fractures and stress fractures),and to collate information on return rates to sport(RRS)and mean return times(RTS)to the sport.METHODS A systematic search of PubMed,MEDLINE,EMBASE,CINAHL,Cochrane Library,Physiotherapy Evidence Database,and Google Scholar was performed in December 2022 using the keywords‘Toe’,‘Phalanx’,‘Fracture’,‘injury’,‘athletes’,‘sports’,‘non-operative’,‘conservative’,‘operative’,‘return to sport’.All studies which recorded RRS and RTS following toe phalanx fractures were included.RESULTS Thirteen studies were included:one retrospective cohort study and twelve case series.Seven studies reported on acute fractures.Six studies reported on stress fractures.For the acute fractures(n=156),63 were treated with primary conservative management(PCM),6 with primary surgical management(PSM)(all displaced intra-articular(physeal)fractures of the great toe base of the proximal phalanx),1 with secondary surgical management(SSM)and 87 did not specify treatment modality.For the stress fractures(n=26),23 were treated with PCM,3 with PSM,and 6 with SSM.For acute fractures,RRS with PCM ranged from 0 to 100%,and RTS with PCM ranged from 1.2 to 24 wk.For acute fractures,RRS with PSM were all 100%,and RTS with PSM ranged from 12 to 24 wk.One case of an undisplaced intra-articular(physeal)fracture treated conservatively required conversion to SSM on refracture with a return to sport.For stress fractures,RRS with PCM ranged from 0%to 100%,and RTS with PCM ranged from 5 to 10 wk.For stress fractures,RRS with PSM were all 100%,and RTS with surgical management ranged from 10 to 16 wk.Six cases of conservatively-managed stress fractures required conversion to SSM.Two of these cases were associated with a prolonged delay to diagnosis(1 year,2 years)and four cases with an underlying deformity[hallux valgus(n=3),claw toe(n=1)].All six cases returned to the sport after SSM.CONCLUSION The majority of sport-related toe phalanx fractures(acute and stress)are managed conservatively with overall satisfactory RRS and RTS.For acute fractures,surgical management is indicated for displaced,intra-articular(physeal)fractures,which offers satisfactory RRS and RTS.For stress fractures,surgical management is indicated for cases with delayed diagnosis and established nonunion at presentation,or with significant underlying deformity:both can expect satisfactory RRS and RTS.

战略合作框架协议对股票收益率的影响——基于沪深A股市场的实证分析

战略合作框架协议近些年愈发受到上市公司的关注,但对其市场的影响尚未有明确结论。本文以2004~2022年沪深股市发布的2948份战略合作框架协议为研究样本,采用事件研究方法构建计量模型估计协议对发布公司股票市场表现的影响。结果表明:(1)在协议发布的不同事件窗口期,发布公司股票总体取得显著为正的累积特异收益率,且随与协议发布时点的间隔呈倒U形状;(2)协议的影响具有公司规模和交易对象差异性,小市值公司、交易对象同为企业的公司获得更高累积特异收益率;(3)协议内容与行业类型产生交互影响,从事公用事业的公司获得更高累积特异收益率,产业链协调、项目建设开发、股权投融资领域的协议因行业不同带来差异化的累积特异收益率。研究结论揭示了战略合作框架协议对发布公司股票市场表现的规律性特征,为投资者和上市公司提供借鉴。

国有大型油气企业新能源发电项目经济评价探讨

国有大型油气企业基于减排降碳和可持续健康发展考量,积极探索新能源发电业务,投资项目经济评价方法和参数,成为影响新能源发电业务投资决策和高质量发展的决定性因素。基于经济评价基本原理,根据新能源发电项目技术经济特征,构建新能源发电项目经济评价方法和参数体系。折现现金流法仍然是新能源发电项目经济评价的主要方法,内部收益率和平准化度电成本是衡量项目盈利能力的重要指标。不同类型新能源发电项目经济评价方法具有较高的一致性,但应在投资构成、成本费用估算、收入与税金估算等方面体现差异,重点在营业收入估算中体现项目真正价值。在规制性配置储能要求以及储能收益政策有待落实的情况下,新能源发电项目效益有待提高,建议现阶段适当降低投资回报要求,尤其是出于市场拓展和协同发展目的的战略性新能源发电项目。项目电价和有效利用小时数对新能源发电项目的影响至关重要,应视情况合理选取参数。风光气电融合项目应分业务估算成本。国有大型油气企业应积极开展宏观配套政策和商业模式创新研究,以支撑新能源发电业务的高质量发展。

长期秸秆还田下施氮量对棉花产量和氮素利用的影响

施氮能够增加土壤中氮的有效性,提高植株光合作用,促进植株对氮的吸收和干物质的积累,最终增加作物产量。但是在长期高氮秸秆还田条件下,是否应调整施氮量尚不清楚。为探究长期秸秆还田条件下施氮量对棉花光合速率、干物质和养分积累分配、产量、氮素利用和土壤氮素变化的影响,本研究设置0(N0)、150(N150)、180(N180)、210(N210)、240(N240)、270(N270)和300(N300)kg hm^(–2)共7个施氮量处理。与常规施氮量(N300)相比,2020—2021年,减氮30%(N210)处理2年均获得了较高产量,分别为1853.62 kg hm^(–2)和1872.43 kg hm^(–2),减氮40%(N180)仅在第1年保持了较高产量,为1743.68 kg hm^(–2)。2021年,N210的净光合速率、干物质和养分积累量均高于N180,两者间生殖器官的干物质和养分分配系数、氮肥利用效率未有显著差异,但N180的土壤表观氮盈余量显著降低了39.15%。综上,长期秸秆还田条件下,鲁西北棉区应适量减少施氮量。

长期秸秆还田下追氮量对冬小麦产量和氮素吸收利用的影响

在长期秸秆还田且基施足量氮肥(150 kg/hm^(2))条件下研究拔节期不同追氮量[0 kg/hm^(2)(N150)、37.5 kg/hm^(2)(N150+37.5)、75 kg/hm^(2)(N150+75)、112.5 kg/hm^(2)(N150+112.5)和150 kg/hm^(2)(N150+150)]对冬小麦群体动态、地上部干物质和氮素的积累转运、籽粒产量和氮肥利用效率的影响,明确协同实现较高籽粒产量和氮肥利用效率的追氮量,以期为秸秆还田下冬小麦氮肥高效管理提供理论依据和技术支撑。结果表明,随着施氮量的增加,冬小麦冬前分蘖数和有效穗数均呈先增加后降低的趋势,在N150+75和N150+112.5处理下较高。花前地上部干物质和氮素积累量均随施氮量的增加逐渐增加,花后地上部干物质和氮素积累量均呈先增加后降低的规律。不追氮(N150)和低追氮量(N150+37.5、N150+75)处理的花前干物质转运量与转运率总体上均显著高于高追氮量(N150+112.5、N150+150)和不施氮(N0)处理;花前氮素转运量随施氮量的增加逐渐增加,在N150+150处理达到最大值,但其花前氮素转运率显著低于其他处理。与仅基施氮150 kg/hm^(2)处理相比,拔节期追氮37.5~150 kg/hm^(2)增加籽粒产量10.45%~33.64%。随着追氮量的增加,籽粒产量呈先增加后降低的趋势,在N150+112.5处理下达到最大值,显著高于其他处理,分别较N150、N150+37.5、N150+75、N150+150处理提高30.85%~33.64%、15.04%~20.99%、6.62%~11.07%、7.35%~7.81%;氮肥偏生产力、氮肥农学效率和氮肥生理利用率直线下降,N150+75与N150+112.5处理间差异总体上不显著。综上,拔节期追施氮肥有利于增加冬小麦花前、花后干物质和氮素的积累转运,但过量追氮导致花前干物质和氮素转运率大幅降低,产量增加效应减小,氮肥利用效率大幅降低;在长期秸秆还田基施氮150 kg/hm^(2)条件下,拔节期追氮112.5 kg/hm^(2)有利于协调冬小麦花前、花后干物质和氮素的积累转运,同时拟合分析发现,拔节期追氮107.81~139.50 kg/hm^(2)可获得较高的籽粒产量和氮肥利用效率。

不同秸秆还田方式下黑土玉米田肥料氮素去向

探究不同秸秆还田方式下肥料氮在连续两季作物系统中的去向,为黑土地保护下的氮肥管理提供重要依据。于2020—2021年在吉林梨树开展大田微区试验,设置无秸秆还田(CK)、深翻还田(DTS)、免耕覆盖还田(NTS)3种秸秆还田方式,每种方式下设置2个施氮水平:180 kg·hm^(-2)(N1)和270 kg·hm^(-2)(N2)。结果表明:当季和第二季玉米成熟期植株氮分别有38.0%~46.8%和12.9%~18.6%来源于^(15)N标记氮肥。肥料氮当季平均利用、残留和损失率分别为32.4%~43.9%、32.8%~51.4%和13.2%~32.7%,秸秆覆盖配施适量氮肥(180 kg·hm^(-2))处理下肥料氮当季利用率显著提高29.5%,而秸秆深翻还田则使肥料氮在土壤中的残留率显著增加18.6%。当季施用肥料氮仍有8.5%~14.9%被第二季玉米吸收利用,两季累积利用率达40.9%~58.8%,在高氮(270 kg·hm^(-2))下秸秆深翻还田显著提高肥料氮的第二季利用率及累积利用效率。综上,秸秆覆盖还田配施适量氮肥有利于提高肥料利用效率,而秸秆深翻还田更有利于高施氮量下土壤对肥料氮的保持,增加其被下季作物利用的机会,两者均能显著减少氮的损失。

葡萄枝条原位还田不同处理对其腐解及土壤性质的影响

【目的】探明枝条原位还田增施负载营养微生物菌剂、土壤调理剂、尿素对枝条腐解率及土壤性质的影响,为省时省力的枝条肥料化利用提供科学依据。【方法】以不进行葡萄枝条原位还田为对照(CK),采用田间试验方法,研究枝条原位还田不同处理〔T_(1)(不施肥)、T_(2)(尿素225 kg/hm^(2))、T_(3)(尿素225 kg/hm^(2)、负载营养微生物菌剂60 kg/hm^(2))、T_(4)(尿素225 kg/hm^(2)、负载营养微生物菌剂60 kg/hm^(2)、土壤调理剂300 kg/hm^(2))〕对枝条腐解率与土壤性质的影响。【结果】T_(4)枝条腐解率、土壤有机质、孔隙度和水分含量较CK、T_(1)、T_(2)和T_(3)分别提高12.7%~33.3%,5.52%~33.04%,3.61%~16.41%和2.40%~19.66%,土壤容重降低6.19%~16.54%。T_(4)细菌、放线菌和真菌较CK、T_(1)、T_(2)和T_(3)分别增加0.09~6.94倍、0.33~7.78倍和0.31~1.03倍。T_(4)土壤过氧化氢酶、蔗糖酶、脲酶和磷酸酶活性较CK、T_(1)、T_(2)和T_(3)分别提高0.25~5.48倍、0.04~0.65倍、0.31~1.78倍和0.12~1.60倍。各处理土壤N、P、K、Ca、Mg、Fe、Zn和B含量均为T_(4)>T_(3)>T_(2)>T_(1)>CK。【结论】葡萄枝条原位还田可提升腐解率、土壤有机质含量、孔隙度、水分含量、土壤微生物数量、酶活性与矿质元素含量,降低土壤容重,其中,以葡萄枝条原位还田时增施尿素225 kg/hm^(2)、负载营养微生物菌剂60 kg/hm^(2)、土壤调理剂300 kg/hm^(2)的效果最佳。

考虑库存风险的服装行业新产品预售策略博弈研究

电子商务时代,服装行业线上销售的退货率居高不下。为缓解高退货率连带的库存风险,部分服装企业采用超长预售策略,在相对较长的预售期内次第发货满足顾客订单。在此现实背景下,文章基于报童模型,探讨商家在正常预售和超长预售中的策略选择,并求解两种策略的最优定价、产量、利润和可行条件。结果表明:当需求不确定性较大且产品残值较小,预售时长在合理的范围内且顾客更愿意等待时,应选择超长预售策略,反之选择正常预售策略;并且,超长预售策略能够显著降低库存剩余风险。研究结论对服装企业的预售决策和库存管理具有一定的现实参考价值。

不同腐熟剂对麦秸腐解率与稻田水环境的影响

为探明麦秸还田条件下施用腐熟剂对秸秆腐解效果、稻田水环境风险的影响,选用4种腐熟剂(标识为DA1、DA2、DA3和DA4)进行水稻季麦秸腐解试验。结果表明,施用4种腐熟剂均加快还田后4周内秸秆腐解速度,其中,还田后2周为麦秸快速腐解期,且腐熟剂DA3和DA4促进麦秸腐解的效果更佳,腐解率达36.5%~37.4%,较麦秸还田无腐熟剂处理(CFS)增加了5.1~6.0个百分点。与CFS处理相比,4种腐熟剂处理提高了麦秸还田后3周内田面水化学需氧量(COD)及氮磷含量,增加了水稻生长初期的水环境风险。其中,DA2、DA3和DA4这3种腐熟剂处理后3周内田面水环境风险相对较高,而DA1与CFS处理间水环境风险差异不显著。可见,稻田施用腐熟剂会加速麦秸腐解,同时会增加水稻生长初期的水环境风险,建议南方水网区水稻季谨慎施用腐熟剂。

现货市场中实现保供目标的容量补偿定价方法

为解决电力现货市场环境下的电力系统装机充裕度不足的问题,提出一种实现电力系统保供目标的容量补偿定价方法。首先,根据保供要求的电力系统可靠性标准,构建基于内部收益率评估的机组投资、退役决策模型;其次,通过“机组电能市场收入评估、机组容量补偿收入评估、投资退役决策”的迭代,确定目标年份市场中分类型机组的预期装机;然后,计算目标年份的可靠性指标,根据可靠性指标与标准的偏差调整容量补偿价格,使得发电充裕度能够满足目标年份系统的可靠性标准。算例结果表明,所提定价方法能够在保证电力系统可靠性的基础上,降低电力用户的综合购电成本。

光伏电站建设项目内部基准收益率测算

内部基准收益率(简称基准收益率)是衡量资产价值与建设项目经济价值的重要参数,其取值受宏观经济情况,市场景气程度以及行业发展水平等因素影响,随时间呈动态变化,也因项目的不同而存在差别。光伏发电属于可再生能源发电中十分重要的部分,但由于该行业发展的年限较短,光伏电站建设项目的基准收益率尚缺乏针对行业特点的测算方法。融合资本资产定价模型(CAPM)和加权平均资本成本(WACC)方法,得到适用于项目的权益资本成本和适用于具体项目的基准收益率。并以某屋顶分布式光伏电站项目为例,计算得到该项目的基准收益率为4.50%,符合当前光伏项目4%~8%的基准收益率水平,说明采用该方法计算光伏发电项目的基准收益率是可行的。

宏观经济不确定性与股票超额收益:来自中国A股市场的证据

宏观基本面冲击作为股票市场波动的重要原因被广泛认可,但从宏观经济不确定性视角探讨其对中国市场股票超额收益率影响的研究却相对缺乏。利用中国宏观经济和金融的多指标数据,构建2002—2022年中国宏观经济不确定性指数,考察其对A股超额收益率的影响。研究发现宏观经济不确定性暴露的负向溢价显著存在,即具有负的宏观经济不确定性贝塔股票的未来超额收益率更高;不过这种溢价在不同股权性质、规模和行业的股票中存在差异,并且相对于经济上行时期,经济下行时期的宏观不确定性贝塔(beta)溢价更为显著,凸显其异质性和状态依赖性。本研究对于理解宏观经济不确定性对股票市场的影响以及构建相应的资产组合来应对宏观不确定性冲击具有一定的理论意义和现实价值。

ESG评级分歧与股票收益——内部控制与外部关注的调节效应

随着“双碳”目标与可持续发展理念的不断推进,ESG投资关注度持续提升。但由于不同评级机构的ESG评级标准各异,同一家公司存在明显的ESG评级分歧现象,极大影响了投资者的决策过程。文章以2011—2021年沪深A股上市公司为样本,考察ESG评级分歧对公司股票收益的影响效应。研究发现:ESG评级分歧显著降低了公司股票收益,经过一系列内生性检验和稳健性检验后结论依然成立。调节效应检验表明,实际控制人持股会抑制ESG评级分歧对股票收益的负向效应,外部分析师关注则放大了两者之间的负向关系。文章拓展了ESG评级分歧与股票回报的相关研究,为推动中国ESG评级体系建设、完善公司治理、推动股票市场健康有序发展提供了经验证据。

城市蔓延与教育回报率——基于市辖区与县域的异质性视角

城市蔓延作为影响集聚经济的重要因素,在城市化的高质量协调发展和促进收入分配公平的过程中有着不可忽视的影响。在研究设计上,以城市蔓延指数度量的城市空间结构作为核心解释变量,结合CHIPS中国家庭收入调查数据,考察城市蔓延在全市域、市辖区及县域区域内对劳动者教育回报率的影响。研究发现:高密度、低蔓延度的地级市空间结构对教育回报率在市辖区范围内有显著的提高作用,且更为显著地影响拥有城镇户口的劳动力,而这一效应在县域不明显;进一步的讨论表明,受教育水平越高的劳动者越容易缓解城市蔓延对教育回报率的负面作用。

基于WRF模式的四川省凉山州地区风能资源可开发区域研究

利用MERRA2再分析数据驱动WRF模式,对四川凉山州地区2020年全年进行风资源模拟分析,并用凉山州地区典型测风塔数据对模拟结果进行检验,并进行详细地风资源分析,再根据风电场开发8%基准内部收益率反推可开发风能资源的区域分布。结果表明:凉山州大部分地区100 m高度年平均风速在5 m/s以上,风速极大值一般位于山脊,凉山州风能最好的区域主要集中在会东县和宁南县。凉山州典型区域内均表现出受西南季风影响的特征,即冬、春季节风大,夏、秋季节风小,主风向呈强西南风状态,且风功率密度变化规律与风速的变化规律基本一致。凉山州山地区域可开发风能资源的平均风功率密度临界值为258 W/m^(2),这些区域主要集中在会理、会东、宁南、布拖、木里和盐源县境内。可开发区域分布图对指导凉山州地区风能开发提供科学参考。