Dynamic assets allocation based on market microstructure model with variable-intensity jumps

In order to characterizc large fluctuations of the financial markets and optimize financial portfolio, a new dynamic asset control strategy was proposed in this work. Firstly, a random process item with variable jump intensity was introduced to the existing discrete microstructure model to denote large price fluctuations. The nonparametric method of LEE was used for detecting jumps. Further, the extended Kalman filter and the maximum likelihood method were applied to discrete microstructure modeling and the estimation of two market potential variables： market excess demand and liquidity. At last, based on the estimated variables, an assets allocation strategy using evolutionary algorithm was designed to control the weight of each asset dynamically. Case studies on IBM Stock show that jumps with variable intensity are detected successfully, and the assets allocation strategy may effectively keep the total assets growth or prevent assets loss at the stochastic financial market.

DISCRETE TIME STOCHASTIC EQUILIBRIUM WITH INFINITE HORIZON INCOMPLETE ASSET MARKETS

This paper examines the existence of general equilibrium in a discrete time economy with the infinite horizon incomplete markets.There is a single good at each node in the event tree.The existence of general equilibrium for the infinite horizon economy is proved by taking limit of equilibria in truncated economies in which trade stops at a sequence of dates.

Asymptotic Inefficiency of Incomplete Asset Markets and Symmetric Event Trees

Demonstrating theoretically the possibility that the financial market, albeit incomplete, has equilibrium and that this equilibrium is efficient and has been an important topic at the frontier of the research on general equilibrium for financial markets. The paper examines the asymptotic properties of incomplete financial markets taking into accounting the asset structure. The paper deals with a case in which a structure of securities relates to the asymptotic inefficiency.

The Development of Market Method of Asset Appraisal Based on the Application of Big Data

Big data could be utilized in work and life. Asset appraisal could also make full use of big data to improve the efficiency and effectiveness of appraisal. The paper is going to study the application of big data in different fields to learn how big data works in practices and what the effect is after utilizing the new tool. Then, the paper is going to apply big data in appraisal in specific work environment. By collecting information, researching literature and practicing with appraisers, this paper f＇mds some means to improve market method by making full use of big data. The article researched further by applying the method in different projects of asset appraisal. Real estate, intangible asset, corporate valuation and machines could be valued by the market method improved by big data. There are different details for appraisers to be careful in practical work. Some companies have already put the technology into practice and achieved great benefit, which makes the application of big data meaningful.

Big Data Application in Asset Appraisal Using Market Method

The big data era is coming, which influences the life of human beings in every aspect, such as working, studying, shopping and so on. The data could be uploaded and recorded by the digital devices like smart-phone and pad. The volume of data could provide useful information to hdp learn the habit of human beings and improve the efficiency of work. The domain of asset appraisal could make full use of big data to collect and sort information involving the appraised asset and market. On the one hand, market method of asset appraisal needs a plenty of information of reference substance and industry development. On the other hand, big data with the trait of volume and velocity could be utilized to collect information. The paper reveals that taking advantage of big data application in asset appraisal using market method is an evolutionary process in which the gradual understanding of the potential of big data plays a crucial role.

Does the EVA valuation model explain the market value of equity better under changing required return than constant required return?

Through the Economic-Value-Added(EVA)valuation model,the expected market value of equity can be determined by adding the book value of equity with the present value of expected EVAs under the assumption of constant required return and constant return on equity.The equation of EVA valuation model has taken its shape under the assumption of constant required return and constant return on equity.However,a large body of empirical evidence indicates that required rate of return never remain constant.The EVA-valuation model formulated under constant required return cannot be implemented under the scenario of changing required return.In this study,we explored whether the EVA valuation model could be implemented under changing required return by making any changes in the model and found that it could be implemented under the scenario of changing required return by replacing the book value of the equity of the existing model with the present value of required earnings or normal market earnings.We further examined whether the explanatory ability of the EVA valuation model under the assumption of changing required return is better than that of the valuation model under the assumption of constant required return.Relative information content analyses were conducted by considering sample of the intrinsic value of equities determined by valuation models and the market value of equities of 69 large-cap,88 mid-cap,and 79 small-cap companies.The results showed that the EVA-based valuation model with changing normal market return outperformed the EVA-based valuation model with constant required return.

Social interactions in periodic urban markets and their contributions to sustainable livelihoods:Evidence from Ghana

Periodic markets are an important aspect of local economies,providing a platform for farmers(producers),wholesalers,retailers,and consumers to interact face-to-face and exchange goods and services.These markets have been increasing in urban areas in Africa,Asia,and South America because of urbanization.The increase of periodic urban markets(PUMs)in urban areas is observed as an index of modernization,reflecting a response to transition process.However,there are limited studies on how social interactions in PUMs contribute to sustainable livelihoods.This study investigated the types of social interactions occurring in PUMs in Ghana,the benefits of social interactions for participants of PUMs,and how social interactions contribute to sustainable livelihoods.This research interviewed 162 participants,comprising 27 farmers(farmers were regarded as producers in this study),61 retailers,47 wholesalers from 9 selected PUMs across Ghana,and 27 officers from government institutions and non-governmental market associations to obtain their opinions.We analyzed the interview data using the NVivo software.The results showed that there are seven kinds of social interactions in PUMs,including(i)producer-wholesaler relationship,(ii)producer-consumer relationship,(iii)wholesaler-retailer relationship,(iv)retailer-consumer relationship,(v)trader-driver relationship,(vi)trader-institution relationship,and(vii)trader-international buyer relationship.We found that these social interactions in PUMs enhance sustainable livelihoods by supporting human,social,financial,natural,and physical assets of traders(traders refer to producers,wholesalers,and retailers in this study).Therefore,we concluded that the development of policies to improve PUMs could strengthen social interactions,enabling the achievement of sustainable livelihoods in developing countries.

Editorial to special issue“Hidden market linkages between Bitcoin,cryptocurrencies and financial markets:Evidence from high‑frequency data and higher‑order moments”in financial innovation

The cryptomarket has evolved into a complex system of different types of cryptoassets,each playing an important role within the system.With specific features,opportunities,and risks.Studying their apparent and hidden linkages and general connectedness not only inside the system but also the linkages to the outer markets,being it either the traditional financial markets or the macroeconomic and monetary indicators and variables,plays a crucial role in understanding the market,managing risks,and aiming for profitable opportunities.The cryptomarkets are far from being simply Bitcoin or even just the most popular and capitalised cryptocurrencies and tokens which might have been the case just a few years back.

Investigain:A Productive Asset Management Web Application

The Investigain is a progressive web application to make mutual funds investments through a Systematic Investment Plan.The application utilizes the web’s modern capabilities,such as Asynchronous JavaScript and XML(AJAX),JavaScript,and Hypertext Marker Language(HTML5).The application also uses a powerful relational database management system,such as MySQL,to display asset management information.The application has two portals,one for investors and one for a particular asset manager or asset management company.Each investor has an account in the investor portal.The investor can view his/her profile,current balance,balance history,dividends,the units of mutual funds bought,unit price,the value of each mutual fund,and can pay installments using an embedded online payment gateway.Asset managers can monitor all investments,manage user accounts,and reimburse dividends using the admin portal.This paper also presents the experimental results of using the Investigain application,compares them with existing systems,and details the application’s prospect to improve its socio-economic conditions.The system’s frontend is designed with Bootstrap and jQuery frameworks.The backend is designed using Hypertext Preprocessor(PHP)server-side scripting language.The system demonstrated increased satisfaction from its clients.

Can news-based economic sentiment predict bubbles in precious metal markets?

This study examines the role of market sentiment in predicting the price bubbles of four strategic metal commodities(gold,silver,palladium,and platinum)from January 1985 to August 2020.It is the first to investigate this topic using sentiment indices,including news-based economic and consumer-based sentiments developed using different methods.We observed the role of sentiment as a reliable indicator of future bubbles for some metal commodities and found that bubbles were regularly concomi-tant with bearish sentiments for gold and platinum.Moreover,gold and palladium were the only commodities that experienced a bubble during the COVID-19 pandemic.Overall,our findings suggest inclusion of sentiment to the model that predicts the price bubbles of precious metals.

Determinants of market price of stock： A study on bank leasing and insurance companies of Bangladesh

Financial firms make up a substantial fraction of the domestic equity market. A number of studies subsequently used different conceptual and methodological approaches to model equity return of financial services firms. Movement of the stock price as the consequence of the movement of the micro and macroeconomic factors is strongly supported by the literature review. Dhaka Stock Exchange in Bangladesh is inefficient in weak form. Multiple regression analysis is conducted to find out the relationship microeconomic factors with the stock price. In this study found a significant linear relationship among market return and some microeconomic factors such as net asset value per share, dividend percentage, earning per share of bank leasing and insurance companies. Also found non-linear relationship among the variables is insignificant at 95 percent level of significance.

Analysis of the interest rate marketization risk of local banks in Henan Province --Taking four joint stock commercial banks as an example

With the accelerating process of interest rate marketization, the local banks in Henan Province face a greater risk of interest rate marketization, managing risk effectively can promote the development of local banks in Henan Province and the economic development of Henan Province. This paper analyzes the present situation of management of interest rate marketization in Henan Province, then puts forward some suggestions, such as promoting the development of intermediate business; promoting the product innovation; strengthening the management of assets and liabilities, improving the quality of employees, strengthening the management of non-performing loans, and etc.

人口老龄化视角下的家庭金融资产配置——基于CHFS的分析

为探究人口老龄化对于金融资产配置的影响,本文基于2019年中国家庭金融调查(CHFS),从深度与广度两个层面探究了家庭金融资产配置的生命周期特征。研究发现,风险资产比重在青壮年时期变化不大,而在55岁之后显著减少;股票资产占比、风险资产种数与年龄呈倒U型关系,并在45至55岁达到峰值;现金与银行存款的占比与年龄呈正相关关系。与此同时,本文分析了老龄化程度加深对家庭金融资产配置的影响,发现老年人口占比提升对家庭风险金融市场参与和风险资产配置产生了显著的抑制作用,而这一抑制作用受养老保险覆盖率与收入的调节,并存在地域异质性。机制分析发现,主观风险态度与金融素养是年龄结构影响家庭金融资产配置的重要途径。最后,针对我国人口老龄化背景下的家庭金融资产配置问题,本文结合实证所得结论提出相应的政策建议。

市场情绪与基金投资策略:迎合还是修正?

基金投资策略选择是学术界、监管者和市场参与者共同关注的焦点.本文根据行为资产定价理论将基金投资策略量化为组合收益的市场情绪敏感度,首次在微观层面对其按照市场状态分类界定为迎合情绪策略与修正情绪策略,通过理论模型和实证检验探究基金的投资策略选择对其流量、风险和经理努力程度产生的系统影响,从行为委托代理视角剖析基金业绩的影响机制.研究发现:基金采取迎合策略时,对投资者特别是个体投资者更有吸引力,但会对投资者利益造成隐性侵害,表现为基金未来的风险增大、收益降低,且基金经理在无需付出更多努力的情况下可获得更高报酬.进一步分析表明,基金经理为取悦投资者的消极放任行为是其业绩表现不佳的重要原因;基金采取修正策略时,产生的系列影响则完全相反.本研究为中小投资者的投资实践、基金治理与监管,及解释基金市场异象提供了新的思路与启示.

Fama-French-factor model,size and book-to-market effect:An empirical investigation of the Chinese stock market

In this study, we use Chinese A-share stock market data from 1995 to 2005 to test the persistence of the size and valueeffect and the robustness of the Fama-French three-factor model in explaining the variation in stock returns.Wefind that the three-factor model can explain the common variation in stock returns well.However, it is mis-specifiedfor the Chinese stock market.We demonstrate that the size effect and the book-to-market effect are significant andpersistent over our sample period.Interestingly, the book-to-market effect for China is much stronger than the averageones in mature markets and other emerging markets documented by Fama and French (1998).Moreover, we find noevidence to support the argument that seasonal effects can explain the results of the multifactor model.Last, our mixedobservations on firm-specific fundamentals suggest that the risk-based explanation proposed by Fama and French(1995) cannot shed light on the size and BM effect for China.In view of the features of the Chinese stock market, weinstead argue that China’s size and book-to-market effect may be attributed to syndicate speculators’ manipulation andmispricing caused by irrational investor behavior.

论中国碳市场不良资产的表现与法治应对

碳市场的不良资产代表了碳信用与交易预期落空的不良结果,存在基础不良资产、直接不良资产与进阶不良资产三种表现,拥有亏空价值虚拟性、成因复杂性等特征,对应形成干扰市场交易、阻碍低碳减排的双重危害。基于此,该研究采用规范分析、案例调研等方法,全面分析了碳市场不良资产的定性与法治约束现状,并尝试总结碳市场不良资产规制的理念要义与法治改革措施。研究发现:在不良碳资产的定性上,相应法律缺乏识别对应碳资产不良化的自觉,亦不具备界定其内容与范围的实践。在不良碳资产的预防上,已有的法治安排难以克服企业经营不当、市场环境不佳、虚假承诺与市场投机行为等导致资产不良化的负面因素。在不良碳资产的处置上,现行法律不仅在处置主体、处置内容、处置程序与处置救济领域存在规范空白,仅有的关联尝试亦未契合碳市场不良资产消化的经济规律。因此,有必要着眼于不良碳资产形成与消除的逻辑脉络:在理念层面,一是应推崇透明的竞争观,尽可能消除信息不对称所带来的非正义。二是需要破解利益博弈的“囚徒困境”,充分提振碳市场维持运行的信心、保持信息的顺畅流通、改变碳减排交易的利益总量预设,引导企业积极参与碳市场活动。三是应尽可能缩小承诺兑现的利益差距,避免价值泡沫的形成。在实践层面,一是应在规则与实践中明晰碳市场不良资产的属性、内容与影响。二是应形成预防不良碳资产累积的全面规制体系。三是需要以一体化思维应对碳市场不良资产的处置问题。

数字经济与企业垂直专业化分工:基于长三角的经验证据

数字经济与实体经济的结合是企业生产效率提高、国家经济转型升级的重要路径。在测度长三角地区41个地级市数字经济发展水平的基础上,利用2011—2021年A股上市公司数据,基于交易成本理论,考察长三角地区数字经济发展对企业垂直专业化分工水平的影响,其结果表明:(1)长三角数字经济发展显著促进企业垂直专业化分工水平提升;(2)异质性分析表明,对于非国有企业、制造业及高新技术行业企业,长三角数字经济发展对企业垂直专业化分工水平提升具有更强促进作用,且该影响在长三角核心地区、数字经济高水平地区以及非资源型城市中更显著;(3)机制分析表明,长三角地区数字经济发展通过降低企业资产专用性程度以及提高市场一体化水平两个途径促进企业垂直专业化分工。上述结论揭示了城市数字经济发展促进企业分工的机理,拓展了企业边界的相关研究,可为数字经济与实体经济相互融合从而优化产业结构提供启示。

国内外碳资产政策下油气企业应对措施研究

随着全球气候治理进程的推进,全球碳市场的建设不断完善,越来越多的国家开始建立国家或地方层面的碳交易体系。油气企业作为碳排放大户,做好碳资产管理成为其绿色低碳转型发展的关键。文章基于国际和国内碳资产政策现状研究,分析了国内外强制碳市场和自愿碳市场发展态势,碳边境调节机制(CBAM)和碳税实施的影响,碳捕集、利用与封存(CCUS)项目进入碳市场的交易方式和国内外大型能源企业参与碳资产管理的发展形势。结合油气企业碳资产管理特点,文章提出油气企业应加强碳排放管控水平、夯实碳排放量数据基础、组建碳资产开发专业机构以及推动CCUS项目获得国家政策支持等发展建议。

美国货币政策对中国投资价格影响的溢出效应——基于超调理论的解析

无论是2008年金融危机还是2020年新冠疫情,都对美国经济产生了严重影响。为了应对危机,美国采取了连续且高强度的量化宽松政策。这为美国经济提供了重要支撑,但对全球经济形成了明显冲击,特别是对中国经济稳定增长带来了挑战。文章从理论和实证两个方面讨论美国货币政策对中国投资价格的影响,并引入具有时变特征的TVP-VAR模型检验影响的多重现实作用机制,深入讨论美国货币政策对中国经济的影响。研究结果表明:美国货币政策会直接影响中国固定资产投资价格,也会通过中国股票市场对固定资产投资价格产生间接影响;在间接传导过程中,美国货币政策对中国股票价格的影响存在明显的超调效应,且这种超调效应只存在于短期;机制分析表明,美国货币政策对中国固定资产投资价格的间接影响会受到美国股票市场的调节作用。基于此,今后应审慎管理资本流动,稳步推进人民币国际化进程,增强金融行业的服务能力并加强政策引导,从而有效抵御外部金融风险,妥善应对各类风险挑战。

数据资产价值化实施路径分析

数据资产价值化是引领数据要素市场高速发展的核心驱动力,确权、定价与估值、创新应用价值服务是亟待“攻坚破局”的关键点。重点对数据资产的概念、数据资产价值的影响因素进行阐述,对数据资产价值化的实施路径进行深度分析。数据资产评估作为数据资产价值化过程中的重要一环,其评估结果直接影响到数据资产的价值和未来收益,通过对修正成本法和多期超额收益法两类模型的对比分析,对未来数据资产价值化的发展给出相应对策和建议。