房地产营销策划的市场分析

房地产营销策划的前提是房地产市场分析,而房地产市场调查又是做好房地产市场分析的首要条件。具体可从几个方面展开:一、市场营销环境分析市场营销环境分析,也就是分析楼盘营销活动与政治、经济、法律、自然、文化等环境的关联。市场调查应着重了解掌握以下信息:(一)与房地产有关的政策调控信息、房改措施信息等。这些是对整个房地产市场     

我国上市公司内部控制信息披露问题研究

上市公司内部控制信息是市场信息披露的重要组成部分,是影响市场投资人进行投资决策的重要因素,是市场投资人投资的重要理论依据,同时也是企业自身吸引融资的重要手段。文章基于我国上市公司内部控制信息披露的现状、存在的问题及解决问题的建议3个部分对此进行分析研究。     

信息不对称下的消费者行为探讨

信息不对称是现代经济学中十分重要的概念之一,它是指信息在市场交易双方之间的分布是不均匀的,一方对交易对象的内在属性比另一方更为了解。经济学分析了信息不对称引起的市场失效以及由此产生的逆向选择、道德风险等问题。本文尝试运用信息不对称理论对消费者行为进行分析,并尝试提出解决该信息不对称问题的一些建议。     

专有性成本与公司自愿性信息披露策略

运用数学模型,对专有性成本与上市公司自愿性信息披露水平、产品市场竞争策略与公司自愿性信息披露决策之间的关系进行分析。分析结果发现,专有性成本是公司信息披露决策中的重要影响因素。由于专有性成本的存在,公司在进行自愿性信息披露时,需要权衡其在资本市场上获得的收益和其在产品市场上保持的竞争优势这两者之间孰轻孰重。上市公司在产品市场中的竞争策略的选择也将影响其自愿性信息披露决策。     

证券市场信息不对称下风险防范的博弈分析

证券市场的公平与效率是建立在市场有效性基础上的,信息不对称严重影响市场的有效性。本文分析了信息不对称下证券市场中出现的上市公司信息披露的道德风险和逆向选择风险。并通过监督博弈分析,加强对上市公司信息披露不规范的惩罚力度和建立代理市场—声誉模型,并提出相应的政策建议。     

投资者视角下信息披露质量的测度:基础与框架

资本市场本质上是一个信息市场,信息披露是降低信息不对称,保护投资者利益的根本保证。基于投资者视角,文章在国内外相关文献的基础上,将信息披露全过程理解为信息生成、信息传递及信息反应的统一与整合,提出了一个包含测度目标、测度主体、测度客体、测度标准及测度方法的信息披露测度框架,从而尝试将已有研究纳入该理论分析框架,并为后续的进一步研究提供参考。     

用独立董事制度解决上市公司治理中的信息不对称问题

一、现代公司治理中的信息不对称现象 自阿克洛夫、斯彭斯和斯蒂格利茨分别探讨了产品市场、劳动力市场、保险及资金市场等领域存在的信息不对称问题以来,信息不对称理论一直是分析现代经济问题的重要工具(1).而且该理论在对现代公司治理中的信息不对称现象行为的分析也具有广泛的实际应用价值.在公司治理中,信息不对称现象主要存在于利益相关者之间.     

风险估值模型在衍生金融工具自愿信息披露中的应用

一、衍生金融工具自愿性会计信息披露的概述(一)会计信息披露动因的经济学分析新古典经济学的“有效性市场假定”认为信息是否充分是判断市场是否有效的基石,不同的信息产生不同的市场假定,罗伯茨把市场的有效性划分为弱势有效、次强有效和强有效。有效性市场假定是对传统的权威观点“公司的会计报告是获取公司信息的唯一来源,会计程序的差异和会计盈利将影响公司的市场价值”的否定:市场的有效性建立在完全信息基础上,没有信息的自由、充分地流动,股价就不可能包含所有的信息,股价的变动过程也并非随机行走过程。因此,会计的目标应是向用户…     

卖方优势市场和买方优势市场之比较——市场格局的信息经济学新解

信息不足是市场失灵的一个重要根源。买卖双方信息不对称会造成价值规律不能正常发挥作用,使买方或卖方遭遇意外损失。面对这种情况,买主和第三方如行业协会、行政主管部门、法律等会有相应的措施,那么,作为卖方的企业该如何主动应对呢?下面就此做些分析。一、概念界定卖方优势市场是指卖方比买方拥有对交易至关重要的、更多的信息的市场,买方优势市场是指买方比卖方拥有对交易至关重要的、更多的信息的市场。可见,这二个概念与“买方市场和卖方市场”两个概念是不同的。买方市场是指供过于求的市场,卖方市场是指供不应求的市场。卖方优势市…     

浅析信息的生产者、消费者与市场效率之间的关系

我们通过信息经济学这个主题,即研究信息资源如何配置影响信息福利经济的课题。我们从考察信息提供者和信息需求者从参与信息市场中得到的利益开始,然后我们考虑社会如何使这种利益尽可能达到最大。分析的结论:信息市场上的供求均衡可以使信息提供者和信息需求者的总利益最大化。信息市场通常是组织经济活动的一种好方法。     

基于主成份回归的国际原油价格分析与预测

基于国际石油市场的复杂性,文章考虑了影响原油价格的多方面因素,采用主成份分析的方法,从影响油价的众多因素中提取出能够反映原始变量的足够多信息的几个主成份,然后利用主成份对油价进行回归建立油价预测模型。并且对WT(I西德克萨斯轻质)原油月度价格进行了实证分析,说明了此方法的可行性及有效性。     

Exchange rates and oil prices: A multivariate stochastic volatility analysis

This paper uses the multivariate stochastic volatility (MSV) and the multivariate GARCH (MGARCH) models to investigate the volatility interactions between the oil market and the foreign exchange (FX) market, in an attempt to extract information intertwined in the two for better volatility forecast. Our analysis takes into account structural breaks in the data. We find that when the markets are relatively calm (before the 2008 crisis), both oil and FX markets respond to shocks simultaneously and therefore no interaction is detected in daily data. However, during turbulent time, there is bi-directional volatility interaction between the two. In other words, innovations that hit one market also have some impact on the other at a later date and thus using such a dependence significantly improves the forecasting power of volatility models. The MSV models outperform others in fitting the data and forecasting exchange rate volatility. However, the MGARCH models do better job in forecasting oil volatility.     

The role of oil futures intraday information on predicting US stock market volatility

This study investigates the role of oil futures price information on forecasting the US stock market volatility using the HAR framework. In-sample results indicate that oil futures intraday information is helpful to increase the predictability. Moreover, compared to the benchmark model, the proposed models improve their predictive ability with the help of oil futures realized volatility. In particular, the multivariate HAR model outperforms the univariate model. Accordingly, considering the contemporaneous connection is useful to predict the US stock market volatility. Furthermore, these findings are consistent across a variety of robust checks.     

Volatility forecasting in the Bitcoin market: A new proposed measure based on the VS-ACARR approach

This paper proposes a new volatility-spillover-asymmetric conditional autoregressive range (VS-ACARR) approach that takes into account the intraday information, the volatility spillover from crude oil as well as the volatility asymmetry (leverage effect) to model/forecast Bitcoin volatility (price range). An empirical application to Bitcoin and crude oil (WTI) price ranges shows the existence of strong volatility spillover from crude oil to the Bitcoin market and a weak leverage effect in the Bitcoin market. The VS-ACARR model yields higher forecasting accuracy than the GARCH, CARR, and VS-CARR models regarding out-of-sample forecast performance, suggesting that accounting for the volatility spillover and asymmetry can significantly improve the forecasting accuracy of Bitcoin volatility. The superior forecast performance of the VS-ACARR model is robust to alternative out-of-sample forecast windows. Our findings highlight the importance of accommodating intraday information, spillover from crude oil, and volatility asymmetry in forecasting Bitcoin volatility.     

基于成品油双寡头有限竞争市场的集团客户采购对策研究

中国成品油市场是一个特殊的双寡头垄断有限竞争市场。通过对成品油市场结构和成品油寡头博弈行为的分析,得出产量博弈的状况近期不会出现、价格博弈将使企业走入囚徒困境的结论。然后,结合博弈结果以及现实情况,对集团用户以及成品油其他生产者的行为进行进一步分析,提出集团用户成品油采购对策。     

Mutual excitation between OECD stock and oil markets: A conditional intensity extreme value approach

We analyze the degree of mutual excitation that exists between extreme events across the stock markets of OECD member nations and the Brent and WTI crude oil markets. For this analysis, marked point process models are proposed which are able to capture the dynamics of the intensity of occurrence and comovement during periods of crisis. The results show a significant, negative interdependence between most OECD markets, especially those of the USA, Japan and France. These major oil importing countries display links between equity market losses and positive returns in both oil markets. However, positive interdependence is not observed between any of the OECD countries except for South Korea. The great advantage of this methodology is that, apart from using the size distribution of extreme events, it also uses the occurrence times of extreme events as a source of information. With this information, these models are better able to capture the stylized facts of extreme events in financial markets such as clustering behavior and cross-excitation.     

关于中国粮食产业问题的思考

目前我国粮油市场正处在政策指导与市场调解互补的矛盾之中,文章通过分析我国粮油市场现状,提出了国家粮食安全问题关于粮食安全问题,仅供参考。     

Does oil price variability affect the long memory and weak form efficiency of stock markets in top oil producers and oil Consumers? Evidence from an asymmetric MF-DFA approach

This study examines the asymmetric multifractality and the market efficiency of the stock markets in the countries that are the top crude oil producers (USA, KSA, Canada and Russia) and consumers (Brazil, China, India, and Japan) using an asymmetric multifractal detrended fluctuation analysis (A-MF-DFA) method. The results show evidence of an asymmetric multifractal nature for all markets. Moreover, the multifractality is stronger in the upward movement of the market returns, except in China. The degree of efficiency of the stock markets is shown to be time-varying and experienced a decrease during the 2008 global financial crisis (GFC), but an upside trend occurred during the recent oil price crash followed a significant decline during COVID-19. The stock markets have an anti-persistent feature during GFC and COVID-19, whereas they exhibit a long-term persistent feature during oil price crash. More interestingly, the efficiency of the stock markets of crude oil producers is lower in general than that of oil consumers. Furthermore, the efficiency of the stock market is lower in the downward movement of the market returns than in the upward movement. Asymmetry and oil price uncertainty index are the key driver of the stock markets and can serve as predictor of the stock market dynamics of top oil producers and top oil consumers particularly during COVID-19 and oil price crash.     

基于小波变换和支持向量的国际原油价格预测

本文将小波分析与支持向量回归结合应用于国际原油价格预测,通过小波多尺度分析方法将油价时间序列分解为长期趋势和随机扰动项,然后采用支持向量回归对分解后的油价长期趋势进行预测。油价长期趋势的预测采用多因素预测方法,主要考虑市场供需基本面、库存、经济、投机等因素对石油价格走势的影响,建立多输入单输出的支持向量回归模型。实证研究表明,支持向量回归模型具有较高的预测性能,对原油价格长期趋势预测中,该方法比回归方法的预测精度高。     

上市公司信息披露的博弈分析

本文从不完全信息博弈的角度,对上市公司信息披露的现状及问题进行了分析,揭示了我国信息披露机制存在的问题。发现在市场经济条件下,上市公司、投资者追求利益最大化的博弈行为。根据分析结果提出规范上市公司信息披露的途径,以加深人们对真实披露会计信息重要性的认识。