Analysis and Forecast on the Car Market of Our Country

This paper is intended to forecast the demand of the car market and the quantity of car possession in our country in 2000 by means of two statistics methods, i.e. tendency inference and regression analysis, and then its future growth tendency and market demand in our country are analyzed, according to the strategy requirement and the actual facts of our car industry development.

Analysis of Chinese Power Market in 2007 and Its Forecast

Power supply and demand inJanuary-September, 2007Since 2007, the national economy developed continu-ously, showing a situation of rapid growth, more optimizedstructure, increased efficiency and improvement of people'slivelihood. In the first three quarters, GDP achieved 16.6043trillion Yuan, and its year-on-year growth rate was 11.5%;

Production Forecast of Citrus in China and Production and Marketing Situation of Citrus in Chongqing in 2016 Production Season

According to the statistics of the Ministry of Agriculture,the planting area of citrus would increase steadily,and the yield would decline slightly,2. 556 7 million ha and 36. 168 million t,respectively. Compared with 2015,the planting area would increase by 1. 97% and the yield would increase by 1. 17%. According to the production scheduling of Chongqing Agricultural Commission,the citrus production in Chongqing in 2016 would continue to maintain a steady and rapid growth,the estimated area and yield were 0. 206 7 million ha and 2. 8 million t,increasing by 4. 27% and 4. 48% compared with 2015 respectively. By the end of November 2016,most of mature citrus products in Chongqing would show different degree of rise in purchasing price,while the purchasing price of red orange and some processed raw material fruits would show different amplitude of decline. On the whole,the production and marketing situation of Chongqing citrus would become better.

Analysis and Forecast of China's Garments Market

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Research on the Dynamic Volatility Relationship between Chinese and U.S. Stock Markets Based on the DCC-GARCH Model under the Background of the COVID-19 Pandemic

This study utilizes the Dynamic Conditional Correlation-Generalized Autoregressive Conditional Heteroskedasticity (DCC-GARCH) model to investigate the dynamic relationship between Chinese and U.S. stock markets amid the COVID-19 pandemic. Initially, a univariate GARCH model is developed to derive residual sequences, which are then used to estimate the DCC model parameters. The research reveals a significant rise in the interconnection between the Chinese and U.S. stock markets during the pandemic. The S&P 500 index displayed higher sensitivity and greater volatility in response to the pandemic, whereas the CSI 300 index showed superior resilience and stability. Analysis and model estimation suggest that the market’s dependence on historical data has intensified and its sensitivity to recent shocks has heightened. Predictions from the model indicate increased market volatility during the pandemic. While the model is proficient in capturing market trends, there remains potential for enhancing the accuracy of specific volatility predictions. The study proposes recommendations for policymakers and investors, highlighting the importance of improved cooperation in international financial market regulation and investor education.

Collision of Two Plates——Market Movement Analysis into Home Made and Imported Cars

China’s car market consists of two plates——domestic made (A) and imported (B) cars. The market has experienced a transition process from the past "B strong v.s. A weak" to today’s "A strong v.s. B weak".

Relative Performance Evaluation of Competing Crude Oil Prices’ Volatility Forecasting Models: A Slacks-Based Super-Efficiency DEA Model

With the increasing number of quantitative models available to forecast the volatility of crude oil prices, the assessment of the relative performance of competing models becomes a critical task. Our survey of the literature revealed that most studies tend to use several performance criteria to evaluate the performance of competing forecasting models;however, models are compared to each other using a single criterion at a time, which often leads to different rankings for different criteria—A situation where one cannot make an informed decision as to which model performs best when taking all criteria into account. In order to overcome this methodological problem, Xu and Ouenniche [1] proposed a multidimensional framework based on an input-oriented radial super-efficiency Data Envelopment Analysis (DEA) model to rank order competing forecasting models of crude oil prices’ volatility. However, their approach suffers from a number of issues. In this paper, we overcome such issues by proposing an alternative framework.

The Role of Japanese Candlestick in DVAR Model

The decomposition-based vector autoregressive model （DVAR） provides a new framework for scrutinizing the efficiency of technical analysis in forecasting stock returns. However, its relation- ships with other technical indicators still remain unknown. This paper investigates the relationships of DVAR model with the Japanese Candlestick indicators using simulations, theoretical explanations and empirical studies. The main finding of this paper is that both lower and upper shadows in Japanese Candlestick Granger contribute to the DVAR model explanation power, and thus, providing useful information for improving the DVAR forecasts. This finding makes sense as it means that the infor- mation contained in the lower and upper shadows should be used when modeling the stock returns with DVAR. Empirical studies performed on China SSEC stock index demonstrate that DVAR model with upper and lower shadows as exogenous variables does have informative and valuable out-of-sample forecasts.

C_(3)产业链高质量发展研究及建议

分析预测了我国丙烯及其衍生物聚丙烯、丙烯腈、丙烯酸、苯酚/丙酮、环氧丙烷、丁辛醇等的市场供需情况;指出了我国C_(3)产业链产能全面过剩的原因;提出了新形势下进入C_(3)产业链的切入点、高质量发展建议。

我国蔬菜产业市场运行态势研究

近10年来,我国蔬菜种植面积、产量逐年增加,消费需求也明显上升,总供给和总需求基本平衡,市场运行总体比较稳健。蔬菜市场运行具有季节性波动、产地转换等五大特征。2023年,我国蔬菜市场产销两旺,市场价格高位运行,农业农村部重点监测的28种蔬菜全国批发价格全年平均是近10年来的最高价;展望2024年,蔬菜总供给和总需求基本平衡,略有结余。蔬菜市场主要面临气候变化、种植意愿、产销衔接等五大风险点。建议今后要进一步强化“菜篮子”建设、蔬菜地产地销、均衡上市、监测预警和政策扶持,努力实现蔬菜产业保供稳价和高质量发展。

MD&A纵向文本相似度与分析师盈余预测准确性

注册制下,信息的真实、准确、完整是投资者合理判断证券价值的关键,分析师在信息作用于股价这一过程中扮演着重要的信息中介角色,而年报所披露的信息对分析师盈余预测至关重要。以2012—2021年沪深A股上市公司为样本,探究了管理层讨论与分析(MD&A)纵向文本相似度对分析师盈余预测准确性的影响。研究发现,MD&A纵向文本相似度越高,分析师盈余预测准确性越低,证实了“增量信息”假说。异质性分析表明,这种影响显著存在于规模小、高科技行业、媒体关注度低的公司中,并且公司位于市场化程度低省份时受此影响更大。进一步研究发现,MD&A纵向文本相似度越高,分析师盈余预测的正向偏差越大。此外,分析师盈余预测准确性的下降会进一步降低资本市场的信息效率。因此,上市公司应重视文本信息披露,避免披露内容样板化;分析师和监管部门应加强对上市公司文本信息披露的监督,优化资本市场信息环境。

全国市场VS区域市场:碳市场有效性的差异、成因及其对策

对碳市场有效性进行测度、把握碳市场运行效率,有利于进一步推动碳交易机制优化和效率提升。本文以全国碳排放权交易市场及8个区域试点碳市场为研究对象,以2021年7月16日至2023年6月16日碳配额成交均价为样本,运用结构突变检验法与重标极差分析法对各个碳市场整体与阶段运行效率进行测度。研究结果表明:全国碳市场整体运行效率偏低,仅第一阶段达到了弱式有效水平;在区域试点碳市场中北京碳市场达到弱式有效,若考虑结构突变点时,则上海、广东、湖北、深圳和重庆碳市场达到阶段性弱式有效。在此基础上,进一步剖析了全国碳市场有效性较低的影响因素,并有针对性地提出对策建议。

近海浮式光伏成本分析与预测

随着世界能源转型进程加快及我国双碳目标确立,近海浮式光伏已成为重要海洋新能源。针对当前近海浮式光伏发展受制于成本收益不明确、发展前景未知的问题,首先依据内陆浮式光伏成本与涉海技术确定近海浮式光伏分项成本;其次通过计算光伏系统成本的经济指标,多角度分析近海浮式光伏经济效益;最后通过历史经济数据预测近海浮式光伏未来成本。结果表明,近海浮式光伏项目在未来10年成本显著降低,2024年由于补贴政策项目可实现收支平衡,2026年后补贴撤销,项目可独立盈利。

Riemann Hypothesis, Catholic Information and Potential of Events with New Techniques for Financial and Other Applications

In this research we are going to define two new concepts: a) “The Potential of Events” (EP) and b) “The Catholic Information” (CI). The term CI derives from the ancient Greek language and declares all the Catholic (general) Logical Propositions () which will true for every element of a set A. We will study the Riemann Hypothesis in two stages: a) By using the EP we will prove that the distribution of events e (even) and o (odd) of Square Free Numbers (SFN) on the axis Ax(N) of naturals is Heads-Tails (H-T) type. b) By using the CI we will explain the way that the distribution of prime numbers can be correlated with the non-trivial zeros of the function ζ(s) of Riemann. The Introduction and the Chapter 2 are necessary for understanding the solution. In the Chapter 3 we will present a simple method of forecasting in many very useful applications (e.g. financial, technological, medical, social, etc) developing a generalization of this new, proven here, theory which we finally apply to the solution of RH. The following Introduction as well the Results with the Discussion at the end shed light about the possibility of the proof of all the above. The article consists of 9 chapters that are numbered by 1, 2, …, 9.

PCTC市场分析与平均关键建造周期对标分析

基于英国克拉克森研究公司和全球主要船级社的网站数据,根据手持订单量和交付与完工情况对全球汽车卡车运输船(Pure Car and Truck Carrier,PCTC)进行市场分析,对全球PCTC平均关键建造周期进行对标分析,查找国内造船企业与国外造船企业的差距,为我国造船企业缩短PCTC建造周期提供改进目标。

农机装备再制造的市场需求分析与预测

在资源节约理念影响下,农机装备再制造产业得到快速发展,通过有效利用废旧农机设备,恢复或提高农机性能,有效降低了生产成本,提高了经济效益。农机装备再制造是农机装备产业转型升级的重要途径,以农机市场现状为出发点,分析了农机装备再制造的市场需求情况,总结农机装备再制造阶段性特点,并对未来市场发展特点进行预测,给出了产业发展的对策建议,以期利用农机装备再制造技术更好助力农业现代化发展。

高性能聚烯烃下游应用市场需求分析与预测

高性能聚烯烃是一类具有优异性能和功能的聚烯烃材料,广泛应用于汽车、电子电器、建筑、医疗等领域。近年来,随着科技进步和经济发展,高性能聚烯烃下游应用市场需求不断增长,呈现出巨大的发展潜力。对高性能聚烯烃下游应用市场现状、需求驱动因素、未来发展趋势等进行分析,并提出一些建议。

VPN网络技术的研究与发展趋势分析

近年来,随着IT技术的不断发展,以及人们对于网络数据传输、通信质量等需求的不断提高,虚拟专用网络(Virtual Private Network,VPN)技术成为网络技术关注的热点和关键问题。VPN技术的研究、应用将会向更加智能、尖端、成熟化的趋势发展。本文对VPN技术的产生背景、相关概念、原理和技术进行了阐释,对VPN技术市场应用情况和特点进行了分析,对用户需求开展调研,最后对VPN技术的发展趋势进行了预测和分析,旨在通过对VPN技术的研究与分析,为VPN技术研究人员和用户提供参考。

经济数学在金融经济分析中的应用研究

经济数学在金融经济中扮演着重要角色。文章通过分析经济数学在金融经济分析中的应用价值,系统阐述了其在投资决策、风险管理、金融市场预测等领域的应用方法,最后对经济数学在金融经济分析中的发展趋势进行了展望,旨在更好地发挥经济数学在金融经济分析中的应用价值。

基于微博公众情感状态的新产品市场预测研究

使用社交网络数据获取公众情感,进而预测新产品市场趋势已成为社会化网络环境下市场信息预测研究的新方法。本文研究了基于中文微博情感分析的新产品市场预测的相关问题。首先,根据心理学的《心境状态量表》(POMS),从《同义词词林》中提取出七维度心境词汇种子词集;利用《同义词词林》及word2vec构建中文心境状态词汇语义网络,并通过马尔可夫随机游走算法计算词汇各心境状态维度值,自动化地构建了一个多维度、细粒度的情感状态词典,以便获取微博公众情感状态信息。进一步提出一个整合微博公众情感状态、微博提及数、评论情感及其数量的预测特征模型,采用多任务机器学习方法处理不同提前期的新产品市场预测问题。基于电影数据的实例分析表明,公众情感状态特征能在更长的时段内反映新产品市场趋势,且基于整合的预测特征模型和多任务机器学习方法具有较好的预测效力和预测提前期。