基于因子及聚类分析的甘肃省营商环境综合评价分析

本文基于因子分析和聚类分析方法研究甘肃省2020年营商环境状况。首先从政府行为、经济发展、科技创新等方面选取11个指标构建区域营商环境评级指标体系；其次运用因子分析法，通过SPSS软件提取经济实力因子、基础民生因子2个公因子，并且计算出14个地市在这两个公因子上的得分和综合得分；进一步的，通过系统聚类法将甘肃省14个地市的营商环境划分为3类，其中兰州市为第一类，天水市、庆阳市等为第二类，金昌市、甘南州等为第三类；最后提出了提升甘肃省营商环境的相关政策建议。     

基于因子分析和聚类分析的地域经济发展比较研究——以山东17地市为例

地域经济发展的平衡性对于省级行政区域乃至全国的协调发展至关重要。山东省作为国家蓝色经济区建设的特色省份,在全国经济发展中占有重要地位。本文综合考量山东地区17地市2011年经济发展的13个指标,基于多元统计的方法进行研究分析。首先进行因子分析,从众多指标中提取出两个公因子;然后对结果进行分层聚类,分析各市因子得分和排名,在此基础上进行综合比较。最后,探究了各地市发展不均衡的深层次原因。     

安徽省上市公司综合绩效评价

主要通过运用因子分析法并结合SPSS软件,对安徽省77家上市公司2012年的年报数据进行了多角度、多层次分析。文章选取了具有代表性的15个财务指标数据,首先进行因子分析,提取出反映上市公司盈利能力、经营能力、偿债能力和成长能力四个方面状况的公因子,并对各因子进行分类分析,然后在此基础上建立综合绩效评价模型。     

新三板农业挂牌企业业绩评价

文章选取了36家在全国中小企业股份转让系统挂牌的农业企业,运用因子分析的方法,以公开披露的2014年年报数据为基础,选取16个财务指标作为原始数据,提取6个公因子,建立了企业业绩评价因子分析模型,运用该模型对研究对象的企业业绩进行评价.最终的实证结果表明:综合来说,新三板农业挂牌企业发展质量不高;而且各家企业发展不均衡现象比较普遍,总体上规模扩张能力和业务成长能力比较突出,但偿债能力、盈利能力、营运能力和资产管理能力有待加强,并根据结论提出了相关建议.     

上市公司业绩与流通性相关分析

本文运用因子分析方法进行数据浓缩，提取了体现上市公司业绩的主因子“规模因子”和“收益因子”两个作为反映上市公司业绩的指标，并运用相关分析的方法对主因子及其各变量与上市公司股票流通性的相关性进行了进一步说明。     

因子分析的理论综述

因子分析是从多个变量中选择出几个综合变量的一种降堆多元统计分析方法，其核心是将原有变量的绝大部分信息用较少的几个相互独立的因子反映出来，以达到数据简化的目的；本文从因子分析的本思想、相关模型、基本步骤、基本方法等方面来对其进行了综述，发现采用因子分析方法来分析各个领域中存在的问题已成为解决当今社会中各类信息的主流方法。     

基于分位数因子分析方法的系统性金融风险测度

尾部风险是系统性金融风险爆发的重要导火索，而常用于系统性金融风险测度的因子分析方法一般是从均值角度进行构建。为从尾部视角构建更加及时有效的系统性金融风险指标，本文选取了122个申万二级行业指数的日度收益率，采用分位数因子分析方法，构造了金融市场的尾部风险因子。通过与均值风险因子进行比较发现：（1）尾部风险因子在风险事件刻画和风险预警方面均具有优势；（2）其优势在于尾部风险因子除包含水平信息以外，还具有风险信息；（3）其风险信息不仅对未来市场价格信息具有边际的预测能力，还是风险预警能力的主要来源。本文的研究结果将有助于提升我国的系统性金融风险预警效率，为维护金融稳定提供参考。     

基于因子分析和聚类分析的企业投资价值评价研究——以沪深300股指为例

文章运用因子分析和聚类分析对沪深300股指进行实证分析，通过因子分析将9个重要的财务指标归纳为4个主要因子，即估值因子、盈利因子、质量因子和成长因子。这4个主要因子包含了原始数据80.65%的信息，因此用这4个主要因子替代原来的9个指标来评价上市企业的投资价值。以因子分析得到的4个主因子得分为基础，采用聚类方法对不同层次的数据进行聚类分析，根据“数据聚类树”将300家上市企业分为4类。在此基础上，得出主因子得分和平均综合得分，对各类上市企业的投资价值进行客观评价，旨在为股票投资者分析上市企业的发展前景和股票升值空间提出可行性、科学性和具体性建议。     

基于理财客户个性特征的市场细分与差异性分析

大多数银行还没有形成一个系统、科学的客户细分方法体系.本文从客户心理因素和个性特征的视角出发,对个人理财客户进行市场细分.首先对文中的最客观、最具体的理财客户个性特征变量进行因子分析,萃取出4个个性特征维度,然后选择四个公因子的因子得分作为聚类变量,参与聚类分析,将客户分为3个类别.最后比较三类客户的心理因素特征及个性特点差异、个人银行业务需求差异、客户满意度以及客户忠诚度的差异.在市场细分的基础上制定差异化、有针对性的营销策略.     

居民收入与国民经济协调增长预警机制研究——基于国家治理视角

本文从国家治理的视角,把国民经济与居民收入增长作为经济内生因素,从国民经济、居民收入等一系列相关经济变量中提取反映共同趋势的公因子,根据公因子的变化构建了我国居民收入与国民经济协调增长预警模型,并据此对我国当前状况进行了初步评估,提出了启动响应机制的政策建议。     

Risk evaluations with robust approximate factor models

Approximate factor models and their extensions are widely used in economic analysis and forecasting due to their ability to extracting useful information from a large number of relevant variables. In these models, candidate predictors are typically subject to some common components. In this paper we propose a new method for robustly estimating the approximate factor models and use it in risk assessments. We consider a class of approximate factor models in which the candidate predictors are additionally subject to idiosyncratic large uncommon components such as jumps or outliers. By assuming that occurrences of the uncommon components are rare, we develop an estimation procedure to simultaneously disentangle and estimate the common and uncommon components. We then use the proposed method to investigate whether risks from the latent factors are priced for expected returns of Fama and French 100 size and book-to-market ratio portfolios. We find that while the risk from the common factor is priced for the 100 portfolios, the risks from the idiosyncratic factors are not. However, we find that model uncertainty risks of the idiosyncratic factors are priced, suggesting that with effective diversifications, only the predictable idiosyncratic risks can be reduced, but the unpredictable ones may still exist. We also illustrate how the proposed method can be adopted on evaluating value at risk (VaR) and find it can delivery comparable results as the conventional methods on VaR evaluations.     

Bayesian analysis of the factor model with finance applications

The factor analysis model has been widely applied to study finance problems. The purpose of this paper is to introduce a Bayesian approach for analysing the factor analysis model. The advantages of the proposed Bayesian approach over the classical maximum likelihood rest on its capability to incorporate additional prior information, to determine the number of factors in an objective manner, and to produce parameter and factor score estimates with good statistical properties. Based on recently developed tools in statistical computing, such as the Gibbs sampler and path sampling, methods for obtaining the Bayesian estimates of the parameters and factor scores, and a procedure for computing the Bayes factor for selecting the appropriate number of factors in the model, are developed. The proposed new methodologies are applied to analyse a data set taken from the Hong Kong stock security market. It is found that a three-factor model with a generic market factor can be used to describe the systematic components of asset returns.     

Factor based index tracking

Stock index tracking requires to build a portfolio of stocks (a replica) whose behavior is as close as possible to that of a given stock index. Typically, much fewer stocks should appear in the replica than in the index, and there should be no low frequency or integrated (persistent) components in the tracking error. The latter property is not satisfied by many commonly used methods for index tracking. These are based on the in-sample minimization of a loss function, but do not take into account the dynamic properties of the index components. Moreover, most existing methods do not take into account the known structure of the index weight system. In this paper we represent the index components with a dynamic factor model. In this model the price of each stock in the index is driven by a set of common and idiosyncratic factors. Factors can be either integrated or stationary. We develop a procedure that, in a first step, builds a replica that is driven by the same persistent factors as the index. This procedure is grounded in recent results which suggest the application of principal component analysis for factor estimation even for integrated processes. In a second step, it is also possible to refine the replica so that it minimizes a specific loss function, as in the traditional approach. In both steps the replica weights depend on the existing information on the index weights system. An extended set of Monte Carlo simulations and an application to the most widely used index in the European stock market, the EuroStoxx50 index, provide substantial support for our approach.     

Determinants of smallholder farmers' perceptions of risk in the Eastern Highlands of Ethiopia

This paper reports findings from a study of 178 farm households from two contrasting areas in the Eastern Highlands of Ethiopia. It examines risk perceptions of smallholder farmers under varying contexts. The study utilized both qualitative and quantitative methods of data collection and analysis. It was hypothesized that human capital and household characteristics and orientation, access to resources, infrastructure, information and environmental factors influence perceptions of risks in different ways. Data reduction for independent variables was done by factor analysis (principal component extraction method). Factor analyses identified factors influencing smallholder farmers' perceptions of sources of risks. Logistic regression analyses were used to study the relationships of identified principal components to perceived frequencies of occurrences and consequences of various sources of risks. Logistic regression analyses revealed that asset endowments, locational settings and livelihood diversification strategies pursued determine smallholders' perceived risks. Key findings from the informal survey point out differentiation in perceptions of causes and sources of risks by different actors.     

中国金融业专利的发展特征及影响因素分析

本文通过对1985年以来国内金融业专利状况的统计分析,发现其发展具有以下特征:第一,申请数量2000年以来发生了大幅波动;第二,申请者结构发生了改变;第三,主要集中在传统银行业务的电子化和网络化方面;第四,国外申请者的申请数量接近一半,并且在发明专利的占比上远远超过内地金融机构。本文的实证部分利用多元回归和主成分分析方法,发现中国金融业竞争程度和金融业对外开放程度所代表的需求性因素是影响金融业专利发展的主要原因。     

稀疏主成分在综合评价中的应用

稀疏主成分分析是最近才提出来的一种多元统计分析方法,并成功地用来解决若干降维和数据处理问题,论文分析和总结了稀疏主成分的优点,给出了求解各种稀疏主成分的算法,并将各种稀疏主成分分析方法引入综合评价,通过实例说明了稀疏主成分在综合评价应用中的有效性.     

A latent factor model for the Chinese stock market

We propose a new latent factor model for the Chinese stock market based on an instrumented principal component analysis (IPCA). Compared with other common asset pricing models, the new latent factor model explains a larger proportion of individual and portfolio return variation and shows significant out-of-sample predictability. The long-short investment strategy formed by the IPCA factor also presents the highest average return and Sharpe ratio. Subsample and different horizon results are robust. Market beta, profitability and momentum emerge as the most important characteristics in driving the latent factors. We also provide evidence on the economic grounds of the new latent factor model.     

Identification and evaluation of risk factors related to provincial food insecurity in China

Understanding the risk factors which could cause provincial food insecurity is of great importance for maintaining China’s food security. In this research, fault-tree analysis has been used to identify risk sources and corresponding risk factors, and both the ratio and growth rate analysis method and the risk coefficient method have been used to evaluate the risk profile for each province. The results showed that constrained land resources and natural disasters were the most common risk factors and agricultural machinery inputs were the least frequent risk factor across all provinces. Fertilizer inputs were no longer a risk in 16 high-yielding provinces. Among natural disaster risks, floods mainly occurred in the eastern, northeastern, central, southern, and southwestern regions, with droughts predominately located in the northern, northeastern, western, and southwestern regions. Overall, natural disasters in major grain-producing provinces were much more serious than in other provinces. Methodical construction of agricultural infrastructure and building of early warning systems for natural disasters should be proposed to reduce losses due to natural disasters and policies on fertilizer application should shift from actively encouraging more use to controlling excess application. Those provinces that now are able to fulfill their food-security mandates should shift their focus to resource and environmental sustainability.     

区域金融生态评估方法比较研究

评估方法的运用极大地影响着金融生态评估结果的科学性和有效性。本文针对常用的正态标准化、专家法、标准差加权、因子分析以及层次分析法、模糊综合评价等方法进行比较研究,深入分析各种方法的优势和不足,为开展评估提供参考。     

A framework for the analysis of interview data from multiple field research sites

In general, papers reporting the results of research studies disclose little detail regarding attributes of study design, analytical processes and methods actually used by researchers. This paper describes in some depth the method choices and analytical protocol used in a field study project. The paper describes initially the link between research question, research design and analytical protocol. The major focus of the paper is the application of a systematic analytical protocol designed to encourage completeness and impartiality in the collection and analysis of qualitative data. These method issues are examined in the context of the author's experiences in the field and through the process of data analysis. The methods used are also examined critically in retrospect.