PB的落后因素与偏差因素对未来ROE的影响研究
发布时间：2018-07-22 14:44
【摘要】：净资产收益率是衡量企业盈利能力的重要指标之一，投资人在考虑投资回报时重点关注未来净资产收益率。目前，在预测未来净资产收益率方面主要是通过对企业所处的外部因素（宏观环境、行业环境、经营环境）与内部因素（企业内部资源、企业能力、市场竞争力）进行分析，得出未来的投入与产出，从而预测净资产收益率。本文旨在通过将市净率进行分解，得到提高预测能力的方法，通过量化的方法从另一个角度预测未来净资产收益率,为投资人提供决策依据。 本文主要研究市净率的落后因素与偏差因素以及二因素对未来净资产收益率预测能力，通过将市净率分解成落后因素与偏差因素，以求找到提高预测未来净资产收益率的方法。在研究过程中，先将市净率进行分解，将影响市净率暂时不为1的因素归入到落后因素，将影响市净率长期不为1的因素归入到偏差因素，分别求落后因素与偏差因素。求解出落后因素与偏差因素后，分别求出市净率的落后因素与未来净资产收益率负相关，而市净率的偏差因素与未来净资产收益率正相关。 在计算出落后因素与偏差因素后，，再求解未分解前市净率对未来净资产收益率的预测能力和分解成落后因素与偏差因素后的市净率对未来净资产收益率的预测能力。实证过程主要对面板数据进行分析，采用系统广义矩估计法。考虑到我国二级市场成立才20余年，尚未成熟，在实证分析中仅选取更具代表性的沪深300指数成份股。通过实证研究发现，市净率对未来净资产收益率预测几乎无预测能力，而分解成落后因素与偏差因素后的市净率对未来净资产收益率有着更强的预测能力。
[Abstract]:The ROE is one of the most important measures to measure the profitability of an enterprise. Investors focus on the future ROE when considering the return on investment. At present, in predicting the rate of return on net assets in the future, we mainly analyze the external factors (macro environment, industry environment, business environment) and internal factors (internal resources, enterprise capability, market competitiveness) of the enterprise. Get the future input and output, so as to predict the return on net assets. The purpose of this paper is to obtain a method to improve the forecasting ability by decomposing the price-to-book ratio, and to predict the future return on net assets from another angle through the quantitative method, which provides the basis for investors to make decisions. This paper mainly studies the backward factors and deviation factors of the price-to-book ratio and the ability of two factors to predict the future return of net assets. By decomposing the price-to-book ratio into backward factors and deviations, we can find a way to improve the forecast of the future return of net assets. In the course of the study, the price-to-book ratio is decomposed first, the factors that affect the price-to-book ratio are classified as the backward factors, the factors that affect the price-to-book ratio are classified into the deviation factors, and the backward factors and the deviation factors are obtained respectively. After solving the backward factors and deviation factors, the backward factors of price-to-book ratio are found to be negatively correlated with the future return on net assets, while the deviation factors of the price-to-book ratio are positively correlated with the future return on net assets. After the backward factors and deviation factors are calculated, the prediction ability of P / E ratio to the future net asset return rate before decomposition and the forecasting ability of P / E ratio to the future net asset return rate after being decomposed into backward factors and deviation factors are solved. The empirical process mainly analyzes the panel data and adopts the system generalized moment estimation method. Considering that China's secondary market has only been established for more than 20 years and has not yet matured, only the more representative Shanghai and Shenzhen 300 index stocks are selected in the empirical analysis. Through the empirical study, it is found that the price-to-book ratio has little ability to predict the future return of net assets, but the price-to-book ratio, which is decomposed into backward factors and deviation factors, has a stronger ability to predict the future return of net assets.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F275;F832.51
本文编号：2137799
[Abstract]:The ROE is one of the most important measures to measure the profitability of an enterprise. Investors focus on the future ROE when considering the return on investment. At present, in predicting the rate of return on net assets in the future, we mainly analyze the external factors (macro environment, industry environment, business environment) and internal factors (internal resources, enterprise capability, market competitiveness) of the enterprise. Get the future input and output, so as to predict the return on net assets. The purpose of this paper is to obtain a method to improve the forecasting ability by decomposing the price-to-book ratio, and to predict the future return on net assets from another angle through the quantitative method, which provides the basis for investors to make decisions. This paper mainly studies the backward factors and deviation factors of the price-to-book ratio and the ability of two factors to predict the future return of net assets. By decomposing the price-to-book ratio into backward factors and deviations, we can find a way to improve the forecast of the future return of net assets. In the course of the study, the price-to-book ratio is decomposed first, the factors that affect the price-to-book ratio are classified as the backward factors, the factors that affect the price-to-book ratio are classified into the deviation factors, and the backward factors and the deviation factors are obtained respectively. After solving the backward factors and deviation factors, the backward factors of price-to-book ratio are found to be negatively correlated with the future return on net assets, while the deviation factors of the price-to-book ratio are positively correlated with the future return on net assets. After the backward factors and deviation factors are calculated, the prediction ability of P / E ratio to the future net asset return rate before decomposition and the forecasting ability of P / E ratio to the future net asset return rate after being decomposed into backward factors and deviation factors are solved. The empirical process mainly analyzes the panel data and adopts the system generalized moment estimation method. Considering that China's secondary market has only been established for more than 20 years and has not yet matured, only the more representative Shanghai and Shenzhen 300 index stocks are selected in the empirical analysis. Through the empirical study, it is found that the price-to-book ratio has little ability to predict the future return of net assets, but the price-to-book ratio, which is decomposed into backward factors and deviation factors, has a stronger ability to predict the future return of net assets.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F275;F832.51
【参考文献】
相关期刊论文 前10条
1 刘昱熙;宋旺;;股票回报与公司规模、市净率、市盈率之间的关系——基于中国A股市场的实证论证[J];财会通讯;2011年06期
2 韩良智;每股收益与净资产收益率辨析[J];财会月刊;2004年18期
3 张亚东;朴军;;中国A股公司市盈率、市净率与ROE水平的关系研究[J];管理工程学报;2007年04期
4 段琼;;市盈率与市净率分析[J];经营管理者;2009年08期
5 夏云峰;对净资产收益率指标反映上市公司盈利能力问题的探讨[J];广西会计;2002年12期
6 孙宏廷;;长期投资选低市净率股票[J];股市动态分析;2012年09期
7 仝玉东;浅谈财务分析指标:净资产收益率[J];经济师;2002年07期
8 卢荻千;;基于分位数回归的净资产收益率研究——来自2008年我国上市公司的财务数据[J];金融经济;2009年20期
9 李胜军;;市净率、市售率在上市公司投资价值分析中的应用[J];价值工程;2012年05期
10 毛新述;戴德明;;论公允价值计量与资产减值会计计量的统一[J];会计研究;2011年04期
相关硕士学位论文 前2条
1 赵颖洁;股票的多因素定价模型的研究[D];西安建筑科技大学;2009年
2 苏晓薇;我国上市公司无形资产与企业价值相关性研究[D];东北大学;2007年
本文编号：2137799
本文链接：https://www.wllwen.com/jingjilunwen/zbyz/2137799.html
