**real estate**class of 2007, China's Shanghai and Shenzhen A-share

**listed companies**in the study sample, using 14 indicators using statistical software SPSS15.0, using factor analysis to evaluate the

**ability**of real estate listed companies. The evaluation results indicate that different samples of the score differences as a dividing point average, comprehensive ability and poor each half, and no significant regional differences. ª¥

Keywords: real estate; listed companies; Factor Analysis; comprehensive ability ª¥

0 Introduction ª¥

In recent years, with the Chinese residents housing reform push further in depth, the real estate industry has developed into a pillar industry of China's national economy, to become the main driving force of China's economic development and China's new economic growth point. ª¥

Paper selects the data of 44 real estate listed companies listed on the Shanghai and Shenzhen in 2007, using 14 indicators, using statistical software SPSS15.0 adopted to determine the weight of each index based on the size of the amount of information provided by the various indicators of the actual observations objective weighting method - factor analysis to empirical research, comprehensive ability to evaluate the real estate listed companies.

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A study sample to determine ª¥

In this paper, the listed real estate companies in the China Securities Regulatory Commission listed companies Industry Classification Guidelines as a sample basis. For the study sample in 2007, China's real estate listed companies, excluding the B-share listed companies, the ST company as well as the evaluation indicators there are abnormal value of the company, and finally selected 44 listed real estate companies for the study, evaluation of the listed real estate companies and analysis. Due to limited space, not elaborate here. ª¤

Determination of the evaluation and data sources

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2.1 Evaluation determine ª¥

Choose to participate in the comprehensive evaluation index directly affect the results of the evaluation. Principle of comprehensive, systematic, comprehensive, scientific, purpose, relevance of indicators based on the availability from the short-term solvency and long-term solvency, shareholder profitability and viability of seven, the ability to grow, profitability, development ability to create a listed real estate companies comprehensive capacity evaluation. Screening indicators through the following steps: First, the exclusion of more indicators of missing values; Secondly, the use of screening choose typical indicators and principal component analysis. Eventually selected 14 indicators: current ratio (X

_{ 1 }), quick ratio (the X-

_{ 2 }), asset-liability ratio (X

_{ }), the ratio of net assets (the X

_{ 4 }), inventory turnover rate (X

_{ 5 }), total asset turnover ratio (X

_{ 6 }), Net profit margin (X

_{ 7 }), return on total assets (X

_{ 8 }), ROE (X

_{ 9 }), earnings per share (X

_{ 10 }), the per share net asset (X

_{ 11 }), the main income growth rate (the X

_{ 12 }), net profit growth rate ( X

_{ 13 }), total assets growth rate (X

_{ 14 }). ª¤

2.2 Data sources ª¥

Listed real estate companies involved data from the financial community website and CHINF. ª¤

3 Factor Analysis ª¤

3.1 raw data preprocessing ª¥

Listed companies comprehensive evaluation of the data collected is not directly a comprehensive evaluation and processing of data, excluding outliers, becomes modest indicators and inverse indicator for the positive indicators, while eliminating the impact of extreme values ??and dimensionless, to make comprehensive The evaluation results more reasonable. Target 14 according to the above selection, using standard differential standardized methods for data processing. ª¤

3.2 factor extracted ª¥

First standardization of the original indicators based on principal component analysis and calculate the correlation matrix between the standardized indicators, followed by calculation of the relative amount of the characteristic roots of the matrix and features. And descending order, were calculated which corresponds to the main component. The characteristic value of the first six factors meet the standards of greater than 1. According to the cumulative variance contribution rate factor, run basic model contains 18 variables, five factors can be obtained, these five factors that the cumulative proportion of variance explained 78.102 percent, 78.102 percent of the original indicators that can reflect the first five common factor The amount of information. Table 1. ª¥

The economic significance of the 3.3 factor explained ª¥

After factor analysis of factor F ª 1, F ª 2, F ª 3, F ª 4, F ª 5 of the original variables comprehensive. In this paper, the most used varimax factor rotation, it makes the minimum number of variables with the highest load on each factor, you can simplify the interpretation of the factors. As can be seen from the rotated factor loading matrix: ª¥

(1) The common factor F ª 1 in total asset turnover ratio (X

_{ 6 }), the main income growth rate of inventory turnover rate (X

_{ 3 }), (X-

_{ 12 }), net profit growth rate (X

_{ 13 }) higher loads, these variables reflect the company's profitability and ability to grow, and therefore named the profitable growth factors. (2) the common factor F ª 2 in the asset-liability ratio (X

_{ 3 }) and net assets ratio (X

_{ 4 }) higher loads, these two variables reflect The long-term solvency of the enterprise, so named for the long-term debt service factor. (3) common factor F ª 3 in the net profit margin (X

_{ 7 }), return on total assets (X

_{ 8 }) and ROE (X

_{ 9 }) higher loads, these three indicators reflect the profitability of the enterprise, and therefore named as a profitability factor. F ª 4 (4) common factors in earnings per share (X

_{ 10 }), per share net asset (X

_{ 11 }) and total assets growth rate (X

_{ 14 }) has a higher load on the three indicators reflect a corporate shareholder profitability and development capacity, and therefore named shareholder profit development factor. (5) The common factor F ª 5 higher load current ratio (X

_{ 1 }) and a quick ratio (X

_{ 2 }), these two indicators reflect short-term solvency of the enterprise, so named for the short-term debt factor. ª¤ 3.4 factor score ª¥

Factor variables identified scores of specific data values ??of the original sample data on different factors, and the original score of the variable corresponding Can be calculated based on the calculated factor score function of the coefficient, which can write function scores. Then, the variance contribution rate of weight on each factor score by summing the total factor score. Due to limited space, this article lists only the composite score and each factor score is not listed. Table 2. ª¥

4 Based on the analysis of the empirical results of factor analysis ª¥

Reasonable explanation of the five factors, combined with the individual scores and composite score of listed companies in various public factor can evaluate the comprehensive capacity of 44 real estate listed companies. ª¥

(1) analysis of the composite score. ª¥

Composite score above, we can see that the ranking of the different companies. The top three in order Dingli shares, seabirds development, celebrity home, we usually think of the leading real estate Vanke ranked in the first 15. This analysis indicators selected by this decision, different indicators of the analysis is bound to come to different results. Can be seen from the results, Vanke ranking of each factor is not very front, the top three companies in the first, two of each factor on the score almost all the top several first two factor scores the weights, so that led to this result. ª¥

This article during the factor analysis of standardized data processing, the of various main factor score and the mean score is zero, so 0 is a reference that composite score is greater than the company's comprehensive ability is relatively strong, and the greater the value, the stronger the strength; composite score is less than 0, the relative difference, the greater the absolute value, the strength of the weaker. And so comprehensive ability to sample a basic judgment. The view from the score, a composite score of 21 positive, 23 composite score is negative, that is, the comprehensive ability of good companies and bad companies almost each half. ª¥

(2) a single factor score analysis. ª¥

As can be seen from the individual factor scores of the comprehensive capacity of 44 real estate listed companies and sorting table, different companies in the profitable development capacity, long-term solvency, the ability of operations and cash flows, short-term solvency, risk capacity varies , decision-makers can make a different decision from the different emphases. ª¥

Combined composite score can also be found, not ability in each individual ability is strong, and vice versa; That is not a good hundred good, and a poor one hundred poor. Every company has its own advantages and shortcomings, there is no perfect. ª¥

(3) analysis of regional differences. ª¥

Involved in the analysis of 44 listed real estate companies from all regions, the combined companies the ability to score, you can analyze the regional differences. In order to test whether the differences in the ability of the regional real estate listed companies with significant this paper, the Kruskal-Wa11is H method tested, chi-square test value of 10.612, P = 0.643, comprehensive ability of each listed real estate companies in there was no significant difference. ª¥

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