What do you mean by factor analysis and trend analysis in financial statement analysis? It is best to have an example analysis!

Factor analysis method (factor analysis method)

catalogue

1 What is factor analysis?

2-factor analysis method

3 the general procedure of using factor analysis method

4. Problems that should be paid attention to when using factor analysis method.

What is factor analysis?

Factor analysis, also known as sequence substitution method, is the application and development of the principle of exponential method in economic analysis. According to the principle of index method, when analyzing the changes of things affected by many factors, other factors are fixed in order to observe the influence of one factor change, so that they can be analyzed item by item and replaced item by item, so it is called factor analysis method or sequence substitution method.

The method of factor analysis:

chain substitution

It decomposes the analysis index into measurable factors, and replaces the reference value (usually the standard value or the planned value) with the comparison value (usually the actual value) of each factor in turn according to the dependency relationship between each factor, so as to measure the influence of each factor on the analysis index.

For example, the relationship between a financial indicator and related factors consists of the following formulas: actual indicator: PO = × BO× CO; Standard index: PS = as× bs× cs. The total difference between actual and standard is PO-PS, and the total difference of P G is affected by three factors, A, B and C, and their respective influence degrees can be calculated by the following formulas:

The influence of a factor change: (ao-as) × bs× cs;

The influence of the change of factor B; ao×(Bo-Bs)×Cs；

The influence of the change of factor c: Ao×Bo×(Co-Cs).

Finally, the sum of the respective influence numbers of the above three factors should be equal to the total difference Po-Ps.

Difference analysis method

It is a simplified form of serial substitution method, which uses the difference between the comparison value of each factor and the reference value to calculate the influence of each factor on the analysis index.

For example, the total profit of an enterprise is affected by three factors, and its expression is: total profit = operating profit+investment profit and loss+net non-operating income and expenditure. When analyzing the changes of profits last year and this year, we can calculate the changes of total profits this year and the different changes of three influencing factors compared with last year, so that we can know which of the three factors is mainly responsible for the increase or decrease of profits this year.

Exponential decomposition method

For example, the profit rate of assets can be decomposed into the product of asset turnover rate and sales profit rate.

Fixed base substitution method

Replace the standard value with the analysis value respectively, and determine the influence of various factors on financial indicators, such as the difference analysis of standard cost.

General procedure using factor analysis method

1, to determine the indicators to be analyzed;

2. Determine the factors affecting the index and their relationship with the index;

3. Calculate and determine the influence degree and quantity of each factor.

Problems needing attention in using factor analysis method

1, pay attention to the correlation of factorization;

2. The order of factor substitution;

3. Seriality of sequential substitution, that is, when calculating each factor change, it is based on the previous calculation, and the influence result of factor change is determined through serial comparison;

4. Assumption of calculation results, the influence number of various factors calculated by serial substitution method will be different due to the different order of substitution calculation, that is, the calculation result is only the result under a certain assumption. Therefore, when applying this method, financial analysts should pay attention to make this assumption logical and have practical economic significance, so that the assumption of calculation results will not hinder the effectiveness of analysis.

It refers to an analytical method to determine the influencing factors, measure their influence degree and find out the reasons for the change of indicators. Trend analysis is also called comparative analysis and horizontal analysis. It is an analytical method to reveal the financial status, operating conditions and cash flow trends of enterprises by comparing the same indicators or ratios in two or more consecutive periods on a regular and monthly basis. When trend analysis is adopted, comparative accounting statements are usually prepared. [Edit this paragraph] The purpose of the application is to determine the main reasons for the changes in the company's financial status and operating results;

Judge whether the company's financial situation and the development trend of operating results are beneficial to investors;

Forecast the future development trend of the company. This analysis method belongs to a dynamic analysis, based on difference analysis and ratio analysis, which can effectively make up for its shortcomings. [Edit this paragraph] Comparison of important financial indicators in application mode

It compares the same indicators or ratios in financial reports in different periods, directly observes their changes and ranges, inspects their development trends and predicts their development prospects. This method is statistically called dynamic analysis. There are two ways to do this.

1, fixed base dynamic ratio: that is, the value of a certain period is taken as the index value of fixed base period and compared with other periods. The calculation formula is: fixed base dynamic ratio = analysis period value ÷ fixed base period value. For example, taking 2000 as a fixed base period, the profit growth rates of 200 1 and 2002 are analyzed. Suppose that the net profit of an enterprise in 2000 was 6,543,800 yuan, in 2006 it was 6,543,800 yuan, and in 2002 it was 6,543,800 yuan. Then:

Dynamic proportion of fixed base of 200 1 year =120 ÷100 =120%.

Dynamic proportion of fixed base in 2002 =150 ÷100 =150%.

2. Ring-on-ring dynamic ratio: it is a dynamic ratio calculated based on the previous period value of each analysis period, and its calculation formula is: ring-on-ring dynamic ratio = analysis period value ÷ previous period value. Or take the above data as an example, then:

200 1 year-on-year dynamic ratio =120÷100 =120%

2002 month-on-month ratio =150 ÷120 =125%.

Comparison of two kinds of accounting statements

Comparison of accounting statements is a method of juxtaposing the amounts of several consecutive accounting statements and comparing the amounts and ranges of the same indicators, so as to judge the financial situation and the development and changes of operating results of enterprises. When comparing and analyzing with this method, it is best to calculate both the absolute value and the relative value of the increase and decrease of related indicators. This can effectively avoid the one-sidedness of the analysis results.

For example, the profit statement of an enterprise reflects that the net profit in 2000 was 500,000 yuan, in 2006, 5438+0 was 6.5438+0 million yuan, and in 2002, it was 6.5438+0.6 million yuan.

Through absolute value analysis: compared with 2000, the net profit of 200 1 increased by 100-50=50 (ten thousand yuan); In 2002, compared with 200 1, the net profit increased by 160- 100=60 (ten thousand yuan), indicating that the benefit growth in 2002 was better than 200 1.

Through the analysis of relative value, the net profit growth rate of 200 1 compared with 2000 is: (100-50) ÷ 50×100% =100%; Compared with 200 1, the growth rate of net profit in 2002 is: (160-100) ÷100×100% = 60%. It shows that the benefit growth in 2002 is obviously less than 200 1.

3. Comparison of project composition of accounting statements

This method is developed on the basis of comparison of accounting statements. It is based on an overall indicator in accounting statements as 100%, and calculates the percentage of each component item in the overall indicator, so as to compare the percentage increase and decrease of each item and judge the changing trend of related financial activities. This method can more accurately analyze the development trend of enterprise financial activities than the first two methods. It can be used not only for vertical comparison of the financial situation of the same enterprise in different periods, but also for horizontal comparison between different enterprises. At the same time, this method can also eliminate the influence of business scale differences in different periods (different enterprises), which is conducive to analyzing the consumption and profitability of enterprises, but the calculation is more complicated.

When using the trend analysis method, we must pay attention to the following problems: 1, the indicators used for comparison in different periods must be consistent in calculation caliber; 2. The influence of accidental projects must be eliminated, so that the analysis data can reflect the normal operating conditions; 3. Using the principle of exception, pay attention to an index with significant changes and study its reasons, so as to take countermeasures and avoid disadvantages. [Edit this paragraph] The overall classification trend analysis method is generally divided into four categories: (1) longitudinal analysis method; (2) transverse analysis method; (3) standard analysis method; (4) Comprehensive analysis method. In addition, the trend analysis method also has a trend prediction analysis.

Trend prediction analysis uses regression analysis, exponential smoothing and other methods to analyze and predict the financial statement data, analyze its development trend and predict the possible development results. The following briefly introduces how to use the trend linear equation for trend prediction analysis, and the other four methods are introduced later.

Trend linear equation is a widely used method to predict sales and income when analyzing trends. The formula is: y = a+bx.

Where: a and b are constants, x represents the value of the periodic coefficient, x is determined by the distribution, and ∑x=0. In order to make σx = 0. When the number of periods is even or odd, the distribution of values is slightly different. [Edit this paragraph] TrendAnalysis was originally put forward by Trigg, and the error of judgment method was monitored through the trajectory signal of Trigg. This kind of trajectory signal can reflect the interaction between system error and random error, but it cannot be monitored separately. After that, Cembrowski and others separately processed the two estimated values in the ballistic signal, so that they could monitor the systematic error and random error respectively, namely the mean rule of TRIGG, an index system of "precision trend" (mean value), and the variance chi-square rule of TRIGG, an index system of "precision trend" (standard deviation). On the surface, trend analysis is similar to the traditional Shewhart control chart, that is, the average value is used to monitor the system error, while the range or standard deviation is used to monitor the random error. In the trend analysis, the estimated values of mean (precision trend) and standard deviation (precision trend) are obtained by exponential smoothing method. Exponential smoothing needs to introduce weights to complete the calculation, and in each determination of a certain sequence, the weight of the last determination is more important than the previous one, thus increasing the response to the newly started trend and playing the role of "early warning" and "anti-lag".

(a) the trajectory signal of trigg

Trajectory signal of Trigg = smooth prediction error (SFE)/ mean absolute deviation (MAD). The basic mathematical relationship related to it is as follows.

The average estimated value obtained by exponential smoothing is called SM-mean. The sm- mean of each measured value in the measurement sequence is calculated by formula 9- 1: sm- mean = a× (new main control measured value) +( 1-a )× (former sm- mean) (9- 1), where a is the smoothing coefficient, and a =/.

According to the above calculation formula, the last quality control measurement value is weighted by a, the penultimate quality control measurement value is weighted by a (1-a), and the penultimate quality control measurement value is weighted by a.. A (1-A) 2 is weighted, and so on. If a is 0.2, the weight of the latest control measurement is 0.2, and in reverse order, the weight of the previous control measurement is 0. 16, 0. 128, and so on.

For the standard deviation, a similar calculation can be made, but it is more complicated because the difference between the new control measured value and the average estimated value must be calculated first, and this difference is called the prediction error.

Prediction error = new control measured value-previous SM- average value (9-2)

Smooth prediction error (SFE) = a× (new prediction error) ten (1-a )× (previous smooth prediction error) (9-3)

The prediction error is estimated by exponential smoothing, which is called mean absolute deviation (MAD).

Mad = a× (new prediction error) —( 1—a)× (pre-MAD) (9—4)

Final listing:

Trajectory signal = smooth prediction error (SFE)/ mean absolute deviation (MAD) (9-5)

Generally, 95% and 99% confidence levels of trajectory signals are defined as the boundary between warning and out of control (see Table 9-3).

Table 9-3 Control Limit of Trajectory Signal under Different N

N warning boundary beyond control boundary

5 0.33 0.7 1 0.82

10 0.20 0.6 1 0.80

15 0. 10 0.4 1 0.54

20 0. 10 0.4 1 0.54

(2) Trigg average rule (PFR = 0.0 1. Pfr=0.002)

This rule is mainly used to monitor system errors, which is the index system of "accuracy trend analysis" in trend analysis. When applying this rule, first calculate the "pre-sm-mean" of the smooth mean, which is actually the mean (t-mean) of the measured values of quality control products. If the standard deviation of the initial quality control material is Ts, the average value of the quality control material is used to test the estimated value of the smooth average value and the z value is used to test:

Z = N(sm—-mean-t-mean)/ts (9-6)

Among them, z is equivalent to the number of standard deviations, which is related to the "significance level" of statistical test. The control limit of the smooth average (SM-N lean) in the Trigg average rule can be calculated according to Formula 9-6 (see Table 9-4) by determining the Z values of different levels through Pfr.

Table 9-4 Control Limit of Trigg Average Rule

Control limit

Pfr=0.0 1 Pfr=0.002

5 0.33 1.25 Ts 1.38 Ts

10 0.20 0.82 0.98

15 0. 10 0.67 0.79

20 0. 10 0.58 0.69

(3) Trigg variance card method (Pfr = 0.05；; Pfr=0.0 1，Pfr=0.002)

This rule is mainly used to monitor random errors, that is, the indicator system of "precision trend analysis" in trend analysis; The most critical statistical data is the smooth standard deviation SM-S, and the mathematical expression of SM-S is:

Smooth standard deviation (9-7)

Where a and MAD are as defined above. The specific method is to use chi-square (X2) statistical test to test the significant change of the estimated value of the smooth standard deviation (SM-S), that is, to compare the "true" variance (T2s) with the squared smooth standard deviation (SM-S):

X2=(sm2s/T2s)×(N- 1) (9—8)

The critical chi-square values (X2) of different levels are determined by Pfr, and the control limit of the Trigg variance chi-square rule is calculated according to Formula 9-8. See Table 9-5.

Table 9-5 Control Limit of Trigg Variance Chi-Square Rule

Control limit

Pfr = 0.05 Pfr = 0.0 1 Pfr = 0.002

5 0.33 1.54 1.82 2. 15

10 0.20 1.37 1.55 1.75

15 0. 10 1.30 1.44 1.6 1

20 0. 10 1.26 1.38 1.52