FINANCIAL MODELING

Financial Modeling

Financial Modeling

Financial Modelling

Financial modeling is the task of building an abstract representation (a model) of a financial decision making situation.[1] This is a mathematical modeldesigned to represent (a simplified version of) the performance of a financial asset or a portfolio, of a business, a project, or any other investment. Financial modeling is a general term that means different things to different users; the reference usually relates either to accounting and corporate finance applications, or to quantitative finance applications. While there has been some debate in the industry as to the nature of financial modeling - whether it is a tradecraft, such as welding, or a science - the task of financial modeling has been gaining acceptance and rigor over the years.

Requirement 1 and 2:

Descriptive Statistics

FTSE

Mean

3.814346848

Standard Error

0.00655003

Median

3.727205043

Standard Deviation

0.068069905

Sample Variance

0.004633512

Kurtosis

-0.769484796

Skewness

-0.439612093

Range

0.275120856

Minimum

3.552351808

Maximum

3.827472664

Sum

401.1494595

Count

108

The above table of descriptive statistics is showing that mean price of FTSE index is 3.81 with the standard deviation of 0.068. Moreover, the variance of the price is 0.004 which shows that there is little variation in the stock price of FTSE index.

Descriptive Statistics

BP

Mean

2.52557468

Standard Error

0.0111836

Median

2.563626954

Mode

2.62838893

Standard Deviation

0.116223382

Sample Variance

0.013507874

Kurtosis

0.787574519

Skewness

-1.140517619

Range

0.522552554

Minimum

2.165867268

Maximum

2.688419822

Sum

272.7620654

Count

108

The descriptive statistics of BP is showing that mean stock price of BP is 2.52 with the standard deviation of 0.116. Furthermore, the variance of the stock price is 0.013 which shows that there is high variation in the stock price of BP.

Descriptive Statistics

LAND SEC R.E.I.T. Group

Mean

2.769752847

Standard Error

0.006945877

Median

2.755111596

Mode

2.737192643

Standard Deviation

0.07218367

Sample Variance

0.005210482

Kurtosis

-0.3522154

Skewness

0.043091767

Range

0.349561079

Minimum

2.578065884

Maximum

2.927626962

Sum

299.1333074

Count

108

The above table of LAND SEC R.E.I.T.is reflecting that mean stock price of the company is 2.76 which is high than the BP with the standard deviation of 0.072. Furthermore, the variance of the stock price is 0.005 which reflects that there is not too much variation in the stock price of LAND SEC R.E.I.T.

Requirement 3:

Return of BP = 1.025930193 + -4.414487679 (Rf) + e

The above equation is showing the regression equation of the BP; furthermore, it can be observed that there is a negative relationship of beta value of the risk free return of one month treasury bill with the return of BP.

Return of LAND SEC R.E.I.T.= 0.996296358 + 3.650151964 (Rf) + e

The above regression model for LAND SEC R.E.I.T is showing that there is a positive relationship of risk free return of one month Treasury bill with the return of British Sky Broad casting Group. This shows that CAPM for the LAND SEC R.E.I.T will be beneficial for the stock holders as the beta value of LAND SEC R.E.I.T is positive in contrast to BP whose beta value is negative.

Effectiveness of the Capital Asset Pricing Model

Numerous studies have examined the effectiveness of the Capital Asset Pricing Model (CAPM) and most have found that for emerging and developing country markets this is subject to considerable ambiguity. More recently, additional factors have been proposed to provide a more reliable explanation of the cross section of average returns. These include firm size, the book to market equity ratio, the price earnings ratio, the cash flow to price ratio and the performance of the firm in terms of sales growth (see Shum and Tang (2005) for a full review). A major innovation to asset pricing was proposed by Fama and French (1993) ...