It For Real Estate Applications

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IT FOR REAL ESTATE APPLICATIONS

IT for Real Estate Applications

IT for Real Estate Applications

Introduction

The two interpretations have different implications, however, for the post contractual profits and stock prices of U.K Real estate customers at the turn of the last century the railroads. Edinburgh used ordinary least squares, the capital asset pricing model, and railroad stock prices to see with which interpretation returns on railroad stocks over the period the lease was in effect were consistent. Because these returns were abnormally high, Edinburgh concluded that the primary effect of the lease was the promotion of economic efficiency, not market power.

Anticipated % of sales

Financial Inputs, EURm, 31 Dec

2009

2010

2011

2012E

2013E

2014E

2015E

Sales

39,823

44,262

47,582

50,437

51,950

53,508

55,113

growth

 

11.1 %

7.5 %

6.0 %

3.0 %

3.0 %

3.0 %

 

 

 

 

 

 

 

 

EBITDA

6,039

7,332

8,327

9,079

9,351

9,631

9,920

margin

15.2 %

16.6 %

17.5 %

18.0 %

18.0 %

18.0 %

18.0 %

 

 

 

 

 

 

 

 

EBIT / Operating Profit

5,020

6,339

7,185

7,868

8,104

8,347

8,598

margin

12.6 %

14.3 %

15.1 %

15.6 %

15.6 %

15.6 %

15.6 %

 

 

 

 

 

 

 

 

Depreciation & Amortisation

1,019

993

1,142

1,210

1,247

1,284

1,323

% of sales

2.6 %

2.2 %

2.4 %

2.4 %

2.4 %

2.4 %

2.4 %

 

 

 

 

 

 

 

 

Capital expenditure

(1,258)

(1,701)

(1,903)

(2,017)

(2,078)

(2,140)

(2,205)

% of sales

- 3.2 %

- 3.8 %

- 4.0 %

- 4.0 %

- 4.0 %

- 4.0 %

- 4.0 %

 

 

 

 

 

 

 

 

Working Capital

 

 

 

 

 

 

 

Current assets

 

 

 

 

 

 

 

- Inventories

3,578

4,309

 

 

 

 

 

- Trade and other receivables

3,429

4,135

 

 

 

 

 

- Current Tax Assets

173

298

 

 

 

 

 

- Non- current assets held for sale

17

876

 

 

 

 

 

Current liabilities

 

 

 

 

 

 

 

- Trade payable and other liabilities

(8,413)

(10,226)

 

 

 

 

 

- Provisions

(420)

(408)

 

 

 

 

 

- Current tax liabilities

(487)

(639)

 

 

 

 

 

- Others

0

(57)

 

 

 

 

 

Net Working Capital

(2,123)

(1,712)

 

 

 

 

 

 

 

 

 

 

 

 

 

Change in Working Capital

 

411

476

504

519

535

551

% sales

 

0.9 %

1.0 %

1.0 %

1.0 %

1.0 %

1.0 %



Net present value

If I paid £40m for a business that was expected to generate the cash flow stream below, and my cost of capital

was 14 %, what would I expect the NPV of the investment to be?

Cost of funds

14 %

Year

0

1

2

3

Future value

- 40

20

26

34

Discount factor

1.00

0.88

0.77

0.67

Present value

- 40.00

17.54

20.01

22.95

Answer: net present value =

20.50

Check: present value of cash flows

60.50

Formula for NPV

Price paid

- 40.00

Price paid

Answer: net present value of investment =

20.50

NPV

IRR

What would my IRR on the investment be (= discount rate where NPV = zero)?

Answer: IRR (= discount rate) =

40 %

Iterate and change cost of funds until NPV = zero

Year

0

1

2

3

Future value

- 40

20

26

34

Discount factor = 1/(1+interest rate)^year

1.00

0.71

0.51

0.37

Present value

- 40.00

14.30

13.29

12.42

Net present value =

0.00

Note, Excel formula check:

40 %

Formula for IRR

Question 02

The aim of this section is to show how geographical representation of existing data can help to interpret trends in wine consumption. The maps simply portray the distribution of existing data. However, other areas of epidemiology have shown the dangers in interpreting what seem to be straightforward data. There are issues to do with level of aggregation and reference populations for rate calculation. These issues are explored in data sets. The data set from London, England show new cases of wine consumption.

There are several types of geographical study:-

•descriptive - to describe the geographical distribution of disease

•ecological (or “geographical correlation”) - to describe the geographical distribution and relationship of disease with exposure

•cluster/ investigative - to study clusters or clustering (disease excess with or without an identifiable source); and to investigate potential point sources (e.g industrial pollution and chemical accidents)

•?migrant (or “environmental genetics”) - to study changes in disease patterns among people that move from high or low risk to another region with low or high risk respectively.

Problems with the data in terms both of the population counts (denominator) and accuracy ...
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