Tata Steel

2013 IIM Lucknow

FM PROJECT REPORT Submitted to: Prof. Madhumita Chakraborty

Group - 12 Sahil Bansal-ABM09047 Niraj Agarwal-PGP28385 Ashutosh Tripathi-PGP28389 Prashant Kajaria-PGP28405

Contents Findings of the project ............................................................................................................................ 3 Introduction ............................................................................................................................................ 4 TATA STEEL .............................................................................................................................................. 4 SAIL.......................................................................................................................................................... 4 Bhushan Steel ......................................................................................................................................... 5 Sesa Goa Limited ..................................................................................................................................... 5 Cost of Capital ......................................................................................................................................... 6 Tax Rate................................................................................................................................................... 6 Cost of Equity .......................................................................................................................................... 6 Dividend Discount Model.................................................................................................................... 6 Earnings Capitalisation Model ............................................................................................................ 7 CAPM Model ....................................................................................................................................... 7 Market Beta ........................................................................................................................................ 8 Tata Steel ........................................................................................................................................ 8 Bhushan Steel.................................................................................................................................. 9 SesaGoa......................................................................................................................................... 10 SAIL ................................................................................................................................................ 11 Cost of Debt .......................................................................................................................................... 12 Weighted Average Cost of Capital ........................................................................................................ 13 TEST OF WEAK FORM OF EMH FOR TATA STEEL .................................................................................. 13 WEAK FORM OF EMH ................................................................................................................. 13 Autocorrelation ............................................................................................................................. 13 Method ............................................................................................................................................. 13 Observation and Analysis...................................................................................................................... 13 RUNS Method (Non Parametric Test) ............................................................................................... 13 Autocorrelation Method: .................................................................................................................. 14 Conclusion ............................................................................................................................................. 18 References: ........................................................................................................................................... 19 Appendix ............................................................................................................................................... 19 Daily Data of TATA Steel: .................................................................................................................. 20

Findings of the project 1. Kd less than Rf- In certain cases Kd is coming out to be less than Rf. The analysis suggests that these anomalies arise because of certain possible reasons like FCCBs- The cost of foreign currency convertible bonds is comparatively less than the debt rate in the domestic market. This is basically due to low rate of interest in the foreign markets like U.S., Japan etc. 2. Ke variation in EDM and DDM –There is high variation in the calculation of the cost of the equity using the earning discount model and the dividend discount model due to the assumption that the industry growth rate is applicable to all the companies. Moreover the variation in the earning rate over the years due to business cycles and the variations in the rate of dividend have further accentuated the variation. 3. Beta is calculated using monthly data- Beta calculation has been done using monthly data. While using the daily or weekly data it is the high volatility will be set off over such a long period of time making beta to be very small in value. This very small beta will not be a true reflection of the sensitivity of the stock. 4. Kd calculation is approximated- For the calculation of the cost of debt, the formula used is Interest/Total debt. This formula is approximate and not exact. Thus the cost of debt is somewhat tainted. The reason for the acceptance of such cost of debt is the unavailability of the interest rate on debt in the financial statement and the notes of accounts of the companies. 5. Weight should be Market value- The weight that should be used to calculate the cost of capital should include the market value of the equity. The calculations involve the use of both the book value as well as the market value to ascertain the anomalies. The data clearly shows that the book value is not a proper measure as it grossly underestimates the value of equity leading to much lower cost of capital.

Introduction TATA STEEL Backed by 100 glorious years of experience in steel making, Tata Steel Ltd is the world's 12th largest steel company with an annual crude steel capacity of 28 million tonnes. Established in the year 1907 as Tata Iron & Steel Company Ltd., the company is the first integrated plant in Asia and diversified steel producer with major operations in India, Europe and South East Asia. They have manufacturing units in 26 countries and a presence in 50 European and Asian markets. The company together with their subsidiaries, engages in the manufacture and sale of steel products in India and internationally.

The company is executing their plan to increase their crude steel capacity from 6.8 million tonnes per annum to 9.7 million tonnes per annum at their Jamshedpur Works by 2012-13 and it has set a target of achieving an annual production capacity of 100 million tons by 2015. The company is also has major on-going capital projects which include capacity augmentation of the Jamshedpur plant. The preliminary work on the 6 million tonne per annum capacity Greenfield steel plant at Kalinganagar, Orissa is in progress. Tata Steel is also India's second-largest and second-most profitable company in private sector with turnover of US$ 26.13 billion in FY 2011- 2012, having over 81,000 employees across five continents and is a Fortune 500 company.

SAIL Steel Authority of India Limited (SAIL) is the leading steel-making company in India. It is a fully integrated iron and steel maker, producing both basic and special steels for domestic construction, engineering, power, railway, automotive and defence industries and for sale in export markets. SAIL is also among the five Maharatnas of the country's Central Public Sector Enterprises. With a turnover of 48,681 crore (US$8.9 billion), the company is among the top five highest profit earning corporate of the country. With an annual production of 13.5 million metric tons, SAIL is the 14th largest steel producer in the world. Major plants owned by SAIL are located at Bhilai, Bokaro, Durgapur, Rourkela, Burnpur and Salem and is investing Rs 21000 crore in West Bengal, to set up a wagon factory. The company has the distinction of being India’s second largest producer of iron ore and of having the country’s second largest mines network. Currently, SAIL, is in the process of modernizing and expanding its production units, raw material resources and other facilities to maintain its dominant position in the Indian steel market. The objective is to achieve a production capacity of 26.2 MTPA of Hot Metal from the base level production of 14.6 MTPA (2006-07 – Actual).

Bhushan Steel Bhushan Steel Ltd formerly known as Bhushan Steel & Strips Ltd is a globally renowned and one of the leading players in the steel industry. Backed by more than two decades, of experience in steel making, Bhushan steel is now India’s 3rd largest Secondary Steel Producer Company with an existing steel production capacity of 2 million tonnes per annum. Bhushan Power and Steel Limited has seven plants at four locations – Chandigarh, Derabassi in Punjab, Bangihatti, near Dankuni in West Bengal, and Thelkoloi in Orissa BSL uses advanced technology and replenishes the same as and when required. This has led to the Khopoli plant has given a tremendous boost of 425000 MT per annum to BSL’s total production capacity. This led to gross sales increasing 8-fold over a period of six years. Its biggest expansion is in Orissa – it has signed an agreement with the Government of Orissa for setting up of a three million tonnes capacity steel plant at Meramandali in Dhenkanal district, and as part of its total integration of the steel value chain, Bhushan Steel is in the process of setting up a power plant and an advanced hot rolling plant on 1,618 acres (6.55 km2) at Meramandali in Dhenkanal district near Angul, at a cost of 5,200crore and its subsequent backward integration and expansion to 4 million tonnes.

Sesa Goa Limited Sesa Goa Limited is multinational iron-ore producer and exporter with operations in the states of Goa and Karnataka in India and in Liberia, West Africa. It is India's largest producer and exporter of iron ore in the private sector, with production of above 21 million tonnes of iron ore in fiscal year 2010. In 2007, it became a majority-owned subsidiary of Vedanta Resources Plc, listed on the London Stock Exchange, when Vedanta acquired 51% controlling stake from Mitsui & Co., Ltd. In June 2009, Sesa Goa Limited acquired VS Dempo & Co. Private Limited (now Sesa Resources Limited) along with its fully owned subsidiary Dempo Mining Corporation (now Sesa Mining Corporation Limited) and 50% equity in Goa Maritime Private Limited. In 2011, Sesa acquired 51% stake in Western Cluster Limited, Liberia. China is the biggest client accounting for 80% of the iron ore sales. Codli is the largest iron ore producing mine of Sesa Goa with a current production capacity of more than 7.0 mtpa. The Sonshi mine has a capacity of more than 3.0 mtpa. Approximately 65% of total production of metallurgical coke is consumed by Sesa group, for its pig iron production. The remainder is sold to customers located in India. Sesa Goa has patented a technology that provides high quality output and produces power.

Cost of Capital The cost of capital is the rate of return that capital could be expected to earn in an alternative investment of equivalent risk. It is used to evaluate new projects of a company as it is the minimum return that investors expect for providing capital to the company, thus setting a benchmark that a new project has to meet. The Cost of Capital comprises of the cost of debt and cost of equity. The overall cost of capital of a company may be calculated as the weighted average of these two costs. Tata steel’s capital structure comprises both debt and equity. Hence, WACC would be an ideal method to calculate its cost of capital. The WACC is calculated as: WACC= Kd*(1-T)*Wd+ Ke*We Where: Kd= cost of debt Ke= cost of equity Wd= weight of debt We= weight of equity T= tax rate

Tax Rate Flat tax rate for Indian companies is 30%. For Indian companies, income is taxed at a flat rate of 30%. Another way to derive the tax rate is to find out the taxes paid by the firm as a percentage of its revenue. However this method is not recommended and hence we use the statutory tax rate for WACC calculations. T = 30%

Cost of Equity The Cost of Equity may be calculated using the following methods `

Dividend Discount Model The cost of equity can be measured by the dividend discount model. Ke = (D1 / P0) + g

This model may not provide us the correct cost of equity as: 1. The dividend for all the companies has not been stable and has varied in the past few years. 2. The dividend for the companies is not expected to follow any constant growth rate in the future years as well. Company Tata Steel Bhushan Steel SesaGoa Sail

Growth Rate 0.035 0.035 0.035 0.035

Ke (DPS) 6.148162 4.665006 5.5592 5.626316

Earnings Capitalisation Model Ke = E1 / P0

Company

E1

P0

Ke(EPS)

Tata Steel Bhushan Steel SesaGoa Sail

67.07 47.7 19.24 8.25

453.1 409.44 194.25 94.05

14.80247 11.65006 9.904762 8.77193

The limitations are: The firm employs debt and the dividend pay-out is not 100 percent. The earnings are not stable, and consequently the future earnings are not equal to the current earnings. Hence, the growth rate is not zero. Secondly, we cannot be sure whether the investment opportunities available to it are expected to earn a rate of return equal to the cost of equity. Hence this method will would not give us the right model for evaluation of cost of equity.

CAPM Model Since CAPM is the superior method of determining Ke, We use the value determined by this method rather than DDM and ECM. The problem with the formulas used in DDM and ECM is that they have an underlying assumption of regular future growth which is at best an approximation. Second, errors inevitably creep into the estimate of g. To estimate the cost of equity using the CAPM method, we need the following variables 1. Risk Free Rate: In 2010, the Indian government did not have a bond whose maturity date was 2030. Hence we take the risk free rate as the current yield on the 30-year Indian Government bonds which is 7.8%. This is chosen because this is the closest approximation of Tata Steel’s valuation period which is we have taken as 20 years. Rf = 7.8%

2. Market Return Rate: We consider the market return rate as the average return on the BSE Sensex over the last 10 years is 2002 to 2012 (optimum time period). Rm=12%

Market Beta Beta analyzes the market volatility of Tata Steel’s stocks. To have a correct measurement of Beta, we take the market returns and Tata steel returns for last six years.

Beta is calculated using the following formula: Beta= covariance (Market Returns, Firm Returns)/Variance (Market returns) Tata Steel

Tata Steel 0.3

y = 1.7021x - 0.006

0.2 0.1

-0.15

-0.1

0 -0.05 0 -0.1 -0.2 -0.3 -0.4

Bhushan Steel

tata steel 0.05

0.1

0.15

Linear (tata steel)

Bhushan Steel 1 y = 1.4407x + 0.0159

0.8 0.6 0.4

Bhushan Steel

0.2

Linear (Bhushan Steel)

0 -0.2

-0.1

0

0.1

0.2

-0.2 -0.4

SesaGoa

`

Sesagoa

-0.15

SAIL

-0.1

0.35 0.3 0.25 0.2 0.15 0.1 0.05 0 -0.05-0.05 0 -0.1 -0.15 -0.2

y = 1.3735x + 0.0072

Sesagoa Linear (Sesagoa) 0.05

0.1

0.15

SAIL 0.25 y = 1.3985x - 0.0033

0.2 0.15 0.1

SAIL

0.05 -0.15

-0.1

0 -0.05-0.05 0

Linear (SAIL) 0.05

0.1

0.15

Linear (SAIL)

-0.1 -0.15 -0.2 -0.25

We calculate the Cost of Equity as Ke=Rf+ β*(Rm-Rf)

Company Tata Steel Bhushan Steel SesaGoa Sail

Rm 12% 12% 12% 12%

Rf 7.8% 7.8% 7.8% 7.8%

β

Ke

1.702 1.44 1.373 1.398

0.14948 0.13848 0.13567 0.13672

Cost of Debt Company Tata Steel Bhushan Steel SesaGoa Sail

Total Debt 59796.67 21350.97 3741.34 17360.59

Interest 1925.42 1046.27 420 983.99

Kd 0.032199452 0.049003394 0.06789 0.056679525

Weighted Average Cost of Capital Tata Steel Bhusan Steel Sesagoa Sail

CAPM BV 0.081300213 0.07242991 0.12222066 0.112607202

CAPM MV 0.084648823 0.076925351 0.133758415 0.109658631

EDM 0.069151676 0.039444663 0.085179677 0.064337419

DDM 0.028169019 0.015394001 0.046790545 0.040397932

TEST OF WEAK FORM OF EMH FOR TATA STEEL WEAK FORM OF EMH The weak form of the EMH says that past prices, volume, and other market statistics provide noinformation that can be used to predict future prices.If stock price changes are random, then past prices cannot be used to forecast future prices.Price changes should be random because it is information that drives these changes, andinformation arrives randomly.This form of the EMH, if correct, repudiates technical analysis. Autocorrelation

The Serial Correlation Coefficient measures the relationship between the values of a random variable at time t and its value in the previous period. Autocorrelations are reliable measures for testing of dependence/independence of random variables in a series. If no autocorrelations arefound in a series then the series is considered random. The study used return to investors in BSESensex derived from the log transformation of the price ratio to convert the data intocontinuously compounded rates than using discrete compounding. It is given by R= ln(Pt/Pt-1)The closing rates of the past 1250 trading days are selected for the study.

Method If the random walk theorem to prevail, the stock prices should vary around a constant mean with constant variance and should be probabilistically independent. The independence can be tested using Auto Correlation Function which shows the pattern of auto correlations present in the time series as well as the extent to which current values of the series are related to various lags of the past data. In an efficient market, the testing hypothesis is defined as H0 = Auto correlation is Zero against an alternate hypothesis of H1= Auto correlation is non- zero

Observation and Analysis RUNS Method (Non Parametric Test) The run test, also called Geary test, is a non-parametric test whereby the number of sequences of

consecutive positive and negative returns is tabulated and compared against its sampling distribution under the random walk hypothesis. A run is defined as the repeated occurrence of the same value or category of a variable. It is indexed by two parameters, which are the type of the run and the length. Stock price runs can be positive, negative, or have no change. The length is how often a run type occurs in succession. In an efficient market, the testing hypothesis is defined as: H0 = Auto correlation is Zero against an alternate hypothesis of H1= Auto correlation is non- zero.

Runs Test tatasteel a

Test Value

bhusansteel

sesagoa

sail

nifty

.0015

.0223

.0133

.0028

.0044

Cases < Test Value

41

41

42

38

38

Cases >= Test Value

38

38

37

41

41

Total Cases

79

79

79

79

79

Number of Runs

44

39

42

40

50

Z

.807

-.327

.377

-.100

2.168

Asymp. Sig. (2-tailed)

.420

.743

.706

.920

.030

Here it is seen that at 95% Confidence Interval, the observed Z value lies in the range of (1.65, 1.65). Hence, we do not reject H0. This means that all the companies are efficient in the weak form of market. This implies that the past or historical data doesn’t aid in predicting the future or current market outcome.

Autocorrelation Method: Tata Steel:

Box-Ljung Statistic Autocorrel Std. Errora ation

Lag

Value

Sig.b

df

Partial Autocorrel Std. Error ation

1

0.119

0.11

1.156

1

0.282

0.119

0.113

2

0.043

0.11

1.313

2

0.519

0.03

0.113

3

0.108

0.109

2.295

3

0.514

0.101

0.113

4

0.107

0.108

3.268

4

0.514

0.084

0.113

5

-0.029

0.108

3.34

5

0.648

-0.058

0.113

6

-0.247

0.107

8.683

6

0.192

-0.262

0.113

7

-0.041

0.106

8.835

7

0.265

-0.008

0.113

8

-0.115

0.105

10.035

8

0.263

-0.102

0.113

9

-0.064

0.105

10.408

9

0.318

0.023

0.113

10

-0.056

0.104

10.694

10

0.382

0.014

0.113

11

-0.191

0.103

14.132

11

0.226

-0.191

0.113

12

0.005

0.102

14.134

12

0.292

0.003

0.113

13

-0.13

0.102

15.769

13

0.262

-0.149

0.113

14

-0.154

0.101

18.113

14

0.202

-0.168

0.113

15

0.044

0.1

18.306

15

0.247

0.121

0.113

16

-0.012

0.099

18.321

16

0.305

-0.037

0.113

From the above table we that the autocorrelation values are almost 0 and the consistency is maintained in the lags. Additionally, the test results lead us to accept the null hypothesis H0 that autocorrelation doesn’t exist. This further implies that the market is efficient in the weak form.

Bhushan Steel:

Lag

Autocorrelation

Std. a Error

Box-Ljung Statistic Value

df

Sig.

b

Partial Autocorrelation

Std. Error

1

0.149

0.11

1.813

1

0.178

0.149

0.113

2

0.051

0.11

2.025

2

0.363

0.029

0.113

3

0.036

0.109

2.134

3

0.545

0.025

0.113

4

-0.225

0.108

6.46

4

0.167

-0.241

0.113

5

-0.037

0.108

6.581

5

0.254

0.03

0.113

6

0.029

0.107

6.656

6

0.354

0.052

0.113

7

0.003

0.106

6.657

7

0.465

0.014

0.113

8

0.022

0.105

6.701

8

0.569

-0.042

0.113

9

-0.069

0.105

7.138

9

0.623

-0.082

0.113

10

-0.03

0.104

7.219

10

0.705

0.014

0.113

11

-0.131

0.103

8.835

11

0.637

-0.125

0.113

12

-0.07

0.102

9.306

12

0.677

-0.03

0.113

13

0.096

0.102

10.191

13

0.678

0.096

0.113

14

-0.096

0.101

11.103

14

0.678

-0.125

0.113

15

-0.061

0.1

11.473

15

0.718

-0.097

0.113

16

0.137

0.099

13.371

16

0.645

0.156

0.113

From the above table we that the autocorrelation values are almost 0 and the consistency is maintained in the lags. Moreover, the test results lead us to accept the null hypothesis H0 that autocorrelation doesn’t exist. This further implies that the market is efficient in the weak form. Hence, the past records are futile to predict the current prices.

Sesagoa: Box-Ljung Statistic Lag

Autocorrelation

Std. a Error

Value

df

Sig.

b

Partial Autocorrelation

Std. Error

1

-0.01

0.11

0.008

1

0.927

-0.01

0.113

2

-0.103

0.11

0.889

2

0.641

-0.103

0.113

3

0.015

0.109

0.908

3

0.824

0.013

0.113

4

0.204

0.108

4.448

4

0.349

0.196

0.113

5

-0.106

0.108

5.414

5

0.367

-0.103

0.113

6

-0.021

0.107

5.452

6

0.487

0.016

0.113

7

-0.042

0.106

5.609

7

0.586

-0.069

0.113

8

-0.024

0.105

5.662

8

0.685

-0.065

0.113

9

0.071

0.105

6.119

9

0.728

0.111

0.113

10

0.148

0.104

8.137

10

0.615

0.14

0.113

11

0.002

0.103

8.137

11

0.701

0.043

0.113

12

-0.214

0.102

12.525

12

0.404

-0.207

0.113

13

-0.028

0.102

12.598

13

0.479

-0.092

0.113

14

-0.076

0.101

13.166

14

0.514

-0.175

0.113

15

0.013

0.1

13.184

15

0.588

0.045

0.113

16

-0.023

0.099

13.237

16

0.655

0.095

0.113

From the above table we that the autocorrelation values are almost 0 and the consistency is maintained in the lags. Moreover, the test results lead us to accept the null hypothesis H0 that autocorrelation doesn’t exist. This further implies that the market is efficient in the weak form. Hence, the past records are futile to predict the current prices.

SAIL: Box-Ljung Statistic Lag

Autocorrelation

Std. a Error

Value

df

Sig.

b

Partial Autocorrelation

Std. Error

1

0.071

0.11

0.415

1

0.52

0.071

0.113

2

0.122

0.11

1.643

2

0.44

0.117

0.113

3

0.02

0.109

1.677

3

0.642

0.004

0.113

4

0.116

0.108

2.828

4

0.587

0.102

0.113

5

-0.094

0.108

3.586

5

0.61

-0.113

0.113

6

-0.025

0.107

3.642

6

0.725

-0.037

0.113

7

0.056

0.106

3.923

7

0.789

0.084

0.113

8

-0.006

0.105

3.926

8

0.864

-0.019

0.113

9

0.039

0.105

4.062

9

0.907

0.051

0.113

10

0.081

0.104

4.665

10

0.912

0.076

0.113

11

-0.118

0.103

5.969

11

0.875

-0.172

0.113

12

-0.15

0.102

8.106

12

0.777

-0.142

0.113

13

-0.171

0.102

10.942

13

0.616

-0.141

0.113

14

-0.315

0.101

20.703

14

0.109

-0.316

0.113

15

-0.006

0.1

20.706

15

0.146

0.133

0.113

16

-0.073

0.099

21.246

16

0.169

-0.001

0.113

From the above table we that the autocorrelation values are almost 0 and the consistency is maintained in the lags. Moreover, the test results lead us to accept the null hypothesis H0 that autocorrelation doesn’t exist. This further implies that the market is efficient in the weak form. Hence, the past records are futile to predict the current prices.

Conclusion We have calculated cost of capital of four steel organisations viz. Tata Steel, Sail India, Bhushan Steel and SesaGoa of Vedanta. For cost of equity we have used DDM model, EDM model and CAPM model. Using EDM and DDM model the cost of equity is coming lesser than risk free interest rate

which is absurd so we have rejected these results and we accepted the results of CAPM model. For cost of debt we have used total debt value and interest. After getting cost of equity and cost of debt, we have calculated cost of capital using WACC in which we have used market value of equity. In efficiency test, auto correlation is coming to be zero so historical data doesn’t help in predicting the current prices so there is no scope of making excess money thus all the four organisations are efficient in weak form of market. Additionally this is also substantiated by runs test that null hypothesis is correct that autocorrelation is zero.

References: 1) 2) 3) 4) 5) 6) 7) 8)

Nseindia.com Tatasteel.com Bhushansteel.com Sesagoa.com Sail.co.in Capitaline.com Google.com/finance Brealey, Myers, Allen, Mohanty (2007), Principles of Corporate Finance, McGrawHill Publications

Appendix Tata Steel

BOOK VALUE MARKET VALUE TOTAL DEBT Beta Rm Rf Risk premium Ke interest Kd EPS DPS g MP per share Ke (EPS) Ke(DPS)

31-03-2013 43061

Bhusan Steel 31-03-2013 7572.72

Sesagoa 31-03-2013 15118.21

Sail 31-032013 40273.16

45685.62 8825.27 16882.27 38847.63 59796.67 21350.97 3741.34 17360.59 1.702 1.44 1.373 1.398 0.12 0.12 0.12 0.12 0.078 0.078 0.078 0.078 0.042 0.042 0.042 0.042 0.149484 0.13848 0.135666 0.136716 1925.42 1046.27 420 983.99 0.03219945 0.049003394 0.06789 0.0566795 67.07 47.7 19.24 8.25 11.998823 4.77 3.999996 1.9998 0.035 0.035 0.035 0.035 453.1 409.44 194.25 94.05 14.8024719 11.65005862 9.904761905 8.7719298 6.14816222 4.665005862 5.5592 5.6263158

CAPM BV CAPM MV EDM DDM

0.08130021 0.07242991 0.12222066 0.1126072 0.08464882 0.076925351 0.133758415 0.1096586 0.06915168 0.039444663 0.085179677 0.0643374 0.02816902 0.015394001 0.046790545 0.0403979

Daily Data of TATA Steel: Date 01-04-2005 04-04-2005 05-04-2005 06-04-2005 07-04-2005 ………. 16-01-2006 18-01-2006 19-01-2006 23-01-2006 24-01-2006 ………. 26-10-2009 27-10-2009 28-10-2009 29-10-2009 30-10-2009 ……….

TATA STEEL 368.33 354.25 344.12 351.41 347.27

Log Returns

Return Actual

-0.016927234 -0.012599945 0.009104202 -0.005146849 -0.00543646

-0.03823 -0.0286 0.021184 -0.01178 -0.01244

320.63 316.04 324.41 321.4 328.01

-0.006262102 0.01135218 -0.004048361 0.008841212 -0.00143231

-0.01244 0.026484 -0.00928 0.020566 -0.00329

505.91 471.24 452.22 439.47 441.81

-0.030831117 -0.017892382 -0.012420532 0.002306308 0

-0.06853 -0.04036 -0.02819 0.005325 0