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\title{Financial Analysis of Cable and Wire Industry 2001-2010 (Case of Pakistan)}
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             \author[1]{Dr. Yasir  Hassan}

             \affil[1]{  Lahore Business School, the University of Lahore, Pakistan}

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\date{\small \em Received: 11 December 2011 Accepted: 10 January 2012 Published: 25 January 2012}

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\begin{abstract}
        


The purpose of this study is to analyse the financial data of cable and wire industry over the decade. In this analysis we see that the performance of cable and wire industry with the help of financial data of cable and wire industry from 2001 to 2010. It will do this by the dependent and independent variables like paid-up-capital, sales, profit after tax, assets, equity and number of shares. With the help of graphical representation which will make it easy for us to analyse when the industry was flourishing the most.

\end{abstract}


\keywords{financial data, flourishing, graphical representation.}

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\let\tabcellsep& 	 	 		 
\section[{INTRODUCTION}]{INTRODUCTION}\par
akistan is manufacturing good quality and reliable electronic items which meet international quality. The electronic goods manufacturing companies in Pakistan also exports the best quality electronic goods in various countries around the world. It is one of a good profit earning sector in Pakistan. Now a day there is great competition in this industry. Different companies are offering different kinds of goods which are increasing competition in this sector. There are so many kinds of electronic goods that are making a man's life easier day by day.There is also one drawback of electronic items like big machineries that it is creating unemployment all over the world because so many works are done by the machinery and the men are being unemployed. To operate the machinery we also need different kinds of wires which are also manufactured by the industry at a big scale. Different kinds of raw materials are required to make these wire sum of which are imported from different countries. The main raw materials rubber, copper, silver, aluminum etc. some different kinds of wires are stated below: 1. Cold Heading and Forging Wires. 2. Mild Steel Wire. Different wires are required for different machines. Heavy machines are operated with wires with high power wire and small machines are operated with a low power wire. Machineries are also big source of pollution. Environment is getting polluted due the use of different kinds of crude oils. Many organizations are working on it to come over the pollution created by the use of machines. 
\section[{II.}]{II.} 
\section[{LITERATURE REVIEW}]{LITERATURE REVIEW}\par
The industrial segment of the electrical industry has carved out some time-tested methods of distribution. Butthe flood of new products and the intensified price competition in many lines is threatening established marketing channels. The author discusses the challenge to the middlemen engaged in the distribution of these products. It is less than the span of two lifetimes since Michael Faraday demonstrated the principle of the electric motor. The evolution of Faraday's crude device into the 450,000 KW turbine generators being designed today typifies the growth of the electrical industry. In the United States alone the annual production of electrical goods and equipment of all types is in ex-cess of \$20 billion. The greatest growth has occurred during the last twenty years. Generating capacity in the United States is now four times as great as it was in the mid-thirties, and kilowatt-hour consumption is six times larger.EDWIN H. 
\section[{LEWIS(Cambridge:}]{LEWIS(Cambridge:}\par
The Technology Press, Massachusetts Institute of Technology, and New York, John Wiley \& Sons, Inc., 1957) \hyperref[b0]{[3]}.\par
Forthe purposes of this paper I will consider "distribution" to mean the wholesale or distributing function which is being efficiently, effectively and economically performed today by hundreds of P organizations in all phases of industry. Inasmuch as my thirty years in business have been devoted to the distribution of electrical equipment I must, therefore, narrow my talk to cover the distribution of electrical supplies and appliances. Basically, however, our business doesn't differ materially from that of other distributors. As a matter of fact, I think it can be said that it typifies better than any other our American system of distribution just as the electrical industry by and large representsa cross-section of all American industry. It is interesting in this connection to note that there is no electrical section of the War Production Board. There is a steel section, a copper section, and so on. The reason there is no electrical section is that in the electrical industry there are represented over fifty other industries from steel to lumber.(HERBERT METZ1944) \hyperref[b1]{[4]} The development of cable television has been subjected to a comprehensive and complex array of federal, state, and local regulations; and many new proposals for regulation are being discussed. This paper attempts a critique of the emerging pattern of regulation. The author analyzes the major policy choices and concludes that only limited regulation can be justified. He proposes a new federal statute that would carefully delimit the respective roles of federal, state, and municipal regulators of cable television. The government has not left development of cable television to the free market. Extensive regulation of rates, programs, ownership, and other facets of cable television service has been proposed and, in large measure, already implemented. A critique of the emerging pat-tern of regulation would seem to be timely.(Richard A. Posner 1972) \hyperref[b2]{[5]} Transitional corporations (TNCs) are producing an ever greater share of the world's output of electrical goods. They also account for a very large share of the international trade in such goods, much of which is on an inter-firm basis. A study prepared at the request of the UNCTAD Secretariat by, Richard S Newfarmer examines how the behavior of TNCs in the electrical industry affects the development and trade of developing countries. ("The International Market Power of Transnational Corporations: A Case Study of the Electrical Industry" by Richard S Newfarmer; UNCTAD/ ST/MD/13.) Excerpts from the summary and conclusions of the study are reproduced below. The general objective of this study has been to show how electrical trans-national conglomerates mobilize and use economic power in international and foreign markets and to understand its effects upon developing countries. In particular, it has focused attention on formal and informal interdependent behavior whereby concerted market tactics and uneasy oligopolistic equilibriums replace vigorous price com-petition in many markets. (Economic and Political Weekly) \hyperref[b3]{[6]} III. This line chart show us three variables. This graph show us that profit after tax has zero or less than zero mean by decline all of the years. Equity has slightly more than zero mean and total assets are low from the very beginning but suddenly decrease in year 2007 and rise in period  {\ref 2008}  
\section[{Methodology}]{Methodology} 
\section[{Conclusion}]{Conclusion}\par
Using the analysis the cable and wire industry we came up with the different conclusion and results.\par
Research study shows us the cable and wire industry has decrease. Many of the company which is working from a long time become default because of few companies in Pakistan industry making huge profits taking the opportunity of monopoly. Using the data of decade we find out cable and wire industry profit before tax and after tax has increased. Graphical representation show us how can we make more good decisions in future production.\par
There are few safety protocol involve with the wire industry which are needed to be over looked. Because of few companies in Pakistan industry there is not much of a perfect computation in current market. So that why government has to focus on wire industry because of major elercity company like WAPDA needed huge quantity of wire since the WAPDA in nationalize so wire cost them for chant. If government focused on wire and cable industry it makes them cheap wire in high quality. Than cable and wire industry will grow.\begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-2.png}
\caption{\label{fig_0}First}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{} \par 
\begin{longtable}{P{0.85\textwidth}}
-2009. PAID-UP CAPITAL (Rs. In million) Standard Deviation Mean 67.167 70.471 75.432 86.813 163.575 201.274 261.700 350.456 376.527 Profit before tax is consistent in year 2004. Years 2001 2002 2003 2004 2005 2006 2007 2008 2009 b) Hypothesis Equity is consistent in year 2008. TOTAL ASSETS(MILL) Years Standard Deviation Mean 2001 1554.664 1191.636 88.870 93.167 98.621 118.342 124.487 173.845 250.322 254.949 323.199 2002 1742.658 1395.243 2003 2177.074 1712.484 2004 2758.343 2389.045 2005 3497.809 2882.721 2006 4972.652 3943.708 2007 7131.222 5773.443 i. Sales TAXATION 6.198 2.172 .620 Coefficient of Variation 75.579 75.639 76.487 73.358 131.399 115.777 104.545 137.461 Coefficient of Variation 130.465 124.900 115.458 121.337 126.091 2.854 .014 PROFIT After TAX Years Standard Deviation Mean H 0 :?2001= ?2002= ?2003= ?2004= ?2005= PROFIT AFTER TAX -.542 .739 -.129 -.733 .476 ?2006= ?2007= ?2008= ?2009= ?2010 Coefficient of Variation 2001 114.224 16.924 H1: At least one mean is significantly different CASH DIVIDEND 93.126 58.265 .286 1.598 .134 674.921 2002 156.482 54.761 285.753 2003 134.157 73.476 182.587 2004 166.759 138.117 120.738 2005 298.528 172.765 172.795 2006 287.412 197.426 ii. Profit After Tax H o : ?2001= ?2002= ?2003= ?2004= ?2005= ?2006= ?2007= ?2008= ?2009= ?2010 applied for checking that which year's mean is significantly different from each The least significance difference test (LSD) is CODES = 5 (FILTER) -10.182 26.299 -.056 -.387 .705 3 (Constant) 673.052 5216.693 .129 .899 H1: The least significance difference test (LSD) is applied for checking that which year's mean is EQUITY (MILL) -.903 .416 -.359 -2.171 .048 145.580 2007 970.588 541.963 179.087 significantly different from each other. TOTAL ASSET (MILL) .304 .127 .416 2.390 .031 123.518 2008 1845.745 2040.762 90.444 2009 10256.642 6011.196 170.626 2010 2339.898 1986.392 117.796 TOTAL 3827.670659 2932.662895 130.5186036 2008 200.301 99.558 201.191 2009 557.506 290.062 192.202 2010 37.861 18.734 Paid up Capital (BANK) / FINANCIAL 11.470 3.513 .349 3.265 .006 CHARGES 202.100 TOTAL 292.3820596 160.3785665 182.3074405 LSD TAXATION 6.135 2.099 .613 2.923 .011 116.500 2010 113.224 134.562 84.143 TOTAL 176.664 166.036 106.4006503 Paid Up Capital was consistent in 2004. Coefficient of Variation is applied for checking the consistency level. NO. OF SHARE Years Standard Deviation Mean Coefficient of Variation 2001 6.717 8.887 75.579 2002 7.047 9.317 75.639 2003 7.543 9.862 76.487 2004 8.681 11.834 73.358 2005 16.357 12.449 131.399 2006 19.042 13.521 140.830 2007 26.170 25.032 104.545 2008 30.498 16.997 179.435 2009 37.653 32.320 116.500 2010 11.322 13.456 84.143 TOTAL 17.10307231 15.367 111.2938713 No. of share is consistent in 2004 just as Paid -up-capital. EQUITY (MILL) Years Standard Deviation Mean Coefficient of Variation 2001 521.074 150.395 346.469 2002 650.548 233.843 278.199 2003 684.637 399.364 171.432 2004 816.125 579.997 140.712 2005 1120.131 746.723 150.006 2006 1256.104 885.362 141.875 2007 2197.657 1608.891 136.595 2008 374.694 386.015 97.067 2009 2966.143 1631.642 181.789 2010 507.196 360.172 140.821 TOTAL 1109.430947 698.2404763 158.8895208 Years (I) Years(J) Mean Differences Sig. PROFIT AFTER TAX -.505 .711 -.120 -.711 .489 Profit after tax is consistent in year 2004. 2001 2009 -234.32816666666668 .032 Total assets are consistent in year 2008 same as equity. SALES (Million) Years Standard Deviation Mean Coefficient of Variation 2001 1424.215 1028.920 138.418 2002 1634.998 1263.856 129.366 2003 2094.101 1671.006 125.320 2004 2860.852 2467.958 115.920 2005 4854.023 3442.194 141.015 2006 7288.295 4983.312 146.254 2007 8557.154 6752.809 126.720 2008 2527.801 2007.524 125.916 2009 15598.602 8352.036 186.764 2010 2596.260 1963.014 132.259 TOTAL 4943.630082 3393.262941 145.6895669 Sales are consistent in year 2004. PROFIT Before TAX Years Standard Deviation Mean Coefficient of Variation 2001 156.433 36.532 428.214 2002 194.044 76.188 254.690 2003 226.938 125.832 180.350 2004 294.858 196.711 149.894 2005 451.578 273.439 165.147 2006 554.596 333.992 166.050 2007 1351.775 757.335 178.491 2008 279.885 133.088 210.300 2009 864.412 459.536 188.106 2010 41.741 22.791 183.145 TOTAL 441.6260054 241.5444775 182.8342382 2002 2009 -230.031875 CASH DIVIDEND 83.201 50.709 .256 1.641 .123 .039 ANOVA g Model Sum of Squares df Mean Square F Sig. 1 Regression 7.581E5 8 94768.711 62.562 .001 a Residual 6059.232 4 1514.808 Total 7.642E5 12 2 Regression 7.581E5 7 108303.187 88.968 .000 b Residual 6086.612 5 1217.322 Total 7.642E5 12 3 Regression 7.580E5 6 126337.515 122.582 .000 c Residual 6183.827 6 1030.638 Total 7.642E5 12 4 Regression 7.579E5 5 151578.725 168.013 .000 d Residual 6315.295 7 902.185 Total 7.642E5 12 5 Regression 7.569E5 4 189237.026 208.502 .000 e Residual 7260.815 8 907.602 Total 7.642E5 12 6 Regression 7.541E5 3 251375.599 224.395 .000 f Residual 10082.123 9 1120.236 Total 7.642E5 12 2003 2009 -224.57721428571432 .050 2004 2009 -204.8561666666667 4 (Constant) 754.171 5128.770 .147 .885 .084 2005 2009 -198.7115 .067 Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 161.733 11495.735 .014 .989 NO. OF SHARE .025 7.040 .001 .003 .997 EQUITY (MILL) -.789 .643 -.314 -1.227 .244 TOTAL ASSET (MILL) .273 .212 .374 1.289 .222 (BANK) / FINANCIAL CHARGES 11.795 6.342 .359 1.860 .088 TAXATION 6.189 3.469 .619 1.784 .100 PROFIT AFTER TAX -.541 .847 -.128 -.639 .535 CASH DIVIDEND 93.416 103.034 .287 .907 .382 CODES = 5 (FILTER) -10.194 27.583 -.056 -.370 .718 2 (Constant) 196.430 5521.657 .036 .972 EQUITY (MILL) -.790 .519 -.314 -1.521 .152 TOTAL ASSET (MILL) .274 .153 .375 1.792 .096 (BANK) / FINANCIAL CHARGES 11.778 3.711 .358 3.173 .007 EQUITY (MILL) -.973 .397 -.387 -2.449 .027 TOTAL ASSET (MILL) .322 .123 .441 2.623 .019 (BANK) / FINANCIAL CHARGES 11.412 3.454 .347 3.304 .005 TAXATION 5.156 1.558 .516 3.310 .005 CASH DIVIDEND 82.729 49.862 .254 1.659 .118 5 (Constant) 5557.157 4459.606 1.246 .231 EQUITY (MILL) -.899 .416 -.358 -2.161 .046 TOTAL ASSET (MILL) .253 .122 .346 2.080 .054 (BANK) / FINANCIAL CHARGES 9.752 3.482 .296 2.800 .013 TAXATION 7.137 1.054 .714 6.772 .000 a. Dependent Variable: SALES (MILL) Now the model can be written as: Sales = b o + b 1 (Bank) / Financial Charges +b 2 Profit After Tax + b 3 Equity +b 4 No. of Shares Backward method is used in multi linear regression for this model. Model is showing that total asset, bank charges and profit after tax are best describing the sale. ANOVA Sum of Squares df Mean Square F Sig. PAID-UP CAPITAL (Rs. In mil) Between Groups 3.949E5 9 43873.390 1.079 .393 Within Groups 2.278E6 56 40678.726 Total 2.673E6 IV.\end{longtable} \par
 
\caption{\label{tab_1}}\end{figure}
 			\footnote{Global Journal of Management and Business Research Volume XII Issue III Version I © 2012 Global Journals Inc. (US)} 			\footnote{Global Journal of Management and Business Research Volume XII Issue III Version I © 2012 Global Journals Inc. (US) 2012 March Financial Analysis of Cable and Wire Industry 2001-2010(Case of Pakistan)} 			\footnote{© 2012 Global Journals Inc. (US)} 			\footnote{MarchFinancial Analysis of Cable and Wire Industry 2001-2010(Case of Pakistan)} 		 		\backmatter  			 			 			  				\begin{bibitemlist}{1}
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\end{document}
