Submitted By redronin

Words 12428

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Words 12428

Pages 50

the Price of Alcan Stock

[pic]

Jason Scott

May 1, 2006

Introduction

In this project, we have developed a model using stepwise regression to predict the price of Alcan’s stock, based on the impact of eight independent variables on the price of Alcan’s stock. The company’s stock is listed on the New York Stock Exchange (NYSE) under the ticker symbol AL. Of the eight variables we will be looking at, we are most interested in the impact that the price of aluminum has on Alcan’s stock. Alcan is the second largest producer of aluminum in the world, and may be one of the purest plays on aluminum, given that Alcan spent the mid 1990’s spinning off all operations not involved with the production of aluminum. If any company would reflect the impact of the change in aluminum prices, it would be Alcan. Additionally, we have a keen interest in this field as both of us are employees of a company recently spun-off from Alcan. The eight independent variables that we chose for our analysis, and our reasons for choosing them, are detailed below.

Definition of Variables

Dependant Variable

Alcan (ALCAN) The dependent variable for our model is the monthly stock price of Alcan. Alcan is publicly traded on the New York Stock Exchange (NYSE) under the ticker symbol AL. The stock price is collected daily and these daily numbers are averaged together to give one monthly value. We have collected the monthly averages for the 60 month period of January 2001-December 2005. The stock prices were gathered from the internet site http://finance.yahoo.com.

Independent Variables

The eight independent variables that we selected for our model are listed below. The data on each of these independent variables were collected for the same time period and the same dates as that for the dependent variable…...

...Making sense of . . . LogNormal stock-price models in Exams MFE/3 and C/4 James W. Daniel Austin Actuarial Seminars http://www.actuarialseminars.com June 26, 2008 c Copyright 2007 by James W. Daniel; reproduction in whole or in part without the express permission of the author is forbidden. Foreword This document brieﬂy describes the ideas behind the use of LogNormal models for stock prices in some of the material for Exams MFE and C of the Society of Actuaries and Exams 3 and 4 of the Casualty Actuarial Society. Not a traditional exam-prep study manual, it concentrates on explaining key ideas so that you can then understand the details presented in the textbooks or study manuals. It can be especially useful to anyone taking Exam C/4 without having studied the material for Exam MFE/3. 2 Chapter 1 LogNormal stock-price models 1.1 Why LogNormal models? Why learn about and use LogNormal models for stock prices? I could answer “Because it’s on the exam syllabi” or “Why not?”, but that wouldn’t be helpful. Instead, I’ll take a little space to motivate this. Suppose that the price of a stock or other asset at time 0 is known to be S(0) and we want to model its future price S(10) at time 10—note that some texts use the notation S0 and S10 instead. Let’s break the time interval from 0 to 10 into 10,000 pieces of length 0.001, and let’s let Sk stand for S(0.001k), the price at time 0.001k. I know the price S0 = S(0) and want to model the price S10000 = S(10...

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..., New Heritage also had created a durable franchise for its line of heirloom dolls. However, the popularity of most doll lines waned after a few years. New Heritage’s Production Division New Heritage Doll Co. had three operating divisions: a doll and doll‐accessory production division, a retailing division, and a licensing division. New Heritage’s doll production division designed and assembled dolls, doll accessories, and children’s accessories into finished product and then packaged them for shipment. The production division generated $125 million in revenue and $7.5 million in operating profit a year.1 Seventy‐five percent of its sales were internal, to New Heritage’s retail division; 25% of its revenues were generated from private‐label goods manufactured for other firms. The dolls ranged from relatively inexpensive baby dolls ($15 to $30 retail price range) to fashion dolls modeled after movie stars that were targeted as upscale collectors’ items ($75 1 The division revenue figures include approximately $95 million of internal sales within divisions which are eliminated when considering consolidated revenue for the company. ________________________________________________________________________________________________________________ Harvard Business School Professor Timothy Luehrman and HBS MBA Heide Abelli prepared this reading to accompany...

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...ll Why Does a Stock's Price Rise or Fall? Introduction Watching the ups and downs of stock prices can be enough to make you seasick. If you own stocks, you've undoubtedly followed their prices with a feeling of either satisfaction or disappointment, depending on how your investments have done. Short-term swings can be bewildering, and sometimes it seems as though stock prices follow a logic all their own. Even so, it is possible to break down stock performance in ways that help distinguish solid growth from inflated expectations. Case Study in Rising Prices: Wal-Mart A stock's price is determined by its fundamentals (how the company has actually performed) combined with its valuation (how much the market is willing to pay for that performance and the promise of future growth). Similarly, when a stock's price goes up, that rise comes from either (1) growth in the underlying business or (2) an increase in the stock's valuation, as the market becomes more optimistic about the company's future. As an illustration of these two drivers of stock performance, consider the history of Wal-Mart WMT. In the 1970s and 1980s, Wal-Mart was the quintessential growth stock. It was profitable, with returns on equity consistently above 20%. Year after year, its revenue and earnings grew by more than 25%, often by more than 30%, as it opened new stores all over the country. As a result of this consistent growth, the annualized return of Wal-Mart's stock from 1970 to 1990...

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...Regression Analysis for Determining the Price of Alcan Stock [pic] Jason Scott May 1, 2006 Introduction In this project, we have developed a model using stepwise regression to predict the price of Alcan’s stock, based on the impact of eight independent variables on the price of Alcan’s stock. The company’s stock is listed on the New York Stock Exchange (NYSE) under the ticker symbol AL. Of the eight variables we will be looking at, we are most interested in the impact that the price of aluminum has on Alcan’s stock. Alcan is the second largest producer of aluminum in the world, and may be one of the purest plays on aluminum, given that Alcan spent the mid 1990’s spinning off all operations not involved with the production of aluminum. If any company would reflect the impact of the change in aluminum prices, it would be Alcan. Additionally, we have a keen interest in this field as both of us are employees of a company recently spun-off from Alcan. The eight independent variables that we chose for our analysis, and our reasons for choosing them, are detailed below. Definition of Variables Dependant Variable Alcan (ALCAN) The dependent variable for our model is the monthly stock price of Alcan. Alcan is publicly traded on the New York Stock Exchange (NYSE) under the ticker symbol AL. The stock price is collected daily and these daily numbers are averaged together to give one monthly value. We have collected the...

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...“IMPACT OF DIVIDEND ON STOCK PRICES” ABSTRACT The project aims to establish the impact of dividend on market price of a share. This has been done for individual companies in Steel sector. After studying the basic concepts of dividends and dividend policy I am able to get a proper perspective of the requirements of the project and also gain a better understanding of the results obtained. I have looked to find the relation between pre dividend price change and the dividend using regression analysis. Similarly, I have analyzed the relation between the post dividend price change and the dividend. It is a matter of fact that dividends are declared by a company primarily to generate capital and also at certain times to maintain the market sentiment. It is in the best interests of the company to maximize the market value of its share and companies use dividend as a tool to maintain their corporate image. However, the degree of correlation between the dividend and the market price is low which implies that several other internal and external factors affect the market value of shares. To gain a holistic picture, I also did a comparative study of two peers in a sector (steel)to better understand how the specific requirements of each sector also impact the dividend policy of a company. The conclusions derived from the analysis performed further consolidated theoretical knowledge and deviations were better understood. SYNOPSIS “Impact...

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... 547 points within 80 minutes from the start of the day's trading on December 08. But stock prices started regaining mysteriously as a section of investors took to the streets and resorted to violent protests and ended the day with 105 points lower. On December 13, Sunday, the market went through major price correction-285 points. Stock prices at the DSE more than doubled over period of last one year with the active participation of both institutional and general investors. Market insiders listed the profit taking by banks at the end of their accounting year, liquidity shortage in view of the hike in the rate of CRR (cash reserve requirement) Statutory Liquidity Ratio (SLR) and central bank's instruction relating to banks' exposure to stock market as major reasons for the ongoing erosion in stock prices. Akter H Sannamat, Managing Director of the Prime Finance and Investment Ltd said that the regulator should investigate whether vested quarters were involved behind the unusual market fall. "The enhanced CRR has created a liquidity crunch in the market and forced some banks to sell their stocks instead of buying to meet the reserve requirement, said Abu Ahmed, who teaches Economics at Dhaka University. The Bangladesh Bank raised the CRR for commercial banks by 50 basis points to six percent, sending financial institutions scrambling for funds. However, DSE president Shakil Rizvi termed the ongoing stock price fall as `natural correction'. He said although SEC......

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...Q1: All the regressions were performed. Output can be made available if needed. See outputs for Q2 in appendix. Q2: Select the model you are going to keep for each brand and explain WHY. Report the corresponding output in an appendix attached to your report (hence, 1 output per brand) We use Adjusted R Squared to compare the Linear or Semilog Regression. R^2 is a statistic that will give some information about the goodness of fit of a model. In regression, the Adjusted R^2 coefficient of determination is a statistical measure of how well the regression line approximates the real data points. An R2 of 1 indicates that the regression line perfectly fits the data. Brand1: Linear Regression R^2 | 0.594 | SemiLog Regression R^2 | 0.563 | We use the Linear Regression Model since R-squared is higher. Brand 2: Linear Regression R^2 | 0.758 | SemiLog Regression R^2 | 0.588 | We use the Linear Regression Model since R-squared is higher Brand 3: Linear Regression R^2 | 0.352 | SemiLog Regression R^2 | 0.571 | We use the Semilog Regression Model since R-squared is higher Brand 4: Linear Regression R^2 | 0.864 | SemiLog Regression R^2 | 0.603 | We use the Linear Regression Model since R-squared is higher Q3: Here we compute the cross-price elasticity. Depending on whether we use linear or semi-log model, Linear Model Linear Model Semi-Log Model Semi-Log Model...

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... Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 4.448334 0.407452 10.91745 6.02E-19 3.640342 5.256326 3.640342 5.256326 Benefits 0.150497 0.089945 1.673202 0.097293 -0.02787 0.328862 -0.02787 0.328862 Y= 4.4483+0.1505X Graph Benefits and Overall Job Satisfaction Regression output from Excel SUMMARY OUTPUT Regression Statistics Multiple R 0.081422 R Square 0.006629 Adjusted R Square -0.00292 Standard Error 1.088941 Observations 106 ANOVA df SS MS F Significance F Regression 1 0.823019 0.823019 0.694067 0.406694 Residual 104 123.3224 1.185792 Total 105 124.1454 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 5.165093 0.443112 11.6564 1.38E-20 4.286385 6.043802 4.286385 6.043802 Benefits -0.08149 0.097817 -0.83311 0.406694 -0.27547 0.112483 -0.27547 0.112483 Y= 5.1651 + -0.0815x Graph Key components of the regression analysis Complete the following chart to identify key components of each regression output. Dependent Variable Slope Y-intercept Equation r^2 Intrinsic -0.0572 5.5062 Y=5.5062+-0.0572x 0.0049 Extrinsic 0.1505 4.4483 Y=4.4483 + 0.1505x 0.0262 Overall -0.0815 5.1651 Y=5.1651 + -0.0815x 0.0066 Similarities and Differences Something that I noticed similar......

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... rooms is 20? Explain your answer. 3) Mr Rama, president of Dan Din Dun Financial Services, believes there is a relationship between the number of client contacts and the dollar amount of sales. To document this assertion, Mr Rama gathered the following sample information. The X indicates the number of client contacts last month, and the Y shows the value of sales (RM thousands) last month for each client sampled. Number of Contacts, X | Sales (RM thousands), Y | 14 12 20 16 46 23 48 50 55 50 | 24 14 28 30 80 30 90 85 120 110 | a. Compute the coefficient of correlation and explain. b. Compute the coefficient of determination and explain. c. Test whether there is a positive correlation between both variables. Use α=0.05. d. Determine the regression equation. e. Determine the value of sales if number of contacts is 25. 4) The commercial division of a real estate firm is conducting a regression analysis of the relationship between X, annual gross rents (in thousands of dollars) and Y, selling price (in thousands of dollars) for apartment buildings. Data were collected on several properties recently sold and the following computer output was obtained. FIGURE 1: MINITAB OUTPUT The regression equation isY = 20.0 + 7.21 XPredictor Coef SE Coef TConstant 20.000 3.2213 6.21X 7.210 1.3626 5.29Analysis of VarianceSOURCE DF SS MSRegression 1 41587.3 41587.3Residual Error 7 ......

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...Stock Price Analysis For each organization, it is very important to consider and review the stock price analysis. Here, the stock price analysis of the organizations Amazon and Ebay shall be carried out. In relation to the stock price analysis, the analysis of the stock prices shall be reviewed from January 1, 2010, 2011 and 2012 and in addition to this, the stock price analysis for the organization shall also be considered regarding the stock price of the organization since the date of its incorporation. The graph showing the changes in the stock prices of the organizations is provided below (Yahoo Finance, 2014). The chart given above shows the changes in the stock prices for Ebayfrom January 1,2010, January 1,2011 and January 1,2012. These charts show the information that, the organization has been in a position to enhance its stock prices since the date of incorportation. So although the stock price has increased since being incorporated, it hasn’t been a substantial increase amount. Based on this chart, it can be said that, the stock price of the Ebay has definitely grown since the date of its incorporation till the present date, but the growth has been small yet. Though, the increase has not been a significant change, the organization has made sure that, it carries out its activities in the most appropriate manner without any kind of problem or issue for it. In relation to the Amazon, the stock prices shall be analyzed as well.. At the time of incorporation...

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... of significance drops outside of our accepted level. Tyler’s criticism seems to be justified. One would think that increased driving times would allow for greater penetration for Radio, but in the model it has no significance. | tv | Amount | 300 | Short | 11.422 | Overall(mf=3) | 34.27 | Profit | 10.28 | net | -289.72 | b) 5) Call: lm(formula = Sales ~ . - Week - week7 - week21 - week49, data = europet) Residuals: Min 1Q Median 3Q Max -2139.97 -681.28 -38.15 631.86 2121.55 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -3.398e+03 3.416e+03 -0.995 0.322562 TV 5.194e+00 1.975e+00 2.630 0.010018 * Radio 5.822e-01 1.592e+00 0.366 0.715483 Fuel.Volume 2.782e-01 5.292e-02 5.257 9.46e-07 *** Fuel.Price 8.307e+01 1.432e+01 5.801 9.22e-08 *** Temp 6.582e+01 2.112e+01 3.117 0.002440 ** Prec -1.390e+02 1.735e+01 -8.010 3.44e-12 *** Holiday...

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... determining on a regular basis, the price of the securities. The Stock Exchange is the center-point of the secondary capital market. The Nigerian Stock Exchange was established in 1960 as the Lagos Stock Exchange, the Nigerian Stock Exchange has come a very long way serving as a facility for easy transfer of stocks ownership and redistribution of wealth. Prices are determined by the interplay of the forces of demand and supply and are reported daily to assist in measuring the worth of investments and price changes over time. This study is based on the Nigerian stock market so as to determine whether investors can predict future prices to earn abnormal return based on historical price or return information which is in support of the technical analysis. The technical analysts believe that market prices exhibit identifiable patterns that are bound to be repeated. In all emerging markets, where market prices do not totally reflect fundamental variables, share prices have been adjudged to follow certain trends as a result of the drive of investors’ sentiments. (Brennan et al., 1997). The Nigerian financial market is not an exception. Studying these trends investors can make quick arbitrage profits by buying when the market is quoting low and selling when it quotes high. Therefore it is necessary to use this study to determine whether successive stock prices are dependent or not i.e. if one can predict future stock prices with historical prices on the Nigerian......

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... System and Its Inspiration.Web. 29 Sept. 2012. . Kumar, M. (2010). Causal Relationship between Stock Price and Exchange Rate: Evidence for India. International Journal Of Economic Policy In Emerging Economies, 3(1), 85-101. Kollias, C., Mylonidis, N., & Paleologou, S. (2012). The Nexus between Exchange Rates and Stock Markets: Evidence from the Euro-Dollar Rate and Composite European Stock Indices Using Rolling Analysis. Journal Of Economics And Finance, 36(1), 136-147. doi:http://dx.doi.org/ 10.1007/s12197-010-9129-8 Lean, H., Narayan, P., & Smyth, R. (2011). Exchange Rate and Stock Price Interaction in Major Asian Markets: Evidence for Individual Countries and Panels Allowing for Structural Breaks. Singapore Economic Review, 56(2), 255-277. Lin, C. (2012). The Comovement between Exchange Rates and Stock Prices in the Asian Emerging Markets. International Review Of Economics And Finance,22(1), 161-172. doi:http:// dx.doi.org/10.1016/j.iref.2011.09.006 Rahman, M., & Uddin, J. (2009). Dynamic Relationship between Stock Prices and Exchange Rates: Evidence from Three South Asian Countries. International Business Research, 2(2), 167-174. Su, D., & Fleisher, B. M. (1998). Risk, Return and Regulation in Chinese Stock Markets. Journal Of Economics And Business, 50(3), 239-256. Sohu., (2012). History data of Shanghai market stock index. http://stock.sohu.com/ Tsai, I. (2012). The Relationship between Stock Price Index and Exchange Rate in Asian Markets: A Quantile......

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... completeness, we also examine of annual meetings, our results are sensitive whether B. Stock Price Comovement to the form of disclosure. and Stock Price Crashes cannot be attributed to Roll (1988) notes that a large proportion of stock price movement systematic factors (in essence, 1- R2 from an asset pricing model regression) and posits that lower market model R2s might reflect greater activity on the part of informed traders. Consequently, the R2 measure is increasingly used as a measure of stock price informativeness (i.e., the extent towhich stockprices reflect firm-specific information). et al. (2000) provide international evidence of higher R2s in poor economies than in and posit that stronger public investor property rights in rich economies promote Morck rich economies of informedarbitrage, which allows the incorporation firm-specific informationintoassetprices. Bushman, Piotroski, and Smith (2004) show that stocks exhibit lower R2s in countries with a freer press and amore developed (2003) show that firms with financial analysis industry. Durnev, Morck, Yeung, and Zarowin lower R2s exhibit a higher association between current returns and future earnings, which suggests lower R2s imply greater stock price informativeness. Finally, Piotroski and Roulstone (2004) show that R2s are inversely related to insider trades, which are assumed to impound firm-specific information into equity prices...

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...A) Estimated regression equation – First Order: y = β0 + β1x1 + β2x2 + ε Output of 1st Model | | | | | | | | | | | | | | Regression Statistics | | | | | | Multiple R | 0.763064634 | | | | | | R Square | 0.582267636 | SSR/SST | | ̂̂̂ | | | Adjusted R Square | 0.512645575 | | | | | | Standard Error | 547.737482 | | | | | | Observations | 15 | | | | | | | | | | | | | ANOVA | | | | | | | | df | SS | MS | F | Significance F | | Regression | 2 | 5018231.543 | 2509115.772 | 8.363263464 | 0.005313599 | | Residual | 12 | 3600196.19 | 300016.3492 | | | | Total | 14 | 8618427.733 | | | | | | | | | | | | | Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Intercept | -20.35201243 | 652.7453202 | -0.031179101 | 0.975639286 | -1442.561891 | 1401.857866 | Age (x1) | 13.35044655 | 7.671676501 | 1.740225432 | 0.107375657 | -3.364700634 | 30.06559374 | Hours (x2) | 243.7144645 | 63.51173661 | 3.837313819 | 0.002363965 | 105.334278 | 382.0946511 | B) equation | ŷ= -20.3520124320994 + 13.3504465516772 x̂1 + 243.714464532425 x̂2 | C) Interpretation of β β̂1 = 13.35044655, If number of hours worked (x2) held fixed, we can estimate that every one-year increase in age (x1) the mean of annual earnings will increase by 13.35044655. β̂2 = 243.7144645, If age (X1) held fixed, we can estimate that every one hour (x2) of work increase, the mean of...

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