...year-end stock price and the X-variable is Disney=s earnings per share reads as follows (t-statistics in parentheses): Pt = -$1.661 + $31.388EPSt, R2 = 86.8% (-1.13) (12.03) Use this model to forecast Disney=s average stock price for the 2007-09 period using the Value Line estimate of Disney=s average earnings per share for 2007-09. Discuss this share-price forecast. 1. We have EPS for 2007/2009 equal to $1.65 Disney’s average stock price for the 2007-09 is Pt = -$1.661 + $31.388(1.65) = $50.13 • Disney’s stock price will grow by $50.13 in case of giving Disney’s EPS for 2007/2009 the same PER for 1980/2003 • According to table 6.7, a five-year average annual rate of capital appreciation of roughly 16.5% per year is represented by 23,33 which is the year end stock price per $ for the year 2003. B. A simple regression model over the 1980-2003 period where the Y-variable is the Disney year-end stock price and the X-variable is Disney=s book value per share reads as follows (t-statistics in parentheses): Pt = $3.161 + $2.182BVt, R2 = 76.9% (1.99) (8.57) Use this model to forecast Disney=s average stock price for the 2007-09 period using the Value Line estimate of Disney=s average book value per share for 2007-09. Discuss this share-price forecast. 2. We have BVPS for 2007/2009 equal to $17.55 Disney’s average stock price for the 2007/2009 is Pt = $3.161 + $2.182(17.55) = $41.46 • Disney’s stock price will...
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...Efficient Market Hypothesis: Examining the Case of South Asian Stock Markets Sharon Prakash Abstract This study examines the relevance of the Efficient Market Hypothesis among emerging stock markets belonging to the South Asian Association for Regional Cooperation (India, Pakistan, Sri Lanka and Bangladesh) and the Global economy. The study employs daily closing prices of eminent market indices from a time period 2004-2013.The stock returns have been subjected to unit root tests such as the Augmented Dickey Fuller test and a panel unit root test. Additionally the existence of random walk for these stock markets has also been examined through the Jarque-Bera statistic. The results indicate information inefficiency in the time period under study for all indices. Investors can therefore predict future prices on the basis of historical information, and receive excessive returns. The results have implications for developing economies wherein the government has to ensure that all asset related information be made public, to curb state interference. Introduction The concept of Efficient Market Hypothesis (EMH) holds special importance in the field of Finance, especially Capital markets. This hypothesis postulates that markets are informationally efficient. This asserts that the price of any security will fully reflect all the information that is available to the investors. That being said, one cannot consistently achieve returns that are excess of the average market returns...
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...Testing the weak form efficiency of Islamabad Stock exchange (ISE) Syed Tauseef Raza Gilani Department of Management Sciences, The Islamia University of Bahawalpur, Pakistan Email: tosif399@gmail.com, Tel: +00923006327270 Abstract The characteristics of stock prices reflect the all available information in market. This study explored the weak form efficiency of Islamabad Stock Exchange (ISE). In this research paper, we have also revealed the behavior of prices traded in Islamabad Stock Exchange, and how it behaves in different unusual events. Stock markets are the major contributor to economy. To test the weak form efficiency of Islamabad Stock exchange, we have tested Efficient Market Hypothesis. EMH is method to measure the stock prices trends in the market. Efficient market hypothesis also helps for making the right investment decisions. From two of decades, EMH has obtained much great importance in the field of finance. So it has attracted many researchers to explore the anomalous behavior of efficient stock market. Efficient market hypothesis has three main categories: 1. Weak form 2. Semi-strong form 3. Strong form. We will focus only weak form of market efficiency in ISE. Focus of the study is to analyze the weak form of ISE-10 in the stock market. For this purpose we have used different statistical technique for analyzing the data that is collected from the official website of ISE. Data will be in the form of weekly ISE-10 share index. Time period of data is From...
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...discussed instrumental variables (IV) estimators in the context of Generalized Method of Moments (GMM) estimation and presented Stata routines for estimation and testing comprising the ivreg2 suite. Since that time, those routines have been considerably enhanced and additional routines have been added to the suite. This paper presents the analytical underpinnings of both basic IV/GMM estimation and these enhancements and describes the enhanced routines. Some of these features are now also available in Stata 10’s ivregress, while others are not. The additions include: • Estimation and testing that is robust to, and efficient in the presence of, arbitrary serial correlation. • A range of test statistics that allow the user to address the problems of underidentification or weak identification, including statistics that are robust in the presence of heteroskedasticity, autocorrelation or clustering. • Three additional IV/GMM estimators: the GMM continuously updated estimator (CUE) of...
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...on accounting and stock performance data. Much has been made of this distinction in both the popular and the academic literature, where gains from hostile takeovers result from replacing incumbent managers and gains from friendly takeovers result from strategic synergies. Alternatively, hostility could ref lect strategic choices made by the bidder or the target. Empirical tests show that most deals described as hostile in the press are not distinguishable from friendly deals in economic terms, except that hostile transactions involve publicity as part of the bargaining process. THE PERCEPTION OF HOSTILITY in American takeovers has had important connotations in both the popular and the academic literature. Unwelcome bids are often perceived to threaten at least some of the stakeholders in target corporations, leading to extensive defensive reactions by the management of the target firm. In contrast, friendly takeovers are often seen to create synergies that make both the bidder and the target firm better off ~see, for example, Mørck, Shleifer, and Vishny ~1988, 1989!!. The distinction between hostile and friendly takeovers is also important if removing an inefficient target management team creates the gains from hostile takeovers. Manne ~1965! refers to this as part of the market for corporate control. Several papers have shown that management turnover increases following hostile takeovers, including Shivdasani ~1993!. Although these theoretical polar cases seem intuitive, in...
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...theory stock returns have shown a noticeable volatility; thus if an investor desires to increase expected returns she must face a higher level of risk. Similarly, it has been proven that owing a group of financial securities can assist the investor to improve the return/risk tradeoff; that is owing eight stocks will produce an improved return/risk product over time versus owing one stock. Therefore, in evaluating a portfolio it is critically important to compare returns and risks involved; but in order to compare and evaluate returns and risks the investor has to know how to calculate these two important criteria (Markowitz, 1970). The return of a stock is based on its current price, its expected price plus distributed dividends. Therefore, if the current price of a stock is $40.00, its expected market price, let us say after a year, is increased to $50.00 and the distributed dividends amount to $5.00, its return is calculated as: [(Pt-Po) + DIV]/Po; Po is the current price of the stock, Pt is the price of the stock after one year and DIV are the distributed dividends per share. Substituting the above assumed numbers into the equation we have [($50-$40) +$5]/$40 = 0.25 or 25%. The risk of a stock is mainly measured by the standard deviation (Markowitz, 1987). In the case of a portfolio the expected return is the weighted average return of the returns of all the stocks included in the portfolio. The weight represents the amount that has been invested in each of the stocks included...
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...Clifford S. Asness Value and momentum strategies both have demonstrated power to predict the crosssection of stock returns, but are these strategies related? Measures of momentum and value are negatively correlated across stocks, yet each is positively related to the cross-section of average stock returns. We examine whether the marginal power of value or momentum differs depending upon the level of the other variable. Value strategies work, in general, but are strongest among low-momentum (loser) stocks and weakest among high-momentum (winner) stocks. The momentum strategy works, in general, but is particularly strong among low-value (expensive) stocks. These results hold despite finding comparable spreads in value measures among stocks with different levels of momentum and comparable spreads in the momentum measure among stocks with different levels of value. Any explanation for why value and momentum work must explain this interaction. esearchers have convincingly demonstrated that value strategies can be used to predict stock returns. For instance, Fama and French (1992) showed that value strategies based on a firm’s ratio of book-to-market value of equity (BV/MV) have power to forecast stock returns. Similarly, Lakonishok, Shleifer, and Vishny (1994) showed that value strategies based on a firm’s cash-flow-toprice ratio (C/P) have power to forecast stock returns. Although conflicting explanations have been offered for the success of these strategies, the empirical...
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...INTRODUCTION The most common form of the Efficient Markets Hypothesis (EMH) states that market prices fully reflect all publicly available information (Fama 1970). The EMH has been highly influential among academics, but practitioners and regulators appear unconvinced. Investors work hard to identify mispriced stocks on the basis of public data, or pay others to do so, even though the EMH asserts that such efforts are wasted. Managers seek to boost stock prices by hiding bad news in footnotes, and regulators work hard to defeat such efforts, even though the EMH asserts that information is reflected in prices no matter how obscure its presentation. Beliefs about inefficiency play a central role in the debate over recognizing expenses for incentive stock options. Opponents of expensing argue that the resulting lower net income will inappropriately reduce market prices, while proponents argue the market does not fully recognize compensation costs reported only in footnotes. In efficient markets, however, expensing these costs has no direct effect on prices, as long as the details of the compensation are included in footnotes. The decision to expense option costs could reduce stock price indirectly, even in efficient markets, by affecting the terms of contracts between the reporting firm and other parties (Watts and Zimmerman 1986). However, few of the parties to the debate appear concerned about these effects. The academic community is showing increasing dissatisfaction with the EMH...
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...model with these settings, we get that the mean of the main response variable - average cost - is 568.4 and the half width is equal to 2.37. Although the confidence interval is not extremely wide taking into account the relatively high value of mean, we still perform a check whether it is possible to get more precise results by using common random numbers. To figure out if the model would benefit from the use of CRN we perform a pilot study. In this study we need to have two different scenarios and then we can decide whether it is useful to use CRN by checking the following inequality: { } { } { } and if this inequality holds, then it is worth using CRN in the model. In our case the scenarios differ in three variables: review period , the lead time and . For the first scenario we use the values of the base case, that is and . For the second scenario we change these values to and . We select as the response variable the average cost, for which we will check whether the inequality holds. So in the formula { } is the variance of the average cost in scenario . To calculate this variance we above...
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...Statistics Darrell Washington BUS308: Statistics for Managers Instructor: Gary Withers November 23, 2015 Statistics Introduction Data analysis is done to convert the raw data into meaningful information. Statistics is all about this data analysis. Before actually working on data analysis in real world, it is important that the basic knowledge is possessed by everybody involved in this process. The following paper seeks to provide basic knowledge in some specific areas of statistical data analysis. Descriptive statistics As the name suggests, descriptive statistics means analysis of data to describe or summarize data in a meaningful manner. The analysis helps in determination of patterns that exist in the data. Descriptive statistics simply describes the data but not present an analysis beyond the data. One cannot make any conclusions about any hypothesis using this. The data, when presented to users, is difficult to comprehend in its raw form. Sometimes the sheer size and volume of data may render it impossible to understand what it represents. Descriptive statistics helps in proper presentation of data such that it can be understood and analyzed by the user. For example, if we had the data about the returns from stocks of 100 companies, then that data would make no sense as it would be difficult to comprehend. But if that data is arranges, classified industry-wise, an average is calculated for each industry and for all the stocks, and then the interpretation would...
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...Weak- Form Market Efficiency of Dhaka Stock Exchange (DSE), Bangladesh ABU TAHER MOLLIK Economics & Finance, Regional School of Business, Faculty of Law and Management, La-Trobe University, Bendigo, VIC 3550, Australia. Email:abumollik@yahoo.com.au; a.mollik@latrobe.edu.au M KHOKAN BEPARI PhD Student School of Commerce and Marketing Faculty of Arts, Business, Informatics and Education Central Queensland University, Australia Email: k.bepari@cqu.edu.au; khokan552@yahoo.com Phone:+610402917968 Weak Form Market Efficiency of Dhaka Stock Exchange (DSE), Bangladesh Abstract This paper examines the weak-form efficiency in Dhaka Stock Exchange (DSE) of Bangladesh adjusting for thin trading problem. Both non-parametric tests and parametric tests are used. The data sets consist of daily DSE General Index (DSE-GEN) and DSE 20 Index for the period ranging from January 1, 2002 to December 31, 2007. The results of the study reveal that DSE return series are not normally distributed. Both the return series are stationary and do not follow a random walk. Overall, the study rejects the weak form efficiency of DSE. Key words: Efficient Market Hypothesis; Dhaka Stock Exchange; Random Walk Model; Weak Form of Efficiency; Return autocorrelation. JEL classification: G14, N25, G 34 Weak Form Market Efficiency of Dhaka Stock Exchange (DSE), Bangladesh 1. Introduction The theory of efficient market hypothesis (EMH) proposed by Fama (1965) was a ‘water...
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...Firms Size And Gains From Acquisition By Santosh Singh Vasudev 1 PDF Created with deskPDF PDF Writer - Trial :: http://www.docudesk.com Firms Size And Gains From Acquisition Contents Introduction 1 Predictable Hypothesis 2 Data And Methodology 6 Data 6 Methodology 8 Abnormal Performance Measure 8 Test Statistics 9 Empirical Findings 10 Conclusion 22 References 24 2 PDF Created with deskPDF PDF Writer - Trial :: http://www.docudesk.com Firms Size And Gains From Acquisition Introduction 1. Takeovers are one of the most important events in corporate finance, both for a firm and the economy. Extensive research has shown that shareholders in bidding firms gain significantly and that wealth is created at the announcement of takeovers i.e., combined bidder and target returns are positive. 2. Our main focus is on examining the returns to acquirer’s i.e. large and small firms, making bids for public, private, and subsidiary targets, using cash and stock, and seeing how the acquirers’ returns vary by these characteristics and the acquirer’s size. Our study enables us to provide new evidence on what bidder returns tell us about takeovers. Therefore, our sample provides a fruitful testing ground for probing the meaning of returns to acquirers. I. Predictable Hypothesis A. Investment Opportunity Hypothesis 3. Myers (1977) links the existence of growth opportunities and corporate borrowing activity...
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...Stock Picking Skills of SEC Employees Shivaram Rajgopal Schaefer Chaired Professor of Accounting Goizueta Business School Emory University 1300 Clifton Road NE, Atlanta, GA 30030 Email: shivaram.rajgopal@emory.edu Roger M. White PhD Student in Accounting J. Mack Robinson School of Business Georgia State University Email: rwhite42@gsu.edu Preliminary and incomplete Comments welcome This draft: February 18, 2014 Abstract: We use a new data set obtained via a Freedom of Information Act request to investigate the trading strategies of the employees of the Securities and Exchange Commission (SEC). We find that a hedge portfolio that goes long on SEC employees’ buys and short on SEC employees’ sells earns positive and economically significant abnormal returns of (i) about 4% per year for all securities in general; and (ii) about 8.5% in U.S. common stocks in particular. The abnormal returns stem not from the buys but from the sale of stock ahead of a decline in stock prices. We find that at least some of these SEC employee trading profits are information based, as they tend to divest (i) in the run-up to SEC enforcement actions; and (ii) in the interim period between a corporate insider’s paper-based filing of the sale of restricted stock with the SEC and the appearance of the electronic record of such sale online on EDGAR. These results raise questions about potential rent seeking activities of the regulator’s employees. We acknowledge financial assistance from our respective...
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...of Business Case Studies – November/December 2010 Volume 6, Number 6 Calculating The Beta Coefficient And Required Rate Of Return For Coca-Cola John C. Gardner, University of New Orleans, USA Carl B. McGowan, Jr., Norfolk State University, USA Susan E. Moeller, Eastern Michigan University, USA ABSTRACT In this paper, we demonstrate how to compute the required rate of return for Coca-Cola using modern portfolio theory with data downloaded from the internet. We demonstrate how to calculate monthly returns for the index and Coca-Cola and how to use the returns to compute the beta coefficient and the required rate of return using the downloaded data. We show how to validate the data for the market index and the company and how to compute the returns using the dividend and stock split adjusted prices. We demonstrate how to graph the characteristic line for Coca-Cola and use the graph to check that the regression was run correctly. We use Coca-Cola and the S&P 500 Index in this paper, but any company listed on Yahoo! Finance can be used as the example. This paper can be used as the basis of a lecture on intermediate corporate finance or investments to demonstrate the process using a real company. Keywords: beta; characteristic line; required rate of return; Coca-Cola; teaching note INTRODUCTION M arkowitz1 (1952) began modern portfolio theory (MPT) which can be used to explain the relationship between risk and return for assets, particularly stocks. Stock of companies...
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...Lecture 0 Statistics Review Yexiao Xu School of Management The University of Texas at Dallas 1 Outline Probability Random variables Distributions Characterizing a random variable (ex-ante) • Expected returns • variances, covariances • Correlation Statistics (ex-post) 2 Random Events Many events occurs with uncertainty • Working condition of hard drive in your laptop ─ Working properly versus hard drive crash • Driving home ─ Safely get to home versus accident • Stock price ─ Going up versus going down We know the possible outcomes of a random event, but we do not know which outcome will actually occur An outcome of a event could be • Discreet: roll of a dice {one of the six faces} • Continuous: plane arrival time {sometime today} • Multivariate: weight and height of a person ─ { (short and heavy), (short and light), (tall and heavy), (tall and light)} 3 What Is Probability? The likelihood that each outcome will occur are usually different Probability is a numerical measure of the likelihood of an event to occur • It can only take a number between 0 and 1 Interpreting the probability scale • 0 Event never will occur 0.5 Event and “not event” are equal likely 1 Event will Always occur 4 Random Variables A Random Variable: maps from outcomes of an event to numerical values • It assigns numerical values to each possible outcome ─ Instead of using descriptive language to describe...
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