...Event Study Analysis: CLM Chapter 4 Definition: An event study attempts to measure the valuation effects of a corporate event, such as a merger or earnings announcement, by examining the response of the stockprice around the announcement of the event. One underlying assumption is that the market processes information about the event in an efficient and unbiased manner (more on this later). Event Study Analysis The steps for an event study are as follows: – – – – – – – Event Definition Selection Criteria Normal and Abnormal Return Measurement Estimation Procedure Testing Procedure Empirical Results Interpretation Event Study Analysis The time line for a typical event study is shown below in event time: T0 T1 0 T2 T3 The interval T0-T1is the estimation period The interval T1-T2 is the event window Time 0 is the event date in calendar time The interval T2-T3 is the post-event window There is often a gap between the estimation and event periods Models for measuring normal performance In an event study we wish to calculate the abnormal performance associated with an event. To do so, we need a model for normal returns. – For example: Suppose a firm announces earnings and the stock price rises by 3%, but the market also went up 2% that day. How much of the 3% rise should be attributed to the announcement of earnings. • Fortunately, over short event windows (one or two days) the choice of normal return models usually has little effect on the results ...
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...Interpretation of SPSS output for Car Care Inc. Jacquelynn Patterson Liberty University Online Professor Lingley Busi 331-B01 October 7, 2013 1.0 Introduction Statistics in social sciences are an important aspect in making the understanding of social behaviors plausible in organizations, governments, marketers and other cohorts with same interest. Initially, statistical manipulations were conducted manually and obliged researchers to have formulas at their fingertips. This strenuous exercise was susceptible to shortcomings in case large volumes of data were to be analyzed. In addition, manual calculations depend on human nature that is vulnerable to ill health, emotional exhaustion and fatigue. As a result, there are many chances of making errors when dealing with manual calculations. This would finally affect the end results obtained. The above mentioned problems are likely to be amplified especially when dealing with a huge number of research subjects. If this is the case, it implies that marketing research data analysis would be the most vulnerable if manual statistical manipulations were embraced. This is because marketing research depends heavily on many respondents in order for the results to valid and reliable for making inferences to the whole population. Inevitably, marketers are bludgeoned into using statistical software that can handle large volumes of cases in a single command. This does not only reduce...
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...various options on asking price and to relay how this information could be used to set prices on used Mustangs. Statistical analysis by Hypothesis Testing and Multiple Regression Analysis was performed on the asking prices for used Mustangs and it was found that there are five independent variables that affect the selling price of used Mustangs: • If the car is a convertible or not • If the car is a GT model or not • Age of the car in years • Odometer reading in miles • Number of cylinders in the engine II. Introduction Research suggests that pricing strategies can have a huge influence on company profits.[2] Several customers of Tom’s Used Mustangs have mentioned that asking prices are way out of line with the rest of the market. These prices may be too high or too low, and are never close to the going rate. It had been determined that asking prices for the used Mustangs were based on an informal scheme and has not proved to be as effective as anticipated. In researching competitors, and because the physical characteristics are many, there has been some difficulty pinpointing a useful pricing strategy. To effectively find a pricing scheme, statistical analysis of the given data involved hypothesis testing and multiple-regression analysis. Hypothesis testing is the rational agenda for applying statistical tests. The main question we usually wish to dig up from a test such as this is whether the sample data is important...
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...Identification of relevant social factors that affect customer behavior in purchasing car 1.1 Background of the Study The main purpose of this research is to identify the relevant social factors that affect purchase intention in purchasing car. The result of the research could be used as reference by the car dealer and manufacture which allows to understand the requirement of the market demand in Malaysia. Since there are a lot of competitors in vehicle industry provides advance manufacturing technologies and facilities which to be successful, automaker companies have to strengthen the need according to the need of the customer in order to remain in the car manufacturing industry. Carmaker and marketers should not only focuses on manufacturing vehicle and performance of the vehicle instead they also should emphasises on the social factors which influence the buyers decision in purchasing car such as reference group, family factor and social status. Other than that, the basic principle in the current market which is governing is customer orientation and customer centeredness in belief. Currently, the Competitive market is forced to produce the goods according to the customer needs (Tafler, 2007). The study on the consumer purchase behaviour which also refer as consumer behaviour, provides information of the consumer patterns and purchase intention (Nesai, 2009). Other than that, the organization able to survive along the organization could able to supply the needs...
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...Quality Control Theory Jonathan Agee, Steven Bonilla, Joseph Eastman, Chris Ibarola, and Bruce Kleinknight American Public University Abstract Quality. It's one simple word that in today's marketplace means the difference between greatness and bankruptcy. It's what separates the pretenders from the contenders. Because of the large availability of products on today's market, quality has become a major factor in people deciding factors. Gone are the days of old when companies could produce a product of sub-par quality and be profitable because the competitors were out of the market place. With quality being such a huge deciding factor these days with customers, it would be financially ruining if managers produce a product lacking in quality. Just try to fathom if car companies like BMW would be around if they produced poor products. Imagine showing up to a BMW dealership to purchase a "Melbourne Red Metallic" car only to find every red car was a different shade from the other. To prevent these catastrophic business practices, companies have created a control process to compare their new products to a set standard. It's this continued quality that keeps the customer and creates a successful business. Throughout this report, we will explain how companies can ensure their success by controlling the quality of their products. Before we get into the models and examples of quality control, we fist must have a basic background understanding of the concept. Quality is defined...
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...States Markets Robert R. Ebert1 and Mariel Montoney2 1 2 Department of Economics, Baldwin-Wallace College, 275 Eastland Rd., Berea, OH 44017; Economics Program, Baldwin-Wallace College, 275 Eastland Rd., Berea, OH 44017 The South Korean automobile industry has undergone considerable growth since its inception in the 1960s. That growth was initially driven by domestic demand. Since the Asian financial crisis of 1997, however, production increases for the South Korean automobile industry have been primarily a function of export sales. The research presented here explores changes in the structure of demand in its two principal marketsdomestic South Korean market and the United States market. Two models of demand are developed- one for each of the markets. Several macro economic variables are identified that have a statistically significant relationship with the demand for automobiles in each of the markets. An interesting finding of the research is that the factors apparently driving demand are different in the two markets suggesting the structure of automobile demand in South Korea differs significantly from the demand for that country’s vehicles in the United States. A major challenge facing the South Korean automobile industry is how to utilize its capacity when confronted with slowing growth in sales in both the domestic and United States markets. Key words: Economics of Korea; Automobile Industry; United States Markets; Domestic Markets The...
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...SUMMARY………………………………………. 3-4 Unique Features of Service Objectives * MARKET/MARKETING…………………………………..…… 5-6 Market Segment Sought Benefits of Service to the Market Segment Summary of Advertising and Pricing Policies Sales Projections * MANAGEMENT…………………………………………………. 6-7 Backgrounds Responsibilities * TECHNOLOGICAL…………………………………………….. 7-8 * FINANCIAL DATA……………………………………………... 9-11 Financial Projections Capital Needed Current Financial Position Start-up Cost * BACKGROUND AND PURPOSE............................................... 12-13 History Description of Products/Services Unique Aspects of our Strategy Table of Contents (Cont.) * SPECIFIC OBJECTIVES……………………………………….13-17 Revenues/Sales Profitability Market Standing Product/Service Quality Management Development Specific Market Location Trends Characteristics Buying Habits of Customers * COMPETITION ANALYSIS…………………………………… 17-21 Direct Competition Auto-care Car Wash Services/ Advantages & Disadvantages Spotless Car Wash Services/ Advantages & Disadvantages Typical Car Wash Services/ Advantages & Disadvantages Indirect competition Pricing...
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...Executive Summary This project will be focusing on 35 Ford Mustangs with a multitude of variables. The variables include price, age of car, mileage, transmission, air conditioning, amount of cylinders, vehicle color, ownership style, body style, and model type. This study will also determine if the mean price of the vehicle is dependent upon the previously mentioned variables excluding vehicle color; identifying variables of significance. Highlighting the significant variables and how they affect price will serve as a tool assisting the company with pricing future Ford Mustangs. Ford Mustangs Tom has currently opened a used car dealership. Previously Tom repaired and collected older model cars as a hobby and recently decided to turn his hobby into a career for himself. Tom has a great deal of technical understanding concerning car parts and how to repair certain vehicle parts. However, Tom has little to no experience on the business end of owning a car dealership. It has been reported that Tom’s asking prices for his vehicles are not aligned with the average market price. Ultimately, Tom does not base his prices on the used car market price; instead he bases it on assumptions. For example, Tom thinks, red cars give the impression of being “sportier and can sell at a premium,” he also believes older models normally sell for less. After much dismay and inaccurate rates in sells, Tom tries to systematically price his Mustangs, but due to the multitude of variables...
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...GAS IN 2020 Phillip Lang BUS 308 Nicholas Bergan 02/13/12 Part 1: Data Analysis The data that will be analyzed in this report is the consumer price index for fuel prices from the year 1982 to 2011. In this report we will be analyzing trend of gasoline prices and were they will take us in the future. Also this report will be help companies dealing with the oil industry and the expected price increases from a statistical perspective. Scatterplot: This chart shows us over time (x-axis) and the average price of fuel (y-axis) per year and explains the rate at which fuel prices are increasing. Without outside variables we can easily see the correlation of fuel prices now and what they will be in the future. The graph shows there is a positive correlation between price and time. The regression line and the positive slope explains that positive correlation. The slope: The slope as indicated by that diagram is .065, the value represents that the fuel price will increase over time, if the all assosiated variables are constant, by .065 units. So all of this information explains the increase in fuel prices as time elaspses. The y intercept: The y intercept from the results is -127.643. Regression model: y = 0.065x - 127.643 Estimating Fuel prices for 2020: When estimating fuel for 2020 within the model we are using we simply have x equal the year to come to the conclusion of where fuel prices will be. If the fuel price rises on average .065 units per year then...
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...ASS4Part1contd 'Storing the firm fixed-effects estimator in the simulated sample HoldbetasimFE(sim) = Application.WorksheetFunction.Index(Application.WorksheetFunction.LinEst(wfroa, wfPE), 1, 1) 'Block bootstrap loop for the FE estimator For j = 1 To b For g = 1 To s r = Int(Rnd * s) + 1 'This picks a random firm identifier For m = 1 To Y 'This loop runs over each year present in a given block i = (g - 1) * Y + m 'This creates an identifier i for observation of block g and period m in the bootstrapped sample Holdroa(i) = wfroa((r - 1) * Y + m) HoldPE(i) = wfPE((r - 1) * Y + m) Next m Next g HoldEst(j) = Application.WorksheetFunction.Index(Application.WorksheetFunction.LinEst(Holdroa, HoldPE), 1, 1) Next j 'Generating the acceptance decision for the FE estimator using block bootstrap in the simulated sample HoldacceptblockFE(sim) = 0 If HoldbetasimFE(sim) > 1.96 * Application.WorksheetFunction.StDev(HoldEst) Then HoldacceptblockFE(sim) = 1 'Classic bootstrap loop for the FE estimator For j = 1 To b For i = 1 To obs r = Int(Rnd() * obs) + 1 Holdroa(i) = roa(r) HoldPE(i) = PE(r) Holdfirm(i) = firm(r) Next i 'Computing Deviations of both Holdroa and HoldPE from their within-firm mean For k = 1 To s 'This step creates temporary variables including...
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...MULTIPLE CHOICE (CHAPTER 4) 1. Using a sample of 100 consumers, a double-log regression model was used to estimate demand for gasoline. Standard errors of the coefficients appear in the parentheses below the coefficients. Ln Q = 2.45 -0.67 Ln P + . 45 Ln Y - .34 Ln Pcars (.20) (.10) (.25) Where Q is gallons demanded, P is price per gallon, Y is disposable income, and Pcars is a price index for cars. Based on this information, which is NOT correct? a. Gasoline is inelastic. b. Gasoline is a normal good. c. Cars and gasoline appear to be mild complements. d. The coefficient on the price of cars (Pcars) is insignificant. e. All of the coefficients are insignificant. 2. In a cross section regression of 48 states, the following linear demand for per-capita cans of soda was found: Cans = 159.17 – 102.56 Price + 1.00 Income + 3.94Temp | |Coefficients |Standard Error |t Stat | |Intercept |159.17 |94.16 |1.69 | |Price |-102.56 |33.25 |-3.08 | |Income |1.00 |1.77 |0.57 | |Temperature |3.94 |0.82 |4.83 | R-Sq = 54.1% R-Sq(adj) = 51.0% From the linear regression results in the cans case...
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...Article Commentary No. 02 TEAM: MARS Student name: * Chotun Kumar Debnath ID: 20120206001 * Harish Chandra Chackraborty ID: 20120206005 Team Leader * MostafizurRahman ID: 20120206021 * Md. Parvez Rana Bhuiyan ID: 20120206024 * Babla Chandra Rudra ID: 20120206027 Article Title: Supplier development and cost management in Southeast Asia- Results from a field study Author(s): Marc Wouters, Ewout van Jarwaarde, Bianca Groen University of Twente, The Netherlands Journal: Journal of Purchasing & Supply Management 13(2007) 1. What is/are the research question(s)? The research questions are as follows: * What motives do international companies in Southeast Asia have for buying from local suppliers and investing in supplier development? * What priorities do international companies have for local supplier development initiatives? * What practice do international companies use for developing local suppliers? * How do companies manage the risk of transaction-specific investments in local supplier development in Southeast Asia? 2. Main theoretical arguments or hypotheses: Arguments: a) Motives for Supplier Development * Cost advantages * Reduction of lead times * Government regulation * Reduction of supplier dependency b) Priorities for Supplier Development, c) Supplier Development practices ...
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...MULTIPLE CHOICE (CHAPTER 4) 1. Using a sample of 100 consumers, a double-log regression model was used to estimate demand for gasoline. Standard errors of the coefficients appear in the parentheses below the coefficients. Ln Q = 2.45 -0.67 Ln P + . 45 Ln Y - .34 Ln Pcars (.20) (.10) (.25) Where Q is gallons demanded, P is price per gallon, Y is disposable income, and Pcars is a price index for cars. Based on this information, which is NOT correct? a. Gasoline is inelastic. b. Gasoline is a normal good. c. Cars and gasoline appear to be mild complements. d. The coefficient on the price of cars (Pcars) is insignificant. e. All of the coefficients are insignificant. 2. In a cross section regression of 48 states, the following linear demand for per-capita cans of soda was found: Cans = 159.17 – 102.56 Price + 1.00 Income + 3.94Temp | |Coefficients |Standard Error |t Stat | |Intercept |159.17 |94.16 |1.69 | |Price |-102.56 |33.25 |-3.08 | |Income |1.00 |1.77 |0.57 | |Temperature |3.94 |0.82 |4.83 | R-Sq = 54.1% R-Sq(adj) = 51.0% From the linear regression results in the cans case...
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...Market Analysis Overview Whether you are starting a new business or launching a new product, conducting a marketing analysis is the first step in determining if there is a need or audience for your idea. Knowing the market's needs and how it is currently serviced provides you with key information that is essential in developing your product/service and marketing plan. Too often, businesses spend thousands of dollars launching a "new" idea with a limited market because of competition. The owner is forced to reevaluate his strategy and determine if there is room for another player. Although the quality of the product is critical, your development of the best product on the market will not necessarily correlate with the most sales. Up to 50 percent of a product's price can be for marketing. The company who wins the marketing game generally will capture the larger share of the market. For related information, see Identify Your Target Market. Conducting a market analysis will help you: 1. Prepare to enter a new market 2. Launch a new product/service 3. Start a new business At the completion of this exercise, you should be able to: • Explain the concepts of a marketing analysis • Determine if there is a need for your idea or product/service • Identify a new market • Analyze your current market • Gain a competitive advantage • Begin to establish a marketing plan Outline: I. Marketing Analysis - What Is It? Why Should You Do It? II...
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...and Tools. A Brief Overview Online Analytical Processing (OLAP): OLAP is the dynamic synthesis, analysis, and consolidation of large volumns of multi-dimensional data. Multi-dimensional OLAP support common analyst operations, such as: ▪ Considation – aggregate of data, e.g. roll-ups from branches to regions. ▪ Drill-down – showing details, just the reverse of considation. ▪ Slicing and dicing – pivoting. Looking at the data from different viewpoints. E.g. X, Y, Z axis as salesman, Nth quarter and products, or region, Nth quarter and products. A Brief Overview Data Mining: Construct an advanced architecture for storing information in a multi-dimension data warehouse is just the first step to evolve from traditional DBMS. To realize the value of a data warehouse, it is necessary to extract the knowledge hidden within the warehouse. Unlike OLAP, which reveal patterns that are known in advance, Data Mining uses the machine learning techniques to find hidden relationships within data. So Data Mining is to ▪ Analyse data, ▪ Use software techniques ▪ Finding hidden and unexpected patterns and relationships in sets of data. Examples of Data Mining Applications: ▪ Identifying potential credit card customer groups ▪ Identifying buying patterns of customers. ▪ Predicting trends of market movement. Basic Structure of Data Mining tools Data Mining Techniques ...
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