...Financial Econometrics With Eviews Roman Kozhan Download free books at Roman Kozhan Financial Econometrics Download free eBooks at bookboon.com 2 Financial Econometrics – with EViews © 2010 Roman Kozhan & Ventus Publishing ApS ISBN 978-87-7681-427-4 To my wife Nataly Download free eBooks at bookboon.com 3 Contents Financial Econometrics Contents Preface 6 1 1.1 1.2 1.3 1.4 Introduction to EViews 6.0 Workfiles in EViews Objects Eviews Functions Programming in Eviews 7 8 10 18 22 2 2.1 2.2 2.3 Regression Model Introduction Linear Regression Model Nonlinear Regression 34 34 34 52 3 3.1 3.2 3.3 Univariate Time Series: Linear Models Introduction Stationarity and Autocorrelations ARMA processes 54 54 54 59 www.sylvania.com We do not reinvent the wheel we reinvent light. Fascinating lighting offers an infinite spectrum of possibilities: Innovative technologies and new markets provide both opportunities and challenges. An environment in which your expertise is in high demand. Enjoy the supportive working atmosphere within our global group and benefit from international career paths. Implement sustainable ideas in close cooperation with other specialists and contribute to influencing our future. Come and join us in reinventing light every day. Light is OSRAM Download free eBooks at bookboon.com 4 Click on the ad to read more Contents ...
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...EViews Workshop Program: MSc in Finance 2011-2012 Instructor: Dimitris Tsouknidis, MSc, MBA, PhD Email: dtsouknidis@gmail.com Course Description • Workshop 1 – Introduction, Regression Analysis, Multiple Regression Analysis • Workshop 2 – Issues with the Classical Linear Regression Model and Univariate Time-series Modeling in Finance • Workshop 3 – Multivariate Time-Series Modeling in Finance and Modeling Long-run Relationships in Finance MSc Finance - EViews Workshop 1 - 2012 2 Workshop 1 Introduction, Classical Linear Regression Analysis and Multiple Regression Analysis 19 January 2012 Agenda • • • • • • • Introduction to EViews Importing Data Loading and Saving Datasets Graphical and Statistical Analysis Regression Analysis Multiple Linear Regressions Case Studies – January Effect MSc Finance - EViews Workshop 1 - 2012 4 Introduction • EViews is a menu-driven econometric software. • Open EViews requires: – Start/All Programs/EViews 7 • EViews organizes data, graphs, output, etc. as objects. • Each of these objects can be copied, saved and/or cut-andpasted. • EViews is not case sensitive e.g. INDEX = index. • EViews is producing workfiles (.wf1). • You can import data from Microsoft Excel (.xls) and create workfiles (.wf1). MSc Finance - EViews Workshop 1 - 2012 5 Creating a Workfile • Click: File/New/Workfile. • You can select the type of your workfile (Dated – regular frequency, Balanced panel, Unstructured/Undated ), the frequency...
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...МИНИСТЕРСТВО ОБРАЗОВАНИЯ РОССИЙСКОЙ ФЕДЕРАЦИИ НАЦИОНАЛЬНЫЙ ФОНД ПОДГОТОВКИ КАДРОВ ИННОВАЦИОННЫЙ ПРОЕКТ РАЗВИТИЯ ОБРАЗОВАНИЯ Программа «Совершенствование дисциплин в вузах» преподавания социально-экономических МИЭФ ГУ-ВШЭ (наименование вуза) Пособие для студентов по курсу «Анализ временных рядов» Москва 2003 Часть I. Руководство по эконометрическому пакету EViews Введение......................................................................................................... 3 1. Общие принципы работы в EViews ............................................................ 3 1.1. Создание рабочего файла EViews ........................................................ 4 Задания для самостоятельной работы......................................................... 9 1.2. Общая структура рабочего файла EViews ........................................... 9 Задания для самостоятельной работы....................................................... 12 2. Анализ одномерных временных рядов ..................................................... 12 2.1. Структура окна временного ряда ....................................................... 12 Задания для самостоятельной работы....................................................... 16 2.2 Построение графика временного ряда ................................................ 17 Задания для самостоятельной работы....................................................... 20 2.3. Описательные статистики временного ряда........................
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...Summary of important EViews-Commands Import of data from EXCEL: if the xlsx-format does not work, use File.xls Choice of sample period: Sample / @all @first @last 1990 2010 1981Q3 2005Q1 1960M1 2000M11 in command line e.g.: smpl @first 1990 Univariate statistics: Click series / View / Spreadsheet Graph Descriptive Statistics&Tests Correlogram data as numbers Graphics z.B. histogram, mean, etc. autocorrelationen Generation/Transformation of series: Generate / x = 0 generates a series with zeros Generate / pi = (pc – pc(-1))/pc(-1)*100 Generates the inflation rate in % based on prices pc Generate / x = log(y) taking logs Generate / dlx = dlog(x) dlx = log(x) – log(x(-1)) Growth rate in continuous time Generate / y = exp(x) exp(x) as command: series x=0 Trend variable (linear): Generate / t = @trend Standard normal distributed realizations: Generate / x = nrnd Lags, lagged variables, taking differences: Generate / x1 = x(-1) x1(t) = x(t-1), Lag 1 of x Generate / dx = d(x) dx(t) = x(t) – x(t-1) = (1-B)x(t) first difference Generate / d2x = d(x,2) d2x(t) = dx(t) – dx(t-1) = (1-B)^(2)x(t) taking first differences twice Generate / d12x = d(x,0,12) d12x(t) = x(t) - x(t-12) = [1-B^(12)]x(t) seasonal difference for monthly data Generate d12_1x = d(x,1,12) d12_1x(t) = (1-B)[1-B^(12)]x(t) Geneartion of dummy variables: seasonal dummies: s=1,2,3,... Generate / ds = @seas(s) as command: series ds = @seas(s) Generate / d1 = 0 and manually in View/Spreadsheet use Edit+/p-value for x of...
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...ivanca@arnet.com.ar . El producto E-views provee herramientas de regresión y predicción bajo Windows. Con E-views usted puede revelar una relación estadística desde sus datos y luego utilizar esta relación para predecir valores futuros de los mismos. Dentro de las áreas en donde E-views puede ser útil están: Predicción de ventas Análisis y predicción de costos. Análisis Financiero. Predicción macroeconómica. Simulación. Análisis científico de los datos y evaluación. E-views es una nueva versión del conjunto de herramientas para manipular series de tiempo originalmente desarrolladas en el software Time Series Processor para grandes computadoras. El predecesor inmediato de E-views fue el MicroTSP, lanzado por primera vez en 1981. Aunque Eviews fue desarrollado por economistas y la mayoría de sus usos están en la economía, no hay nada que haga limitar su utilidad a las series de tiempo económicas. Inclusive considerables proyectos de corte transversal pueden llevarse a cabo en E-views. El objeto básico dentro de E-views es la serie de tiempo. Cada serie posee un nombre, y usted puede realizar cualquier tipo de operación sobre todas las observaciones simplemente mencionando el nombre de la serie. E-views provee convenientes formas de visualización para ingresar las series desde el teclado o desde un archivo, para crear una serie a partir de otra ya existente, para mostrar o imprimir la serie, y para llevar a cabo análisis estadísticos sobre las relaciones entre las series. ...
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...BÀI GIẢNG 2: HƯỚNG DẪN SỬ DỤNG EVIEWS 6.0 ThS Phùng Thanh Bình BÀI GIẢNG 2 HƯỚNG DẪN SỬ DỤNG EVIEWS 6.0 MỤC TIÊU BÀI GIẢNG: 1. Eviews là gì? 2. Workfile là gì? 3. Trình bày dữ liệu trong Eviews? 4. Đối tượng trong Eviews 5. Quản lý dữ liệu trong Eviews 6. Các phép toán và hàm số gì trong Eviews 7. Các vấn đề cơ bản về phân tích dữ liệu chuỗi và nhóm 8. Xây dựng hàm kinh tế lượng trong Eviews 9. Kiểm định giả thiết của mô hình hồi qui trong Eviews ĐỐI TƯỢNG BÀI GIẢNG: 1. Tài liệu bài giảng cho sinh viên đại học 2. Tài liệu tham khảo ôn tập cho học viên cao học NHỮNG VẤN ĐỀ CƠ BẢN VỀ EVIEWS EVIEWS LÀ GÌ? Eviews1 cung cấp các công cụ phân tích dữ liệu phức tạp, hồi qui và dự báo chạy trên nền Windows. Với Eviews ta có thể nhanh chóng xây dựng một mối quan hệ thống kê từ dữ liệu có sẵn và sử dụng mối quan hệ này để dự báo các giá trị tương lai. Eviews có thể hữu ích trong nhiều lĩnh vực như phân tích và đánh giá dữ liệu khoa học, phân tích tài 1 Viết tắt của Econometrics Views 1 BÀI GIẢNG 2: HƯỚNG DẪN SỬ DỤNG EVIEWS 6.0 ThS Phùng Thanh Bình chính, dự báo kinh tế vĩ mô, mô phỏng, dự báo doanh số, và phân tích chi phí. Đặc biệt, Eviews là một phần mềm rất mạnh cho các nghiên cứu dữ liệu thời gian và dữ liệu chéo với cỡ mẫu lớn. Eviews đưa ra nhiều cách nhập dữ liệu rất thông dụng và dễ sử dụng như nhập từ bàn phím, từ các tập tin sẵn có dưới dạng Excel hay Text. Với Eviews, chúng ta có thể dễ dàng tạo ra các chuỗi mới từ các chuỗi hiện hành, hoặc mở rộng...
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...ENGLISH 281 Draft Workshop Questions for Essay Two in Wikis Steps: 1. Post your draft to your appointed Wiki area by Sunday, April 5 by midnight. 2. Review drafts attached to your Wiki area and provide feedback using the below questions, pasting the answers in to the Wiki area and making it clear who the answers are for/whose draft you are commenting on and that you are the writer. For example, you could paste in something like the following: Susan, here are my thoughts/feedback on your draft posted so far: #1. [Provide feedback using the criteria below] #2 [Provide feedback using the criteria below] #3 on [Repeat above] You are expected to complete these steps for at least one draft posted to your group’s Wiki by Monday, April 6 by midnight for possible five points credit. Be sure to answer the “Specific Questions” below the first ten questions here depending on which essay prompt you are reading for a draft. 1. Does the author/student have all of the “front matter” needed in the draft? (i.e, Does it give an author tag with the title of the poem in quotes or name of book in italics and name of film in italics being worked with in the essay, for example and the author(s) name of text being discussed in the first one or two sentences of introduction)? If this is information is missing, let the author know here and also provide an example please of how it could be better. 2. Are the introductory sentences attention-grabbing? If they are...
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...Case Study: CNX Nifty Midcap Index Descriptive statistics A. Closing price 1. Normality Test – non-normal distribution 2. Stationarity test for Log returns – series is stationary Null Hypothesis: LOG_RETURNS has a unit root | | Exogenous: Constant | | | Lag Length: 0 (Automatic based on SIC, MAXLAG=23) | | | | | | | | | | | | | | t-Statistic | Prob.* | | | | | | | | | | | Augmented Dickey-Fuller test statistic | -35.96681 | 0.0000 | Test critical values: | 1% level | | -3.434655 | | | 5% level | | -2.863328 | | | 10% level | | -2.567771 | | | | | | | | | | | | *MacKinnon (1996) one-sided p-values. | | | | | | | | | | | | Augmented Dickey-Fuller Test Equation | | Dependent Variable: D(LOG_RETURNS) | | Method: Least Squares | | | Date: 11/03/10 Time: 16:06 | | | Sample (adjusted): 1/04/2005 11/02/2010 | | Included observations: 1449 after adjustments | | | | | | | | | | | | Coefficient | Std. Error | t-Statistic | Prob. | | | | | | | | | | | LOG_RETURNS(-1) | -0.944031 | 0.026247 | -35.96681 | 0.0000 | C | 0.000692 | 0.000484 | 1.429639 | 0.1530 | | | | | | | | | | | R-squared | 0.472016 | Mean dependent var | 1.64E-07 | Adjusted R-squared | 0.471651 | S.D. dependent var | 0.025333 | S.E. of regression | 0.018414 | Akaike info criterion | -5.150009 | Sum squared resid | 0.490653...
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...Review of Related Studies -- Inventory System The following statements given are related to our study about the inventory system which is found very useful for the proponents in making the system. "It is nearly impossible to overemphasize the importance of keeping inventory levels under control," Ronald Pachura wrote in an article for IIE Solutions. "Whether the problems incurred are caused by carrying too little or too much inventory, manufacturers need to become aware that inventory control is not just a materials management or warehouse department issue. The purchasing, receiving, engineering, manufacturing, and accounting departments all contribute to the accuracy of the inventory methods and records." It is little wonder that business experts commonly cite inventory management as a vital element that can spell the difference between success and failure in today's keenly competitive business world. Writing in Production and Inventory Management Journal, Godwin Udo described telecommunications technology as a critical organizational asset that can help a company realize important competitive gains in the area of inventory management. According to Udo, companies that make good use of this technology are far better equipped to succeed than those who rely on outdated or unwieldy methods of inventory control. Automation can draidatically affect all phases of inventory management, including counting and monitoring of inventory items; recording and retrieval of item storage...
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...I nternational eview of anagement and usiness esearch ol. 2 ssue.1 Impact of Organizational Culture on Employee Performance ALHARBI MOHAMMAD AWADH University Technology Malaysia International Business School, Malaysia E-mail: alharbimohamd@gmail.com ALYAHYA, MOHAMMED SAAD University Utara Malaysia College of Business Malaysia. Email: msy330@hotmail.com Abstract Aim of the study: The relationship between organizational culture and performance has been study and a clear link between them has been identified by certain researcher’s research. The main aim of research article is to identify and measure strong relationship between performance and organizational culture. Methodology: Literature review is adopted as methodology to assess the culture of an organization impacts upon process, employees and systems. Findings: Certain dimensions of culture have been identified so far and research shows that value and norms of an organization were based upon employee relationship. The goal of an organization is to increase level of performance by designing strategies. The performance management system has been measured by balance scorecard and by understanding nature and ability of system culture of an organization have been identified. Recommendation: The strong culture of an organization based upon managers and leaders help in improving level of performance. Managers relate organization performance and culture to each other as they help in providing competitive...
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...t-statistic. Here are the various cases of the test equation: a. When the time series is flat (i.e. doesn’t have a trend) and potentially slowturning around zero, use the following test equation: Δz t = θz t −1 + α 1 Δz t −1 + α 2 Δz t − 2 + L + α p Δz t − p + a t where the number of augmenting lags (p) is determined by minimizing the Schwartz Bayesian information criterion or minimizing the Akaike information criterion or lags are dropped until the last lag is statistically significant. EVIEWS allows all of these options for you to choose from. Notice that this test equation does not have an intercept term or a time trend. What you want to use for your test is the t-statistic associated with the Ordinary least squares estimate of θ . This is called the Dickey-Fuller tstatistic. Unfortunately, the Dickey-Fuller t-statistic does not follow a standard t-distribution as the sampling distribution of this test statistic is skewed to the left with a long, left-hand-tail. EVIEWS will give you the correct critical values for the test, however. Notice that the test is left-tailed. The null hypothesis of the Augmented Dickey-Fuller t-test is H0 :θ = 0 (i.e. the data needs to be differenced to make it stationary) versus the alternative hypothesis of H1 : θ < 0 b. (i.e. the data is stationary and doesn’t need to be differenced) When the time series is flat and potentially slow-turning around a non-zero value, use the following test equation: Δz t = α...
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...Introduction The purpose of the project was to see if using futures contracts to hedge can reduce exposure to market risk over a period of time. This project covered both stock portfolios and bond portfolios. To illustrate this, the method of linear regression and least squares was used. We used linear regression to regress the spot rate against the futures contract return. To complete this project both EViews and Microsoft Excel was used. Summary of Points Stock Regression 2008-2009 Around 96% of the stock portfolio returns can be explained. This was calculated by finding the variance proportion, r2 in EViews. The high percentage suggests that our model is a strong fit for the data that was analyzed. We were also able to show that our estimated beta was reliably different than 0 and reliably different than 1. This was done through two-sided tests using a 95% significance level. The tcrit value was found using the excel function tinv() with 497 degrees of freedom. Testing for B=0, the t-statistic was 110.087, with the tcrit value being 1.964 this was a clear indication to reject the null because 110.087 is not in the range of -1.964 to 1.964. Testing for B=1, the t-statistic was -3.37853, with the tcrit value being 1.964 this was also a clear indication to reject the null because -3.37853 is not in the range of -1.964 to 1.964. After finding the optimal hedge ratio we calculated the dollar position for the futures market hedge to be $9,702,250. By using...
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...A REVOLUTION IN Donald M. Norris is President, Strategic Initiatives, Inc. Jon Mason is Executive Consultant, education.au limited, and Assistant Director, Educational Technology Standards Australia. Robby Robson is President and Senior Partner, Eduworks Corporation, and chair of the IEEE Learning Technology Standards Committee. Paul Lefrere is Executive Director E-learning, Microsoft EMEA, and Professor of E-learning, University of Tampere, Finland. Geoff Collier is CFO and Senior Partner, Eduworks Corporation. KNOWLEDGE SHARING By Donald M. Norris, Jon Mason, Robby Robson, Paul Lefrere, and Geoff Collier 14 EDUCAUSE r eview September/October 2003 © 2003 Donald M. Norris, Jon Mason, Robby Robson, Paul Lefrere, and Geoff Collier Photo by Garry Landsman, © 2003 September/October 2003 EDUCAUSE r eview 15 E-knowledge finds expression in many shapes and forms in a profoundly networked world. It is not just a digitized collection of knowledge. E-knowledge consists of knowledge objects and knowledge flows that combine content,...
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...Hypothesis Testing and EViews p-values: Suppose that we want to test a null hypothesis about a single parameter using its estimated value (for example a mean or a regression coefficient). We can do so using a t-test. To begin, suppose that the parameter to be estimated is β. We must first specify a null hypothesis and an alternative hypothesis. 2 tail test: For a two tailed test, we want to test whether β is a particular value or not. We first set the value of β that we want to test. We’ll call this β0 to indicate that this will be the value of β under the null hypothesis. In a two tail test, the null and alternative hypotheses are: H0 : β = β 0 HA : β = β0 ˆ We proceed by estimating β. We denote the estimated value as β. This could for example be a sample mean estimate of the population mean, a least squared estimate of a regression coefficient, or a maximum likelihood estimate of a model coefficient, ˆ depending on the context. The estimate β is usually accompanied by a standard error ˆ to indicate how precisely it is estimated. We denote this standard error as se(β). This ˆ is a random variable with a sampling distribution. It will have reflects the fact the β different values in different samples. We can then form the following test statistic by computing the standardised statistic ˆ whereby we subtract the hypothesisized value β0 from the estimate β and divide by its standard error: t-stat = ˆ β − β0 ˆ se(β) ˆ Again, this test statistic is a random variable since it depends...
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...whether there is data available that will allow you to answer your question. It is a good idea to write down your ideal data set that would allow you to address your topic. If you find that the available data is not even close to what you had originally desired, you might want to change your topic. Also, remember that knowing the location of your data – website, reference book, etc – is not the same as having your data available to use. It may take a LONG time to get the data in a format that EVIEWS can read. Do not leave this till the last minute. For most data, I enter the data into Excel first. I save the Excel sheet in the oldest version, namely MS Excel Worksheet 2.1 . The reason is that format can be read by most programs whereas newer formats may or may not be read. Eviews easily reads an Excel sheet 2.1 version. You should use the first row to label your columns (variables). Be sure to follow the naming conventions in Eviews and do not use 'C' or 'RESIDUALS'. Eviews can only use numeric data. A warning for time series analysis - In order to find interesting results, you need variation in your data. For example, it would be difficult to find the effect of defense spending on American manufacturing industries if...
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