CHAPTER III METHODOLOGY
|
|
- Alexandrina Jackson
- 6 years ago
- Views:
Transcription
1 CHAPTER III METHODOLOGY 3.1 Description In this chapter, the calculation steps, which will be done in the analysis section, will be explained. The theoretical foundations and literature reviews are already explained in Chapter II. The explanation started from the data collection method, and ended in the calculation to achieve the result Data Collection Data on this research is taken based on the criteria that the stock used in this observation has more than one period to be traded at lower limit of trading price in the observation period from finance.yahoo.com at 27/6/2012. The closing time is 4.00 PM GMT +7, and the closing price is based on the last transaction price in the given day. 3.3 Calculation Methodology Below are the calculation methodology used on this report. The calculation will start with gap analysis and linear interpolation on the stock price, and end with back-testing of the portfolio on the given trading strategy. 15
2 16 Figure 3.1 Calculation Step
3 3.3.1 Return Calculation Return of the data is calculated using continuous compounded return based on equation (2.2). This method is used since the characteristic of the financial assets, which is fluctuated over the time and not directly observable in the data, which only containing the closing price. Another reason in using geometric rate of return is the time difference between the markets closing bell. In order to minimize the problems above, continuous compounded return is give more accurate measurements compared to arithmetic return. The calculation in this section will be calculated in Eviews 7 software Descriptive statistics and Visual Observation Descriptive statistics and Visual Observation helps the observant to get the basic information of the data characteristics, such as trend, distribution characteristic, and prejudgment of stationarity and heteroskedasticity of the data. The calculation and graph in this section will be calculated and plotted in Eviews 7 software Augmented Dickey-Fuller Test As one of the method to detect the stationarity, Augmented Dickey-Fuller test is essential to detect the stationarity of the data, which is based on the result of the test, as explained in Chapter II section The critical value, which will be used as the decision criterion is 5%. The data is stationer if the result of t-statistic value is smaller than the t-statistic value of 5%. Eviews7 software will be use to test the Augmented Dickey-Fuller Heteroskedasticity Test Classical linear regression is based on the assumption that the data is homoskedastic. Because of that reason, test of heteroskedasticity is one of the crucial points for meeting the criteria of classical linear regression. To detect the heteroskedasticity, White Heteroskedasticity test as explained in Chapter II section is used. The data is heteroskedastic if the test result is below the probability value of the F-statistic and R- squared is below the critical value, which is 5%. All of the calculation in this section will be done in Eviews 7 software. 17
4 3.3.5 Autocorrelation Other criteria for the classical linear regression are the independency of the data. To test the independency of the data, Ljung-Box probability value and visual observation from the correlogram can help to detect the correlation of the data, which is a sign of the dependency of the data with the data from past period. The method of calculation is already explained in Chapter II section The data has an autocorrelation if the Ljung-Box test statistic probability is less than critical value, which is 5%. The calculation and graph will be done in Eviews 7 software GARCH Model Building Based on the information from the previous test, a normal GARCH model for the data is selected. Significant autocorrelation on the model is also taken into account in deciding the model. Model selection is based on several criteria listed below based on the priority of the criteria: 1. The model is statistically significant 2. No autocorrelation in the residual 3. Residual is homoskedastic 4. If several model are fitted with the criteria above, the model is chosen based on AIC and BIC ratio as explained in Chapter II section Simplicity of the model The calculation and model building in this section will be done in Eviews 7 software and based on the look-likelihood function Residual Analysis After the model is built, and the coefficient is significant, the remaining residual should be checked. ARCH-LM test, as a tool to check the heteroskedasticity is being used, with 5% rejection criteria. The residual is also being tested in order to make sure that there are no remaining autocorrelation in the residual. 18
5 3.3.8 Critical Value Calculation Based on the conditional variance and forecasted return from GARCH model explained above, critical value is calculated based on equation (2.29) for normal distribution, and equation (2.30) for GARCH with t-student distribution. The degree of freedom is defined based on GARCH with t-student modification degree of freedom calculation result Model Back-Testing To obtain the result of the back testing, the comparison between the actual return and the critical value is compared. To obtain the result, below is the methodology, which are used to measure the back testing result 1. Count the number of observations, which are lower than the lower critical value, or higher than upper critical value. 2. Divide the result with the number of observation. 3. Compare the result from stage 2 to the given 1- confidence interval. 4. The model is under-confident if the result from stage 2 is higher than 1- confidence interval, and the model is over-confident if the result from stage 2 is lower than 1-confidence interval. 5. Calculate Z value based on equation (2.31) 6. Reject the model as the unbiased estimator if the calculated Z value excess Z value of 1-confidence interval divided by Portfolio Back-Testing To measure the indicator performance, back-testing on trading strategies is used. Below is the methodology to obtain the result of back-testing. 1. Calculate the indicator of buying and selling point for each of the trading strategies 2. Calculate actual return produced by the portfolio by equation (2.2) 19
6 There are several assumptions in back-testing on the trading strategies in this research, which are: 1. There are no trading commission and fee for each of transactions. 2. Jakarta Stock Exchange is being used as a benchmark of portfolio. 3. The closing price and the next opening price is the same. 4. Back-testing assumes that the researcher is being able to buy and sell at the next day opening price of the buying and selling signal. 20
Chapter 4 Level of Volatility in the Indian Stock Market
Chapter 4 Level of Volatility in the Indian Stock Market Measurement of volatility is an important issue in financial econometrics. The main reason for the prominent role that volatility plays in financial
More informationBrief Sketch of Solutions: Tutorial 2. 2) graphs. 3) unit root tests
Brief Sketch of Solutions: Tutorial 2 2) graphs LJAPAN DJAPAN 5.2.12 5.0.08 4.8.04 4.6.00 4.4 -.04 4.2 -.08 4.0 01 02 03 04 05 06 07 08 09 -.12 01 02 03 04 05 06 07 08 09 LUSA DUSA 7.4.12 7.3 7.2.08 7.1.04
More informationGARCH Models. Instructor: G. William Schwert
APS 425 Fall 2015 GARCH Models Instructor: G. William Schwert 585-275-2470 schwert@schwert.ssb.rochester.edu Autocorrelated Heteroskedasticity Suppose you have regression residuals Mean = 0, not autocorrelated
More informationBooth School of Business, University of Chicago Business 41202, Spring Quarter 2014, Mr. Ruey S. Tsay. Solutions to Midterm
Booth School of Business, University of Chicago Business 41202, Spring Quarter 2014, Mr. Ruey S. Tsay Solutions to Midterm Problem A: (30 pts) Answer briefly the following questions. Each question has
More informationBooth School of Business, University of Chicago Business 41202, Spring Quarter 2010, Mr. Ruey S. Tsay. Solutions to Midterm
Booth School of Business, University of Chicago Business 41202, Spring Quarter 2010, Mr. Ruey S. Tsay Solutions to Midterm Problem A: (30 pts) Answer briefly the following questions. Each question has
More informationEconomics 413: Economic Forecast and Analysis Department of Economics, Finance and Legal Studies University of Alabama
Problem Set #1 (Linear Regression) 1. The file entitled MONEYDEM.XLS contains quarterly values of seasonally adjusted U.S.3-month ( 3 ) and 1-year ( 1 ) treasury bill rates. Each series is measured over
More informationModelling volatility - ARCH and GARCH models
Modelling volatility - ARCH and GARCH models Beáta Stehlíková Time series analysis Modelling volatility- ARCH and GARCH models p.1/33 Stock prices Weekly stock prices (library quantmod) Continuous returns:
More informationThis homework assignment uses the material on pages ( A moving average ).
Module 2: Time series concepts HW Homework assignment: equally weighted moving average This homework assignment uses the material on pages 14-15 ( A moving average ). 2 Let Y t = 1/5 ( t + t-1 + t-2 +
More informationEmpirical Study on Short-Term Prediction of Shanghai Composite Index Based on ARMA Model
Empirical Study on Short-Term Prediction of Shanghai Composite Index Based on ARMA Model Cai-xia Xiang 1, Ping Xiao 2* 1 (School of Hunan University of Humanities, Science and Technology, Hunan417000,
More informationBooth School of Business, University of Chicago Business 41202, Spring Quarter 2012, Mr. Ruey S. Tsay. Solutions to Midterm
Booth School of Business, University of Chicago Business 41202, Spring Quarter 2012, Mr. Ruey S. Tsay Solutions to Midterm Problem A: (34 pts) Answer briefly the following questions. Each question has
More informationModeling Volatility of Price of Some Selected Agricultural Products in Ethiopia: ARIMA-GARCH Applications
Modeling Volatility of Price of Some Selected Agricultural Products in Ethiopia: ARIMA-GARCH Applications Background: Agricultural products market policies in Ethiopia have undergone dramatic changes over
More informationMODELING VOLATILITY OF BSE SECTORAL INDICES
MODELING VOLATILITY OF BSE SECTORAL INDICES DR.S.MOHANDASS *; MRS.P.RENUKADEVI ** * DIRECTOR, DEPARTMENT OF MANAGEMENT SCIENCES, SVS INSTITUTE OF MANAGEMENT SCIENCES, MYLERIPALAYAM POST, ARASAMPALAYAM,COIMBATORE
More informationResearch Article The Volatility of the Index of Shanghai Stock Market Research Based on ARCH and Its Extended Forms
Discrete Dynamics in Nature and Society Volume 2009, Article ID 743685, 9 pages doi:10.1155/2009/743685 Research Article The Volatility of the Index of Shanghai Stock Market Research Based on ARCH and
More informationIS INFLATION VOLATILITY CORRELATED FOR THE US AND CANADA?
IS INFLATION VOLATILITY CORRELATED FOR THE US AND CANADA? C. Barry Pfitzner, Department of Economics/Business, Randolph-Macon College, Ashland, VA, bpfitzne@rmc.edu ABSTRACT This paper investigates the
More informationModeling Exchange Rate Volatility using APARCH Models
96 TUTA/IOE/PCU Journal of the Institute of Engineering, 2018, 14(1): 96-106 TUTA/IOE/PCU Printed in Nepal Carolyn Ogutu 1, Betuel Canhanga 2, Pitos Biganda 3 1 School of Mathematics, University of Nairobi,
More informationA Note on the Oil Price Trend and GARCH Shocks
MPRA Munich Personal RePEc Archive A Note on the Oil Price Trend and GARCH Shocks Li Jing and Henry Thompson 2010 Online at http://mpra.ub.uni-muenchen.de/20654/ MPRA Paper No. 20654, posted 13. February
More informationA Note on the Oil Price Trend and GARCH Shocks
A Note on the Oil Price Trend and GARCH Shocks Jing Li* and Henry Thompson** This paper investigates the trend in the monthly real price of oil between 1990 and 2008 with a generalized autoregressive conditional
More informationForecasting Exchange Rate between Thai Baht and the US Dollar Using Time Series Analysis
Forecasting Exchange Rate between Thai Baht and the US Dollar Using Time Series Analysis Kunya Bowornchockchai International Science Index, Mathematical and Computational Sciences waset.org/publication/10003789
More informationCase Study: Predicting U.S. Saving Behavior after the 2008 Financial Crisis (proposed solution)
2 Case Study: Predicting U.S. Saving Behavior after the 2008 Financial Crisis (proposed solution) 1. Data on U.S. consumption, income, and saving for 1947:1 2014:3 can be found in MF_Data.wk1, pagefile
More informationMarket Integration, Price Discovery, and Volatility in Agricultural Commodity Futures P.Ramasundaram* and Sendhil R**
Market Integration, Price Discovery, and Volatility in Agricultural Commodity Futures P.Ramasundaram* and Sendhil R** *National Coordinator (M&E), National Agricultural Innovation Project (NAIP), Krishi
More informationGraduated from Glasgow University in 2009: BSc with Honours in Mathematics and Statistics.
The statistical dilemma: Forecasting future losses for IFRS 9 under a benign economic environment, a trade off between statistical robustness and business need. Katie Cleary Introduction Presenter: Katie
More informationVolatility in the Indian Financial Market Before, During and After the Global Financial Crisis
Volatility in the Indian Financial Market Before, During and After the Global Financial Crisis Praveen Kulshreshtha Indian Institute of Technology Kanpur, India Aakriti Mittal Indian Institute of Technology
More informationThi-Thanh Phan, Int. Eco. Res, 2016, v7i6, 39 48
INVESTMENT AND ECONOMIC GROWTH IN CHINA AND THE UNITED STATES: AN APPLICATION OF THE ARDL MODEL Thi-Thanh Phan [1], Ph.D Program in Business College of Business, Chung Yuan Christian University Email:
More informationA Predictive Model for Monthly Currency in Circulation in Ghana
A Predictive Model for Monthly Currency in Circulation in Ghana Albert Luguterah 1, Suleman Nasiru 2* and Lea Anzagra 3 1,2,3 Department of s, University for Development Studies, P. O. Box, 24, Navrongo,
More informationINFORMATION EFFICIENCY HYPOTHESIS THE FINANCIAL VOLATILITY IN THE CZECH REPUBLIC CASE
INFORMATION EFFICIENCY HYPOTHESIS THE FINANCIAL VOLATILITY IN THE CZECH REPUBLIC CASE Abstract Petr Makovský If there is any market which is said to be effective, this is the the FOREX market. Here we
More informationEstimation, Analysis and Projection of India s GDP
MPRA Munich Personal RePEc Archive Estimation, Analysis and Projection of India s GDP Ugam Raj Daga and Rituparna Das and Bhishma Maheshwari 2004 Online at https://mpra.ub.uni-muenchen.de/22830/ MPRA Paper
More informationDemand For Life Insurance Products In The Upper East Region Of Ghana
Demand For Products In The Upper East Region Of Ghana Abonongo John Department of Mathematics, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana Luguterah Albert Department of Statistics,
More informationVolatility Analysis of Nepalese Stock Market
The Journal of Nepalese Business Studies Vol. V No. 1 Dec. 008 Volatility Analysis of Nepalese Stock Market Surya Bahadur G.C. Abstract Modeling and forecasting volatility of capital markets has been important
More informationForecasting the Volatility in Financial Assets using Conditional Variance Models
LUND UNIVERSITY MASTER S THESIS Forecasting the Volatility in Financial Assets using Conditional Variance Models Authors: Hugo Hultman Jesper Swanson Supervisor: Dag Rydorff DEPARTMENT OF ECONOMICS SEMINAR
More informationARCH Models and Financial Applications
Christian Gourieroux ARCH Models and Financial Applications With 26 Figures Springer Contents 1 Introduction 1 1.1 The Development of ARCH Models 1 1.2 Book Content 4 2 Linear and Nonlinear Processes 5
More informationModeling and Forecasting TEDPIX using Intraday Data in the Tehran Securities Exchange
European Online Journal of Natural and Social Sciences 2017; www.european-science.com Vol. 6, No.1(s) Special Issue on Economic and Social Progress ISSN 1805-3602 Modeling and Forecasting TEDPIX using
More informationMODELING EXCHANGE RATE VOLATILITY OF UZBEK SUM BY USING ARCH FAMILY MODELS
International Journal of Economics, Commerce and Management United Kingdom Vol. VI, Issue 11, November 2018 http://ijecm.co.uk/ ISSN 2348 0386 MODELING EXCHANGE RATE VOLATILITY OF UZBEK SUM BY USING ARCH
More informationRecent analysis of the leverage effect for the main index on the Warsaw Stock Exchange
Recent analysis of the leverage effect for the main index on the Warsaw Stock Exchange Krzysztof Drachal Abstract In this paper we examine four asymmetric GARCH type models and one (basic) symmetric GARCH
More informationThe analysis of the multivariate linear regression model of. soybean future influencing factors
Volume 4 - Issue 4 April 218 PP. 39-44 The analysis of the multivariate linear regression model of soybean future influencing factors Jie He a,b Fang Chen a,b * a,b Department of Mathematics and Finance
More informationAn Empirical Research on Chinese Stock Market Volatility Based. on Garch
Volume 04 - Issue 07 July 2018 PP. 15-23 An Empirical Research on Chinese Stock Market Volatility Based on Garch Ya Qian Zhu 1, Wen huili* 1 (Department of Mathematics and Finance, Hunan University of
More informationResearch on the GARCH model of the Shanghai Securities Composite Index
International Academic Workshop on Social Science (IAW-SC 213) Research on the GARCH model of the Shanghai Securities Composite Index Dancheng Luo Yaqi Xue School of Economics Shenyang University of Technology
More informationDeterminants of Stock Prices in Ghana
Current Research Journal of Economic Theory 5(4): 66-7, 213 ISSN: 242-4841, e-issn: 242-485X Maxwell Scientific Organization, 213 Submitted: November 8, 212 Accepted: December 21, 212 Published: December
More informationJet Fuel-Heating Oil Futures Cross Hedging -Classroom Applications Using Bloomberg Terminal
Jet Fuel-Heating Oil Futures Cross Hedging -Classroom Applications Using Bloomberg Terminal Yuan Wen 1 * and Michael Ciaston 2 Abstract We illustrate how to collect data on jet fuel and heating oil futures
More informationAn Analysis of Spain s Sovereign Debt Risk Premium
The Park Place Economist Volume 22 Issue 1 Article 15 2014 An Analysis of Spain s Sovereign Debt Risk Premium Tim Mackey '14 Illinois Wesleyan University, tmackey@iwu.edu Recommended Citation Mackey, Tim
More informationPer Capita Housing Starts: Forecasting and the Effects of Interest Rate
1 David I. Goodman The University of Idaho Economics 351 Professor Ismail H. Genc March 13th, 2003 Per Capita Housing Starts: Forecasting and the Effects of Interest Rate Abstract This study examines the
More informationAmath 546/Econ 589 Univariate GARCH Models
Amath 546/Econ 589 Univariate GARCH Models Eric Zivot April 24, 2013 Lecture Outline Conditional vs. Unconditional Risk Measures Empirical regularities of asset returns Engle s ARCH model Testing for ARCH
More informationANALYSIS OF THE RELATIONSHIP OF STOCK MARKET WITH EXCHANGE RATE AND SPOT GOLD PRICE OF SRI LANKA
ANALYSIS OF THE RELATIONSHIP OF STOCK MARKET WITH EXCHANGE RATE AND SPOT GOLD PRICE OF SRI LANKA W T N Wickramasinghe (128916 V) Degree of Master of Science Department of Mathematics University of Moratuwa
More informationGraduate School of Business, University of Chicago Business 41202, Spring Quarter 2007, Mr. Ruey S. Tsay. Midterm
Graduate School of Business, University of Chicago Business 41202, Spring Quarter 2007, Mr. Ruey S. Tsay Midterm GSB Honor Code: I pledge my honor that I have not violated the Honor Code during this examination.
More informationComputer Lab Session 2 ARIMA, ARCH and GARCH Models
JBS Advanced Quantitative Research Methods Module MPO-1A Lent 2010 Thilo Klein http://thiloklein.de Contents Computer Lab Session 2 ARIMA, ARCH and GARCH Models Exercise 1. Estimation of a quarterly ARMA
More informationDATABASE AND RESEARCH METHODOLOGY
CHAPTER III DATABASE AND RESEARCH METHODOLOGY The nature of the present study Direct Tax Reforms in India: A Comparative Study of Pre and Post-liberalization periods is such that it requires secondary
More informationA STUDY ON IMPACT OF BANKNIFTY DERIVATIVES TRADING ON SPOT MARKET VOLATILITY IN INDIA
A STUDY ON IMPACT OF BANKNIFTY DERIVATIVES TRADING ON SPOT MARKET VOLATILITY IN INDIA Manasa N, Ramaiah University of Applied Sciences Suresh Narayanarao, Ramaiah University of Applied Sciences ABSTRACT
More informationIndian Institute of Management Calcutta. Working Paper Series. WPS No. 797 March Implied Volatility and Predictability of GARCH Models
Indian Institute of Management Calcutta Working Paper Series WPS No. 797 March 2017 Implied Volatility and Predictability of GARCH Models Vivek Rajvanshi Assistant Professor, Indian Institute of Management
More informationBooth School of Business, University of Chicago Business 41202, Spring Quarter 2013, Mr. Ruey S. Tsay. Midterm
Booth School of Business, University of Chicago Business 41202, Spring Quarter 2013, Mr. Ruey S. Tsay Midterm ChicagoBooth Honor Code: I pledge my honor that I have not violated the Honor Code during this
More informationFinancial Econometrics: Problem Set # 3 Solutions
Financial Econometrics: Problem Set # 3 Solutions N Vera Chau The University of Chicago: Booth February 9, 219 1 a. You can generate the returns using the exact same strategy as given in problem 2 below.
More informationCHAPTER 2 THEORETICAL FOUNDATION. Bank is one of a well-known financial institution in Indonesia. In general,
CHAPTER 2 THEORETICAL FOUNDATION 2.1 Bank Bank is one of a well-known financial institution in Indonesia. In general, bank is known as a place for people to save their money. It is a safer and better way
More informationPrerequisites for modeling price and return data series for the Bucharest Stock Exchange
Theoretical and Applied Economics Volume XX (2013), No. 11(588), pp. 117-126 Prerequisites for modeling price and return data series for the Bucharest Stock Exchange Andrei TINCA The Bucharest University
More informationConflict of Exchange Rates
MPRA Munich Personal RePEc Archive Conflict of Exchange Rates Rituparna Das and U R Daga 2004 Online at http://mpra.ub.uni-muenchen.de/22702/ MPRA Paper No. 22702, posted 17. May 2010 13:37 UTC Econometrics
More informationDonald Trump's Random Walk Up Wall Street
Donald Trump's Random Walk Up Wall Street Research Question: Did upward stock market trend since beginning of Obama era in January 2009 increase after Donald Trump was elected President? Data: Daily data
More informationAssicurazioni Generali: An Option Pricing Case with NAGARCH
Assicurazioni Generali: An Option Pricing Case with NAGARCH Assicurazioni Generali: Business Snapshot Find our latest analyses and trade ideas on bsic.it Assicurazioni Generali SpA is an Italy-based insurance
More informationLAMPIRAN. Null Hypothesis: LO has a unit root Exogenous: Constant Lag Length: 1 (Automatic based on SIC, MAXLAG=13)
74 LAMPIRAN Lampiran 1 Analisis ARIMA 1.1. Uji Stasioneritas Variabel 1. Data Harga Minyak Riil Level Null Hypothesis: LO has a unit root Lag Length: 1 (Automatic based on SIC, MAXLAG=13) Augmented Dickey-Fuller
More informationThe Analysis of ICBC Stock Based on ARMA-GARCH Model
Volume 04 - Issue 08 August 2018 PP. 11-16 The Analysis of ICBC Stock Based on ARMA-GARCH Model Si-qin LIU 1 Hong-guo SUN 1* 1 (Department of Mathematics and Finance Hunan University of Humanities Science
More informationMacroeconometrics - handout 5
Macroeconometrics - handout 5 Piotr Wojcik, Katarzyna Rosiak-Lada pwojcik@wne.uw.edu.pl, klada@wne.uw.edu.pl May 10th or 17th, 2007 This classes is based on: Clarida R., Gali J., Gertler M., [1998], Monetary
More informationSUSTAINABILITY PLANNING POLICY COLLECTING THE REVENUES OF THE TAX ADMINISTRATION
2007 2008 2009 2010 Year IX, No.12/2010 127 SUSTAINABILITY PLANNING POLICY COLLECTING THE REVENUES OF THE TAX ADMINISTRATION Prof. Marius HERBEI, PhD Gheorghe MOCAN, PhD West University, Timişoara I. Introduction
More informationSteven Trypsteen. School of Economics and Centre for Finance, Credit and. Macroeconomics, University of Nottingham. May 15, 2014.
Cross-Country Interactions, the Great Moderation and the Role of Volatility in Economic Activity Steven Trypsteen School of Economics and Centre for Finance, Credit and Macroeconomics, University of Nottingham
More informationBooth School of Business, University of Chicago Business 41202, Spring Quarter 2012, Mr. Ruey S. Tsay. Midterm
Booth School of Business, University of Chicago Business 41202, Spring Quarter 2012, Mr. Ruey S. Tsay Midterm ChicagoBooth Honor Code: I pledge my honor that I have not violated the Honor Code during this
More informationA SEARCH FOR A STABLE LONG RUN MONEY DEMAND FUNCTION FOR THE US
A. Journal. Bis. Stus. 5(3):01-12, May 2015 An online Journal of G -Science Implementation & Publication, website: www.gscience.net A SEARCH FOR A STABLE LONG RUN MONEY DEMAND FUNCTION FOR THE US H. HUSAIN
More informationSTUDYING THE EFFECT OF FINANCIAL LEVERAGE ON AGENCY COST RESULTING FROM FREE CASH FLOW OF MANUFACTURING COMPANIES ACCEPTED IN TEHRAN STOCK EXCHANGE
STUDYING THE EFFECT OF FINANCIAL LEVERAGE ON AGENCY COST RESULTING FROM FREE CASH FLOW OF MANUFACTURING COMPANIES ACCEPTED IN TEHRAN STOCK EXCHANGE Mahmoodreza Mostaghimi 1, Esmaeil Ramezanpour 2, Amir
More informationList of tables List of boxes List of screenshots Preface to the third edition Acknowledgements
Table of List of figures List of tables List of boxes List of screenshots Preface to the third edition Acknowledgements page xii xv xvii xix xxi xxv 1 Introduction 1 1.1 What is econometrics? 2 1.2 Is
More informationEconometric Models for the Analysis of Financial Portfolios
Econometric Models for the Analysis of Financial Portfolios Professor Gabriela Victoria ANGHELACHE, Ph.D. Academy of Economic Studies Bucharest Professor Constantin ANGHELACHE, Ph.D. Artifex University
More informationTHE IMPACT OF IMPORT ON INFLATION IN NAMIBIA
European Journal of Business, Economics and Accountancy Vol. 5, No. 2, 207 ISSN 2056-608 THE IMPACT OF IMPORT ON INFLATION IN NAMIBIA Mika Munepapa Namibia University of Science and Technology NAMIBIA
More informationForecasting Financial Markets. Time Series Analysis
Forecasting Financial Markets Time Series Analysis Copyright 1999-2011 Investment Analytics Copyright 1999-2011 Investment Analytics Forecasting Financial Markets Time Series Analysis Slide: 1 Overview
More informationMODELING VOLATILITY OF US CONSUMER CREDIT SERIES
MODELING VOLATILITY OF US CONSUMER CREDIT SERIES Ellis Heath Harley Langdale, Jr. College of Business Administration Valdosta State University 1500 N. Patterson Street Valdosta, GA 31698 ABSTRACT Consumer
More informationModelling Stock Market Return Volatility: Evidence from India
Modelling Stock Market Return Volatility: Evidence from India Saurabh Singh Assistant Professor, Graduate School of Business,Devi Ahilya Vishwavidyalaya, Indore 452001 (M.P.) India Dr. L.K Tripathi Dean,
More informationAnalysis of the Relation between Treasury Stock and Common Shares Outstanding
Analysis of the Relation between Treasury Stock and Common Shares Outstanding Stoyu I. Nancie Fimbel Investment Fellow Associate Professor San José State University Accounting and Finance Department Lucas
More informationWeb Appendix. Are the effects of monetary policy shocks big or small? Olivier Coibion
Web Appendix Are the effects of monetary policy shocks big or small? Olivier Coibion Appendix 1: Description of the Model-Averaging Procedure This section describes the model-averaging procedure used in
More informationUnivariate Time Series Analysis of Forecasting Asset Prices
[ VOLUME 3 I ISSUE 3 I JULY SEPT. 2016] E ISSN 2348 1269, PRINT ISSN 2349-5138 Univariate Time Series Analysis of Forecasting Asset Prices Tanu Shivnani Research Scholar, Jawaharlal Nehru University, Delhi.
More informationARIMA ANALYSIS WITH INTERVENTIONS / OUTLIERS
TASK Run intervention analysis on the price of stock M: model a function of the price as ARIMA with outliers and interventions. SOLUTION The document below is an abridged version of the solution provided
More informationIntroductory Econometrics for Finance
Introductory Econometrics for Finance SECOND EDITION Chris Brooks The ICMA Centre, University of Reading CAMBRIDGE UNIVERSITY PRESS List of figures List of tables List of boxes List of screenshots Preface
More informationANALYSIS OF STOCHASTIC PROCESSES: CASE OF AUTOCORRELATION OF EXCHANGE RATES
Abstract ANALYSIS OF STOCHASTIC PROCESSES: CASE OF AUTOCORRELATION OF EXCHANGE RATES Mimoun BENZAOUAGH Ecole Supérieure de Technologie, Université IBN ZOHR Agadir, Maroc The present work consists of explaining
More informationModeling Error Variances Understanding CH, ARCH and GARCH Models
Modeling Error Variances Understanding CH, ARCH and GARCH Models J. Stuart McMenamin Itron s Forecasting Brown Bag Seminar March 9, 011 Please Remember In order to help this session run smoothly, your
More informationInflation and inflation uncertainty in Argentina,
U.S. Department of the Treasury From the SelectedWorks of John Thornton March, 2008 Inflation and inflation uncertainty in Argentina, 1810 2005 John Thornton Available at: https://works.bepress.com/john_thornton/10/
More informationFactor Affecting Yields for Treasury Bills In Pakistan?
Factor Affecting Yields for Treasury Bills In Pakistan? Masood Urahman* Department of Applied Economics, Institute of Management Sciences 1-A, Sector E-5, Phase VII, Hayatabad, Peshawar, Pakistan Muhammad
More informationLAMPIRAN. Lampiran I
67 LAMPIRAN Lampiran I Data Volume Impor Jagung Indonesia, Harga Impor Jagung, Produksi Jagung Nasional, Nilai Tukar Rupiah/USD, Produk Domestik Bruto (PDB) per kapita Tahun Y X1 X2 X3 X4 1995 969193.394
More informationGovernment Tax Revenue, Expenditure, and Debt in Sri Lanka : A Vector Autoregressive Model Analysis
Government Tax Revenue, Expenditure, and Debt in Sri Lanka : A Vector Autoregressive Model Analysis Introduction Uthajakumar S.S 1 and Selvamalai. T 2 1 Department of Economics, University of Jaffna. 2
More informationRelationship between Inflation and Unemployment in India: Vector Error Correction Model Approach
Relationship between Inflation and Unemployment in India: Vector Error Correction Model Approach Anup Sinha 1 Assam University Abstract The purpose of this study is to investigate the relationship between
More informationDeterminants of Merchandise Export Performance in Sri Lanka
Determinants of Merchandise Export Performance in Sri Lanka L.U. Kalpage 1 * and T.M.J.A. Cooray 2 1 Central Environmental Authority, Battaramulla 2 Department of Mathematics, University of Moratuwa *Corresponding
More informationAn Empirical Research on Chinese Stock Market and International Stock Market Volatility
ISSN: 454-53 Volume 4 - Issue 7 July 8 PP. 6-4 An Empirical Research on Chinese Stock Market and International Stock Market Volatility Dan Qian, Wen-huiLi* (Department of Mathematics and Finance, Hunan
More informationEconometrics II. Seppo Pynnönen. Spring Department of Mathematics and Statistics, University of Vaasa, Finland
Department of Mathematics and Statistics, University of Vaasa, Finland Spring 2018 Part IV Financial Time Series As of Feb 5, 2018 1 Financial Time Series Asset Returns Simple returns Log-returns Portfolio
More informationMarket Risk Management for Financial Institutions Based on GARCH Family Models
Washington University in St. Louis Washington University Open Scholarship Arts & Sciences Electronic Theses and Dissertations Arts & Sciences Spring 5-2017 Market Risk Management for Financial Institutions
More informationThe Economic Consequences of Dollar Appreciation for US Manufacturing Investment: A Time-Series Analysis
The Economic Consequences of Dollar Appreciation for US Manufacturing Investment: A Time-Series Analysis Robert A. Blecker Unpublished Appendix to Paper Forthcoming in the International Review of Applied
More informationLecture 5a: ARCH Models
Lecture 5a: ARCH Models 1 2 Big Picture 1. We use ARMA model for the conditional mean 2. We use ARCH model for the conditional variance 3. ARMA and ARCH model can be used together to describe both conditional
More informationThe Relationship between Spot & Future Price of Crude Oil with basic Risk & reserves Using ARCH family models
The Relationship between Spot & Future Price of Crude Oil with basic Risk & reserves Using ARCH family models Sina Mehrabirad PhD Student of Economics İSTANBUL Bilgi University Sina.Mehrabirad@bilgiedu.net
More informationEquity Price Dynamics Before and After the Introduction of the Euro: A Note*
Equity Price Dynamics Before and After the Introduction of the Euro: A Note* Yin-Wong Cheung University of California, U.S.A. Frank Westermann University of Munich, Germany Daily data from the German and
More informationThe University of Chicago, Booth School of Business Business 41202, Spring Quarter 2017, Mr. Ruey S. Tsay. Solutions to Final Exam
The University of Chicago, Booth School of Business Business 41202, Spring Quarter 2017, Mr. Ruey S. Tsay Solutions to Final Exam Problem A: (40 points) Answer briefly the following questions. 1. Describe
More information11/28/2018. Overview. Multiple Linear Regression Analysis. Multiple regression. Multiple regression. Multiple regression. Multiple regression
Multiple Linear Regression Analysis BSAD 30 Dave Novak Fall 208 Source: Ragsdale, 208 Spreadsheet Modeling and Decision Analysis 8 th edition 207 Cengage Learning 2 Overview Last class we considered the
More informationF UNCTIONAL R ELATIONSHIPS BETWEEN S TOCK P RICES AND CDS S PREADS
F UNCTIONAL R ELATIONSHIPS BETWEEN S TOCK P RICES AND CDS S PREADS Amelie Hüttner XAIA Investment GmbH Sonnenstraße 19, 80331 München, Germany amelie.huettner@xaia.com March 19, 014 Abstract We aim to
More informationYafu Zhao Department of Economics East Carolina University M.S. Research Paper. Abstract
This version: July 16, 2 A Moving Window Analysis of the Granger Causal Relationship Between Money and Stock Returns Yafu Zhao Department of Economics East Carolina University M.S. Research Paper Abstract
More informationSTOCK MARKET EFFICIENCY, NON-LINEARITY AND THIN TRADING EFFECTS IN SOME SELECTED COMPANIES IN GHANA
STOCK MARKET EFFICIENCY, NON-LINEARITY AND THIN TRADING Abstract EFFECTS IN SOME SELECTED COMPANIES IN GHANA Wiredu Sampson *, Atopeo Apuri Benjamin and Allotey Robert Nii Ampah Department of Statistics,
More informationFinancial Econometrics Notes. Kevin Sheppard University of Oxford
Financial Econometrics Notes Kevin Sheppard University of Oxford Monday 15 th January, 2018 2 This version: 22:52, Monday 15 th January, 2018 2018 Kevin Sheppard ii Contents 1 Probability, Random Variables
More informationForecasting the Philippine Stock Exchange Index using Time Series Analysis Box-Jenkins
EUROPEAN ACADEMIC RESEARCH Vol. III, Issue 3/ June 2015 ISSN 2286-4822 www.euacademic.org Impact Factor: 3.4546 (UIF) DRJI Value: 5.9 (B+) Forecasting the Philippine Stock Exchange Index using Time HERO
More informationYour Name (Please print) Did you agree to take the optional portion of the final exam Yes No. Directions
Your Name (Please print) Did you agree to take the optional portion of the final exam Yes No (Your online answer will be used to verify your response.) Directions There are two parts to the final exam.
More informationCapital Structure Determinants of Indonesian Plantation Firms: Empirical Study on Indonesian Stock Exchange
Capital Structure Determinants of Indonesian Plantation Firms: Empirical Study on Indonesian Stock Exchange Katherin Yolanda and Subiakto Soekarno Abstract This paper intends to analyze the influence of
More informationStat 328, Summer 2005
Stat 328, Summer 2005 Exam #2, 6/18/05 Name (print) UnivID I have neither given nor received any unauthorized aid in completing this exam. Signed Answer each question completely showing your work where
More informationThe Trend of the Gender Wage Gap Over the Business Cycle
Gettysburg Economic Review Volume 4 Article 5 2010 The Trend of the Gender Wage Gap Over the Business Cycle Nicholas J. Finio Gettysburg College Class of 2010 Follow this and additional works at: http://cupola.gettysburg.edu/ger
More informationAn Empirical Analysis of Effect on Copper Futures Yield. Based on GARCH
An Empirical Analysis of Effect on Copper Futures Yield Based on GARCH Feng Li 1, Ping Xiao 2 * 1 (School of Hunan University of Humanities, Science and Technology, Hunan 417000, China) 2 (School of Hunan
More information