Statistical Models of Stocks and Bonds. Zachary D Easterling: Department of Economics. The University of Akron

Size: px
Start display at page:

Download "Statistical Models of Stocks and Bonds. Zachary D Easterling: Department of Economics. The University of Akron"

Transcription

1 Statistical Models of Stocks and Bonds Zachary D Easterling: Department of Economics The University of Akron Abstract One of the key ideas in monetary economics is that the prices of investments tend to move in the opposite direction as interest rates. Is there a correlation between stocks, bonds and housing and do they move in the same direction? Can an economist predict the movement of one by looking at the aggregate of the others in relation to interest rates? Using Simple and Multiple Linear Regression, Chi- Square, One-Sample, and Two-Sample T-tests, this short work will focus on any positive or negative correlation between the Federal Funds Rate and investment media.

2 Simple Linear Regression: Using the Federal Reserve Federal Funds Rate to predict the yield to maturity on a One-Year Treasury Security. H 0 : The Federal Funds Rate is not a useful predictor of the One-Year Treasury Security yield. H a : The Federal Funds Rate is a useful predictor of the One-Year Treasury Security yield. Figure 1: MiniTab Output for Simple Linear Regression The regression equation is One Year Security = Federal Funds Rate Predictor Coef SE Coef T P Constant Fed Funds Rate S = R-Sq = 49.2% R-Sq(adj) = 48.9% MiniTab was used to predict the yield to maturity on a One-Year Treasury Security using the Federal Funds Rate; which is set daily by the Federal Reserve Bank. The output generated by MiniTab in conjunction with the hypotheses made in a simple linear regression leads me to accept the idea that the Federal Funds rate is indeed a useful predictor of the One-Year Treasury Security because of the incredibly small P-value indicated in the output. The R 2 values indicate however, that only 48.9% of the variability in the One Year Treasury is explained by the movement of the Federal Funds Rate. Unfortunately, the residual plot information for the Simple Linear Regression is somewhat suspect. While the Versus Fits scatter plot does indicate a random cloud of residuals, the Histogram does not resemble a clear Normal Analysis of Variance Curve. In this case the Histogram appears more right Source DF SS MS F P Regression skewed, and may therefore lead Residual Error to the questioning of the viability Total of this model as an overall useful predictor. And while the ANOVA information does lead to the conclusion that this model is useful 1 to make Treasury Bill Security rate predictions using the Federal Funds Rate, as indicated by the low P-value; the overall ability of the Federal Funds Rate to predict the One Year Treasury Security rate requires further study. H 0: The Model is not useful and contains no linear relation.

3 H a: The Model is useful and has linear relation.

4 Multiple Linear Regression: Using the Federal Funds Rate, Standard and Poor s 500, and the Average Selling Price of Housing in the United States to predict the yield to maturity on a One Year Treasury Security. H 0 : ß 1 : The Federal Funds Rate does not contribute to the model consisting of all other predictors. H 0 : ß 2 : The Standard and Poor s 500 does not contribute to the model consisting of all other predictors. H 0 : ß 3 : Average Selling Price of a US Home does not contribute to the model consisting of all other predictors. Figure 2: MiniTab Output for Multiple Linear Regression. The regression equation is Tbill_MnthlyPctChng = FFR_Pctchng SNP_PctChng_Monthly Housing_AvgPctChng Predictor Coef SE Coef T P Constant Fed Funds Rate S & P Avg. Selling Price S = R-Sq = 2.0% R-Sq(adj) = 0.4% MiniTab was next used to predict the monthly percentage change in the One Year Treasury Security using the percentage changes in the Federal Funds Rate, the Standard and Poor s 500, and the Average Selling Price (ASP) of a US Home. Output confirmed the previous simple linear regression; that there is indeed some relationship between the Federal Funds Rate and the One Year Treasury Security. In this regression the relatively low P-value for the Federal Funds Rate indicates that it does contribute to the model which includes the S&P 500 and the ASP of a US Home. However the exceptionally high P-values of both the S & P 500 and the ASP of a US Home indicate they do not contribute to the overall model. The coefficients for the slope of the lines of the S & P 500 and the ASP of a US Home are in direct conflict with the slope of the Federal Funds Rate. Analysis of Variance Source DF SS MS F P Regression Residual Error Total Residuals for the Multiple Linear Regression confirm (despite the one outlier in the Versus Fits scatter plot) that this model is not useful; ANOVA further solidifies this confirmation. The large P-value stemming from the ANOVA F-test indicates weak evidence against the model null hypothesis 1 ; implying that there is little to no linear relationship between the One Year Treasury Security and the combined variables: Federal Funds Rate, S & P 500, and ASP of a US Home.

5 Chi-Square Test: Comparing the proportions of increasing and decreasing months of the Federal Reserve Federal Funds Rate and the Standard and Poor s 500. H 0 : The direction of movement of the Federal Funds Rate has no association with the direction of movement in the Standard and Poor s 500. H a : The direction of movement of the Federal Funds Rate has an association with the direction of movement of the Standard and Poor s 500. Since the previous Multiple Linear Regression analysis indicated that there seemed to be no linear relationship between the One Year Treasury Security and both the S & P 500 and the ASP of a US Home; MiniTab was used to perform a Chi-Square test to determine whether or not there was any association between the movement (increasing or decreasing) of the Federal Funds Rate and the movement of the S & P 500. For the Federal Funds Rate, all the months that had a positive rate change were labeled as FFR Inc, and subsequently all months that had a negative rate change were labeled as FFR Dec. The same process was then applied to the S & P 500 to create categorical variables associated with a numerical change. The Chi-Squared Test led to the conclusion that there is no association between the movement of the Federal Funds Rate and the S & P 500. The P-value returned by the Chi-Square Test indicates very weak evidence against the null hypothesis, leading to its acceptance. Figure 4: MiniTab Output for two One Sample T-tests. Rows: S & P 500 Columns: Fed Funds Rate FFR Dec FFR Inc One Sample and Two Sample T-tests: Testing the movement of the average Federal Funds Rate. Since the Federal Funds Rate can be used to estimate the One Year Treasury Security, it is important to determine whether certain snippets of time have an average rate that is different from the overall Federal Funds Rate. If the mean Federal Funds Rate moves, then there would be periods where the return on One Year Treasury Securities would yield higher or lower returns as compared to the overall average. All SNP Dec SNP Inc All Cell Contents: One-Sample T 1990 s (January 1991 to December 1999) Test of mu = vs not = N Mean StDev SE Mean 95% CI T P (4.116, 5.518) One-Sample T 2000 s (January 2000 to December 2006) Test of mu = vs not = N Mean StDev SE Mean 95% CI T P (2.312, 4.101) Figure 3: MiniTab Output for Chi-Square Test. Count Expected count Pearson Chi-Square = 0.023, DF = 1, P-Value = Likelihood Ratio Chi-Square = 0.023, DF = 1, P-Value = 0.880

6 H 01 : The Federal Funds Rate of the 1990 s is no different than the overall Federal Funds Rate. H a1 : The Federal Funds Rate of the 1990 s is different from the overall Federal Funds Rate. H 02 : The Federal Funds Rate of the 2000 s is no different than the overall Federal Funds Rate. H a2 : The Federal Funds Rate of the 2000 s is different from the overall Federal Funds Rate. As the One Sample T-tests show, in both cases the sample means are different from the overall averages. The P-value of as returned by the 1990 s One Sample T-test indicates strong evidence against H 01. In this case the T-test confirms that the Federal Funds Rate in the 1990 s is not the same as the overall Federal Funds Rate from January 1991 to December In fact, with 95% certainty, the mean can be found somewhere between 4.116% and 5.518% as compared to the overall average of 4.112%. The second One Sample T-test indicates that as well, the mean Federal Funds Rate during January 2000 and December 2006 is not the same as the overall Federal Funds Rate. The P-value of is strong evidence against H 02 leading to the conclusion that this mean rate has also moved. Again, with 95% certainty, the mean can be found somewhere between 2.312% and 4.101%. Figure 5: MiniTab Output for a Two Sample T-test. Two-Sample T-Test and CI 1990 s vs 2000 s Sample N Mean StDev SE Mean Difference = mu (1) - mu (2) Estimate for difference: % CI for difference: (0.481, 2.740) T-Test of difference = 0 (vs not =): T-Value = 2.82 DF = 167 P-Value = Finally, since there was no overlapping confidence interval between the 1990 s and the 2000 s, a Two Sample T-test was run to determine if there was a difference in the two means. The test confirmed that yes there is a difference in the two means, as indicated by the small P- value. This is strong evidence against the null hypothesis, leading to a rejection of the null, and a conclusion that the means are indeed different. A 95% confidence interval puts the difference somewhere between 0.481% and 2.740%. H 0 : The mean Federal Funds Rate of the 1990 s is not different from the mean Federal Funds Rate in the 2000 s. H a : The mean Federal Funds Rate of the 1990 s is different from the mean Federal Funds Rate in the 2000 s.

7 Data Sources Bureau of Labor Statistics. Consumer Price Index - All Urban Consumers. US Department of Labor. tput_view=pct_1mth (10 November 2008). Federal Reserve Board of Governors. Monthly Federal Funds Rate. (1 December 2008). Federal Reserve Bank. One Year Government Securities by Month. (4 December 2008). Office of Federal Housing Enterprise Oversight. Housing Prices Indexes. (8 November 2008). The National Data Book. Banking, Finance, & Insurance: Money Stock, Interest Rates, Bond Yields. US Census Bureau. (10 November 2008). The Federal Reserve Board. H.15 Selected Interest Rates. Federal Reserve Bank e40f3f1f&filetype=csv&label=include&layout=seriescolumn&from=01/01/1990&to=12/31/2008 (10 November 2008). Yahoo! Finance. S&P 500 Historical Index. (16 November 2008).

Are the movements of stocks, bonds, and housing linked? Zachary D Easterling Department of Economics The University of Akron

Are the movements of stocks, bonds, and housing linked? Zachary D Easterling Department of Economics The University of Akron Easerling 1 Are the movements of stocks, bonds, and housing linked? Zachary D Easterling 1140324 Department of Economics The University of Akron One of the key ideas in monetary economics is that the prices

More information

Linear regression model

Linear regression model Regression Model Assumptions (Solutions) STAT-UB.0003: Regression and Forecasting Models Linear regression model 1. Here is the least squares regression fit to the Zagat restaurant data: 10 15 20 25 10

More information

CHAPTER 7 MULTIPLE REGRESSION

CHAPTER 7 MULTIPLE REGRESSION CHAPTER 7 MULTIPLE REGRESSION ANSWERS TO PROBLEMS AND CASES 5. Y = 7.5 + 3(0) - 1.(7) = -17.88 6. a. A correlation matrix displays the correlation coefficients between every possible pair of variables

More information

Rand Final Pop 2. Name: Class: Date: Multiple Choice Identify the choice that best completes the statement or answers the question.

Rand Final Pop 2. Name: Class: Date: Multiple Choice Identify the choice that best completes the statement or answers the question. Name: Class: Date: Rand Final Pop 2 Multiple Choice Identify the choice that best completes the statement or answers the question. Scenario 12-1 A high school guidance counselor wonders if it is possible

More information

Homework Assignment Section 3

Homework Assignment Section 3 Homework Assignment Section 3 Tengyuan Liang Business Statistics Booth School of Business Problem 1 A company sets different prices for a particular stereo system in eight different regions of the country.

More information

Homework Assignment Section 3

Homework Assignment Section 3 Homework Assignment Section 3 Tengyuan Liang Business Statistics Booth School of Business Problem 1 A company sets different prices for a particular stereo system in eight different regions of the country.

More information

Diploma Part 2. Quantitative Methods. Examiner s Suggested Answers

Diploma Part 2. Quantitative Methods. Examiner s Suggested Answers Diploma Part 2 Quantitative Methods Examiner s Suggested Answers Question 1 (a) The binomial distribution may be used in an experiment in which there are only two defined outcomes in any particular trial

More information

Stat 328, Summer 2005

Stat 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 information

Final Exam - section 1. Thursday, December hours, 30 minutes

Final Exam - section 1. Thursday, December hours, 30 minutes Econometrics, ECON312 San Francisco State University Michael Bar Fall 2013 Final Exam - section 1 Thursday, December 19 1 hours, 30 minutes Name: Instructions 1. This is closed book, closed notes exam.

More information

Estimating a demand function

Estimating a demand function Estimating a demand function One of the most basic topics in economics is the supply/demand curve. Simply put, the supply offered for sale of a commodity is directly related to its price, while the demand

More information

NEWCASTLE UNIVERSITY. School SEMESTER /2013 ACE2013. Statistics for Marketing and Management. Time allowed: 2 hours

NEWCASTLE UNIVERSITY. School SEMESTER /2013 ACE2013. Statistics for Marketing and Management. Time allowed: 2 hours NEWCASTLE UNIVERSITY School SEMESTER 2 2012/2013 Statistics for Marketing and Management Time allowed: 2 hours Candidates should attempt ALL questions. Marks for each question are indicated. However you

More information

GGraph. Males Only. Premium. Experience. GGraph. Gender. 1 0: R 2 Linear = : R 2 Linear = Page 1

GGraph. Males Only. Premium. Experience. GGraph. Gender. 1 0: R 2 Linear = : R 2 Linear = Page 1 GGraph 9 Gender : R Linear =.43 : R Linear =.769 8 7 6 5 4 3 5 5 Males Only GGraph Page R Linear =.43 R Loess 9 8 7 6 5 4 5 5 Explore Case Processing Summary Cases Valid Missing Total N Percent N Percent

More information

An approximate sampling distribution for the t-ratio. Caution: comparing population means when σ 1 σ 2.

An approximate sampling distribution for the t-ratio. Caution: comparing population means when σ 1 σ 2. Stat 529 (Winter 2011) Non-pooled t procedures (The Welch test) Reading: Section 4.3.2 The sampling distribution of Y 1 Y 2. An approximate sampling distribution for the t-ratio. The Sri Lankan analysis.

More information

STA2601. Tutorial letter 105/2/2018. Applied Statistics II. Semester 2. Department of Statistics STA2601/105/2/2018 TRIAL EXAMINATION PAPER

STA2601. Tutorial letter 105/2/2018. Applied Statistics II. Semester 2. Department of Statistics STA2601/105/2/2018 TRIAL EXAMINATION PAPER STA2601/105/2/2018 Tutorial letter 105/2/2018 Applied Statistics II STA2601 Semester 2 Department of Statistics TRIAL EXAMINATION PAPER Define tomorrow. university of south africa Dear Student Congratulations

More information

STAB22 section 2.2. Figure 1: Plot of deforestation vs. price

STAB22 section 2.2. Figure 1: Plot of deforestation vs. price STAB22 section 2.2 2.29 A change in price leads to a change in amount of deforestation, so price is explanatory and deforestation the response. There are no difficulties in producing a plot; mine is in

More information

Booth School of Business, University of Chicago Business 41202, Spring Quarter 2016, Mr. Ruey S. Tsay. Solutions to Midterm

Booth School of Business, University of Chicago Business 41202, Spring Quarter 2016, Mr. Ruey S. Tsay. Solutions to Midterm Booth School of Business, University of Chicago Business 41202, Spring Quarter 2016, Mr. Ruey S. Tsay Solutions to Midterm Problem A: (30 pts) Answer briefly the following questions. Each question has

More information

ST 350 Lecture Worksheet #33 Reiland

ST 350 Lecture Worksheet #33 Reiland ST 350 Lecture Worksheet #33 Reiland SOLUTIONS Name Lotteries: Good Idea or Scam? Lotteries have become important sources of revenue for many state governments. However, people have criticized lotteries

More information

Chapter 14. Descriptive Methods in Regression and Correlation. Copyright 2016, 2012, 2008 Pearson Education, Inc. Chapter 14, Slide 1

Chapter 14. Descriptive Methods in Regression and Correlation. Copyright 2016, 2012, 2008 Pearson Education, Inc. Chapter 14, Slide 1 Chapter 14 Descriptive Methods in Regression and Correlation Copyright 2016, 2012, 2008 Pearson Education, Inc. Chapter 14, Slide 1 Section 14.1 Linear Equations with One Independent Variable Copyright

More information

DATA SUMMARIZATION AND VISUALIZATION

DATA SUMMARIZATION AND VISUALIZATION APPENDIX DATA SUMMARIZATION AND VISUALIZATION PART 1 SUMMARIZATION 1: BUILDING BLOCKS OF DATA ANALYSIS 294 PART 2 PART 3 PART 4 VISUALIZATION: GRAPHS AND TABLES FOR SUMMARIZING AND ORGANIZING DATA 296

More information

Solutions for Session 5: Linear Models

Solutions for Session 5: Linear Models Solutions for Session 5: Linear Models 30/10/2018. do solution.do. global basedir http://personalpages.manchester.ac.uk/staff/mark.lunt. global datadir $basedir/stats/5_linearmodels1/data. use $datadir/anscombe.

More information

Subject CS1 Actuarial Statistics 1 Core Principles. Syllabus. for the 2019 exams. 1 June 2018

Subject CS1 Actuarial Statistics 1 Core Principles. Syllabus. for the 2019 exams. 1 June 2018 ` Subject CS1 Actuarial Statistics 1 Core Principles Syllabus for the 2019 exams 1 June 2018 Copyright in this Core Reading is the property of the Institute and Faculty of Actuaries who are the sole distributors.

More information

CHAPTER 6 DATA ANALYSIS AND INTERPRETATION

CHAPTER 6 DATA ANALYSIS AND INTERPRETATION 208 CHAPTER 6 DATA ANALYSIS AND INTERPRETATION Sr. No. Content Page No. 6.1 Introduction 212 6.2 Reliability and Normality of Data 212 6.3 Descriptive Analysis 213 6.4 Cross Tabulation 218 6.5 Chi Square

More information

General Business 706 Midterm #3 November 25, 1997

General Business 706 Midterm #3 November 25, 1997 General Business 706 Midterm #3 November 25, 1997 There are 9 questions on this exam for a total of 40 points. Please be sure to put your name and ID in the spaces provided below. Now, if you feel any

More information

Contents. An Overview of Statistical Applications CHAPTER 1. Contents (ix) Preface... (vii)

Contents. An Overview of Statistical Applications CHAPTER 1. Contents (ix) Preface... (vii) Contents (ix) Contents Preface... (vii) CHAPTER 1 An Overview of Statistical Applications 1.1 Introduction... 1 1. Probability Functions and Statistics... 1..1 Discrete versus Continuous Functions... 1..

More information

XLSTAT TIP SHEET FOR BUSINESS STATISTICS CENGAGE LEARNING

XLSTAT TIP SHEET FOR BUSINESS STATISTICS CENGAGE LEARNING XLSTAT TIP SHEET FOR BUSINESS STATISTICS CENGAGE LEARNING INTRODUCTION XLSTAT makes accessible to anyone a powerful, complete and user-friendly data analysis and statistical solution. Accessibility to

More information

Copyrighted 2007 FINANCIAL VARIABLES EFFECT ON THE U.S. GROSS PRIVATE DOMESTIC INVESTMENT (GPDI)

Copyrighted 2007 FINANCIAL VARIABLES EFFECT ON THE U.S. GROSS PRIVATE DOMESTIC INVESTMENT (GPDI) FINANCIAL VARIABLES EFFECT ON THE U.S. GROSS PRIVATE DOMESTIC INVESTMENT (GPDI) 1959-21 Byron E. Bell Department of Mathematics, Olive-Harvey College Chicago, Illinois, 6628, USA Abstract I studied what

More information

A Multi-perspective Assessment of Implied Volatility. Using S&P 100 and NASDAQ Index Options. The Leonard N. Stern School of Business

A Multi-perspective Assessment of Implied Volatility. Using S&P 100 and NASDAQ Index Options. The Leonard N. Stern School of Business A Multi-perspective Assessment of Implied Volatility Using S&P 100 and NASDAQ Index Options The Leonard N. Stern School of Business Glucksman Institute for Research in Securities Markets Faculty Advisor:

More information

Factors affecting the share price of FMCG Companies

Factors affecting the share price of FMCG Companies Factors affecting the share price of FMCG Companies Authors: Dharia Dilasha, Kakadia Sachita ABSTRACT To review the factors affecting the share prices of various FMCG companies like revenues, operating

More information

Quantitative Methods

Quantitative Methods THE ASSOCIATION OF BUSINESS EXECUTIVES DIPLOMA PART 2 QM Quantitative Methods afternoon 26 May 2004 1 Time allowed: 3 hours. 2 Answer any FOUR questions. 3 All questions carry 25 marks. Marks for subdivisions

More information

STATISTICS 110/201, FALL 2017 Homework #5 Solutions Assigned Mon, November 6, Due Wed, November 15

STATISTICS 110/201, FALL 2017 Homework #5 Solutions Assigned Mon, November 6, Due Wed, November 15 STATISTICS 110/201, FALL 2017 Homework #5 Solutions Assigned Mon, November 6, Due Wed, November 15 For this assignment use the Diamonds dataset in the Stat2Data library. The dataset is used in examples

More information

Analysis of Variance in Matrix form

Analysis of Variance in Matrix form Analysis of Variance in Matrix form The ANOVA table sums of squares, SSTO, SSR and SSE can all be expressed in matrix form as follows. week 9 Multiple Regression A multiple regression model is a model

More information

A STATISTICAL ANALYSIS OF GDP AND FINAL CONSUMPTION USING SIMPLE LINEAR REGRESSION. THE CASE OF ROMANIA

A STATISTICAL ANALYSIS OF GDP AND FINAL CONSUMPTION USING SIMPLE LINEAR REGRESSION. THE CASE OF ROMANIA A STATISTICAL ANALYSIS OF GDP AND FINAL CONSUMPTION USING SIMPLE LINEAR REGRESSION. THE CASE OF ROMANIA 990 200 Bălăcescu Aniela Lecturer PhD, Constantin Brancusi University of Targu Jiu, Faculty of Economics

More information

Optimal portfolio construction in markets with no risk-free asset available

Optimal portfolio construction in markets with no risk-free asset available Optimal portfolio construction in markets with no risk-free asset available Andreas Emmert Produced during the MSc in Finance studies at Strathclyde University in Glasgow/Scotland Portfolio Theory Optimal

More information

Point-Biserial and Biserial Correlations

Point-Biserial and Biserial Correlations Chapter 302 Point-Biserial and Biserial Correlations Introduction This procedure calculates estimates, confidence intervals, and hypothesis tests for both the point-biserial and the biserial correlations.

More information

Advanced Econometrics

Advanced Econometrics Advanced Econometrics Instructor: Takashi Yamano 11/14/2003 Due: 11/21/2003 Homework 5 (30 points) Sample Answers 1. (16 points) Read Example 13.4 and an AER paper by Meyer, Viscusi, and Durbin (1995).

More information

Stat 101 Exam 1 - Embers Important Formulas and Concepts 1

Stat 101 Exam 1 - Embers Important Formulas and Concepts 1 1 Chapter 1 1.1 Definitions Stat 101 Exam 1 - Embers Important Formulas and Concepts 1 1. Data Any collection of numbers, characters, images, or other items that provide information about something. 2.

More information

starting on 5/1/1953 up until 2/1/2017.

starting on 5/1/1953 up until 2/1/2017. An Actuary s Guide to Financial Applications: Examples with EViews By William Bourgeois An actuary is a business professional who uses statistics to determine and analyze risks for companies. In this guide,

More information

THE ECONOMICS OF BANK ROBBERIES IN NEW ENGLAND 1. Kimberly A. Leonard, Diane L. Marley & Charlotte A. Senno

THE ECONOMICS OF BANK ROBBERIES IN NEW ENGLAND 1. Kimberly A. Leonard, Diane L. Marley & Charlotte A. Senno THE ECONOMICS OF BANK ROBBERIES IN NEW ENGLAND 1 The Economics of Bank Robberies in New England Kimberly A. Leonard, Diane L. Marley & Charlotte A. Senno The University of Rhode Island, STA308 Comment

More information

Multiple Regression. Review of Regression with One Predictor

Multiple Regression. Review of Regression with One Predictor Fall Semester, 2001 Statistics 621 Lecture 4 Robert Stine 1 Preliminaries Multiple Regression Grading on this and other assignments Assignment will get placed in folder of first member of Learning Team.

More information

Impact of Unemployment and GDP on Inflation: Imperial study of Pakistan s Economy

Impact of Unemployment and GDP on Inflation: Imperial study of Pakistan s Economy International Journal of Current Research in Multidisciplinary (IJCRM) ISSN: 2456-0979 Vol. 2, No. 6, (July 17), pp. 01-10 Impact of Unemployment and GDP on Inflation: Imperial study of Pakistan s Economy

More information

Session 178 TS, Stats for Health Actuaries. Moderator: Ian G. Duncan, FSA, FCA, FCIA, FIA, MAAA. Presenter: Joan C. Barrett, FSA, MAAA

Session 178 TS, Stats for Health Actuaries. Moderator: Ian G. Duncan, FSA, FCA, FCIA, FIA, MAAA. Presenter: Joan C. Barrett, FSA, MAAA Session 178 TS, Stats for Health Actuaries Moderator: Ian G. Duncan, FSA, FCA, FCIA, FIA, MAAA Presenter: Joan C. Barrett, FSA, MAAA Session 178 Statistics for Health Actuaries October 14, 2015 Presented

More information

Fall 2004 Social Sciences 7418 University of Wisconsin-Madison Problem Set 5 Answers

Fall 2004 Social Sciences 7418 University of Wisconsin-Madison Problem Set 5 Answers Economics 310 Menzie D. Chinn Fall 2004 Social Sciences 7418 University of Wisconsin-Madison Problem Set 5 Answers This problem set is due in lecture on Wednesday, December 15th. No late problem sets will

More information

The data definition file provided by the authors is reproduced below: Obs: 1500 home sales in Stockton, CA from Oct 1, 1996 to Nov 30, 1998

The data definition file provided by the authors is reproduced below: Obs: 1500 home sales in Stockton, CA from Oct 1, 1996 to Nov 30, 1998 Economics 312 Sample Project Report Jeffrey Parker Introduction This project is based on Exercise 2.12 on page 81 of the Hill, Griffiths, and Lim text. It examines how the sale price of houses in Stockton,

More information

Business Statistics: A First Course

Business Statistics: A First Course Business Statistics: A First Course Fifth Edition Chapter 12 Correlation and Simple Linear Regression Business Statistics: A First Course, 5e 2009 Prentice-Hall, Inc. Chap 12-1 Learning Objectives In this

More information

Time series data: Part 2

Time series data: Part 2 Plot of Epsilon over Time -- Case 1 1 Time series data: Part Epsilon - 1 - - - -1 1 51 7 11 1 151 17 Time period Plot of Epsilon over Time -- Case Plot of Epsilon over Time -- Case 3 1 3 1 Epsilon - Epsilon

More information

Diploma in Business Administration Part 2. Quantitative Methods. Examiner s Suggested Answers

Diploma in Business Administration Part 2. Quantitative Methods. Examiner s Suggested Answers Cumulative frequency Diploma in Business Administration Part Quantitative Methods Examiner s Suggested Answers Question 1 Cumulative Frequency Curve 1 9 8 7 6 5 4 3 1 5 1 15 5 3 35 4 45 Weeks 1 (b) x f

More information

When determining but for sales in a commercial damages case,

When determining but for sales in a commercial damages case, JULY/AUGUST 2010 L I T I G A T I O N S U P P O R T Choosing a Sales Forecasting Model: A Trial and Error Process By Mark G. Filler, CPA/ABV, CBA, AM, CVA When determining but for sales in a commercial

More information

WEB APPENDIX 8A 7.1 ( 8.9)

WEB APPENDIX 8A 7.1 ( 8.9) WEB APPENDIX 8A CALCULATING BETA COEFFICIENTS The CAPM is an ex ante model, which means that all of the variables represent before-the-fact expected values. In particular, the beta coefficient used in

More information

Technical Documentation for Household Demographics Projection

Technical Documentation for Household Demographics Projection Technical Documentation for Household Demographics Projection REMI Household Forecast is a tool to complement the PI+ demographic model by providing comprehensive forecasts of a variety of household characteristics.

More information

Random Effects... and more about pigs G G G G G G G G G G G

Random Effects... and more about pigs G G G G G G G G G G G et s examine the random effects model in terms of the pig weight example. This had eight litters, and in the first analysis we were willing to think of as fixed effects. This means that we might want to

More information

Statistics & Statistical Tests: Assumptions & Conclusions

Statistics & Statistical Tests: Assumptions & Conclusions Degrees of Freedom Statistics & Statistical Tests: Assumptions & Conclusions Kinds of degrees of freedom Kinds of Distributions Kinds of Statistics & assumptions required to perform each Normal Distributions

More information

Central University of Punjab, Bathinda

Central University of Punjab, Bathinda P a g e 1 Central University of Punjab, Bathinda Course Scheme & Syllabus for University Statistics P a g e 1 Sr. No. Course Code 1 TBA1 2 TBA2 3 TBA3 Course Title Basic Statistics (Sciences) Basic Statistics

More information

Chapter 11: Inference for Distributions Inference for Means of a Population 11.2 Comparing Two Means

Chapter 11: Inference for Distributions Inference for Means of a Population 11.2 Comparing Two Means Chapter 11: Inference for Distributions 11.1 Inference for Means of a Population 11.2 Comparing Two Means 1 Population Standard Deviation In the previous chapter, we computed confidence intervals and performed

More information

12.1 One-Way Analysis of Variance. ANOVA - analysis of variance - used to compare the means of several populations.

12.1 One-Way Analysis of Variance. ANOVA - analysis of variance - used to compare the means of several populations. 12.1 One-Way Analysis of Variance ANOVA - analysis of variance - used to compare the means of several populations. Assumptions for One-Way ANOVA: 1. Independent samples are taken using a randomized design.

More information

GETTING STARTED. To OPEN MINITAB: Click Start>Programs>Minitab14>Minitab14 or Click Minitab 14 on your Desktop

GETTING STARTED. To OPEN MINITAB: Click Start>Programs>Minitab14>Minitab14 or Click Minitab 14 on your Desktop Minitab 14 1 GETTING STARTED To OPEN MINITAB: Click Start>Programs>Minitab14>Minitab14 or Click Minitab 14 on your Desktop The Minitab session will come up like this 2 To SAVE FILE 1. Click File>Save Project

More information

Booth 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 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 information

Two-Sample T-Test for Non-Inferiority

Two-Sample T-Test for Non-Inferiority Chapter 198 Two-Sample T-Test for Non-Inferiority Introduction This procedure provides reports for making inference about the non-inferiority of a treatment mean compared to a control mean from data taken

More information

Econometric Methods for Valuation Analysis

Econometric Methods for Valuation Analysis Econometric Methods for Valuation Analysis Margarita Genius Dept of Economics M. Genius (Univ. of Crete) Econometric Methods for Valuation Analysis Cagliari, 2017 1 / 26 Correlation Analysis Simple Regression

More information

Cumulative Abnormal Returns

Cumulative Abnormal Returns Cumulative Abnormal Returns 0.800000 DAY - 20 T0 +186 0.600000 CUMULATIVE ABNORMAL RETURNS 0.400000 0.200000 0.000000-0.200000-0.400000-0.600000-0.800000 3 5 13 16 7 15 17 23 12-20 -10 0 10 20 30 40 50

More information

MATH 143: Introduction to Probability and Statistics Worksheet 9 for Thurs., Dec. 10: What procedure?

MATH 143: Introduction to Probability and Statistics Worksheet 9 for Thurs., Dec. 10: What procedure? MATH 143: Introduction to Probability and Statistics Worksheet 9 for Thurs., Dec. 10: What procedure? For each numbered problem, identify (if possible) the following: (a) the variable(s) and variable type(s)

More information

Cameron ECON 132 (Health Economics): FIRST MIDTERM EXAM (A) Fall 17

Cameron ECON 132 (Health Economics): FIRST MIDTERM EXAM (A) Fall 17 Cameron ECON 132 (Health Economics): FIRST MIDTERM EXAM (A) Fall 17 Answer all questions in the space provided on the exam. Total of 36 points (and worth 22.5% of final grade). Read each question carefully,

More information

The relationship between GDP, labor force and health expenditure in European countries

The relationship between GDP, labor force and health expenditure in European countries Econometrics-Term paper The relationship between GDP, labor force and health expenditure in European countries Student: Nguyen Thu Ha Contents 1. Background:... 2 2. Discussion:... 2 3. Regression equation

More information

MATH 143: Introduction to Probability and Statistics Worksheet for Tues., Dec. 7: What procedure?

MATH 143: Introduction to Probability and Statistics Worksheet for Tues., Dec. 7: What procedure? MATH 143: Introduction to Probability and Statistics Worksheet for Tues., Dec. 7: What procedure? For each numbered problem, identify (if possible) the following: (a) the variable(s) and variable type(s)

More information

Copyright 2011 Pearson Education, Inc. Publishing as Addison-Wesley.

Copyright 2011 Pearson Education, Inc. Publishing as Addison-Wesley. Appendix: Statistics in Action Part I Financial Time Series 1. These data show the effects of stock splits. If you investigate further, you ll find that most of these splits (such as in May 1970) are 3-for-1

More information

CHAPTER 4 DATA ANALYSIS Data Hypothesis

CHAPTER 4 DATA ANALYSIS Data Hypothesis CHAPTER 4 DATA ANALYSIS 4.1. Data Hypothesis The hypothesis for each independent variable to express our expectations about the characteristic of each independent variable and the pay back performance

More information

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Sample Exam 3 MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Question 1-7: The managers of a brokerage firm are interested in finding out if the

More information

Quantitative Techniques Term 2

Quantitative Techniques Term 2 Quantitative Techniques Term 2 Laboratory 7 2 March 2006 Overview The objective of this lab is to: Estimate a cost function for a panel of firms; Calculate returns to scale; Introduce the command cluster

More information

Chapter 18: The Correlational Procedures

Chapter 18: The Correlational Procedures Introduction: In this chapter we are going to tackle about two kinds of relationship, positive relationship and negative relationship. Positive Relationship Let's say we have two values, votes and campaign

More information

Chapter 11 Part 6. Correlation Continued. LOWESS Regression

Chapter 11 Part 6. Correlation Continued. LOWESS Regression Chapter 11 Part 6 Correlation Continued LOWESS Regression February 17, 2009 Goal: To review the properties of the correlation coefficient. To introduce you to the various tools that can be used to decide

More information

Influence of Personal Factors on Health Insurance Purchase Decision

Influence of Personal Factors on Health Insurance Purchase Decision Influence of Personal Factors on Health Insurance Purchase Decision INFLUENCE OF PERSONAL FACTORS ON HEALTH INSURANCE PURCHASE DECISION The decision in health insurance purchase include decisions about

More information

Presented at the 2003 SCEA-ISPA Joint Annual Conference and Training Workshop -

Presented at the 2003 SCEA-ISPA Joint Annual Conference and Training Workshop - Predicting Final CPI Estimating the EAC based on current performance has traditionally been a point estimate or, at best, a range based on different EAC calculations (CPI, SPI, CPI*SPI, etc.). NAVAIR is

More information

Two-Sample T-Test for Superiority by a Margin

Two-Sample T-Test for Superiority by a Margin Chapter 219 Two-Sample T-Test for Superiority by a Margin Introduction This procedure provides reports for making inference about the superiority of a treatment mean compared to a control mean from data

More information

Web 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 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 information

Econ 3790: Business and Economics Statistics. Instructor: Yogesh Uppal

Econ 3790: Business and Economics Statistics. Instructor: Yogesh Uppal Econ 3790: Business and Economics Statistics Instructor: Yogesh Uppal Email: yuppal@ysu.edu Chapter 12 Goodness of Fit Test: A Multinomial Population Test of Independence Hypothesis (Goodness of Fit) Test

More information

Assignment #5 Solutions: Chapter 14 Q1.

Assignment #5 Solutions: Chapter 14 Q1. Assignment #5 Solutions: Chapter 14 Q1. a. R 2 is.037 and the adjusted R 2 is.033. The adjusted R 2 value becomes particularly important when there are many independent variables in a multiple regression

More information

Study 2: data analysis. Example analysis using R

Study 2: data analysis. Example analysis using R Study 2: data analysis Example analysis using R Steps for data analysis Install software on your computer or locate computer with software (e.g., R, systat, SPSS) Prepare data for analysis Subjects (rows)

More information

1) The Effect of Recent Tax Changes on Taxable Income

1) The Effect of Recent Tax Changes on Taxable Income 1) The Effect of Recent Tax Changes on Taxable Income In the most recent issue of the Journal of Policy Analysis and Management, Bradley Heim published a paper called The Effect of Recent Tax Changes on

More information

7. For the table that follows, answer the following questions: x y 1-1/4 2-1/2 3-3/4 4

7. For the table that follows, answer the following questions: x y 1-1/4 2-1/2 3-3/4 4 7. For the table that follows, answer the following questions: x y 1-1/4 2-1/2 3-3/4 4 - Would the correlation between x and y in the table above be positive or negative? The correlation is negative. -

More information

Assignment 3-Solutions

Assignment 3-Solutions Assignment 3-Solutions Question 1. - Joint Probability Mass Function Consider the function x y 1.0 1.0 1.5 2.0 1.5 3.0 2.5 4.0 3.0 4.0 Determine the following: (a) Show that If is a valid probability mass

More information

Correlation between Inflation Rates and Currency Values

Correlation between Inflation Rates and Currency Values Parkland College A with Honors Projects Honors Program 2015 Correlation between Inflation Rates and Currency Values Valeria Rohde Parkland College Recommended Citation Rohde, Valeria, "Correlation between

More information

Data screening, transformations: MRC05

Data screening, transformations: MRC05 Dale Berger Data screening, transformations: MRC05 This is a demonstration of data screening and transformations for a regression analysis. Our interest is in predicting current salary from education level

More information

U.S./U.K. Exchange Rate: A Statistical Analysis

U.S./U.K. Exchange Rate: A Statistical Analysis U.S./U.K. Exchange Rate: A Statistical Analysis Gabriel Di Capua Fabio Rabinovich Lorenzo Salazar Peter Van Noppen B a b s o n C o l l e g e F i n a n c i a l M a r k e t s a n d I n s t r u m e n t s

More information

Contents Part I Descriptive Statistics 1 Introduction and Framework Population, Sample, and Observations Variables Quali

Contents Part I Descriptive Statistics 1 Introduction and Framework Population, Sample, and Observations Variables Quali Part I Descriptive Statistics 1 Introduction and Framework... 3 1.1 Population, Sample, and Observations... 3 1.2 Variables.... 4 1.2.1 Qualitative and Quantitative Variables.... 5 1.2.2 Discrete and Continuous

More information

Topic 8: Model Diagnostics

Topic 8: Model Diagnostics Topic 8: Model Diagnostics Outline Diagnostics to check model assumptions Diagnostics concerning X Diagnostics using the residuals Diagnostics and remedial measures Diagnostics: look at the data to diagnose

More information

11/28/2018. Overview. Multiple Linear Regression Analysis. Multiple regression. Multiple regression. Multiple regression. Multiple regression

11/28/2018. 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 information

Final Exam Suggested Solutions

Final Exam Suggested Solutions University of Washington Fall 003 Department of Economics Eric Zivot Economics 483 Final Exam Suggested Solutions This is a closed book and closed note exam. However, you are allowed one page of handwritten

More information

Study Ch. 11.2, #51, 63 69, 73

Study Ch. 11.2, #51, 63 69, 73 May 05, 014 11. Inferences for σ's, Populations Study Ch. 11., #51, 63 69, 73 Statistics Home Page Gertrude Battaly, 014 11. Inferences for σ's, Populations Procedures that assume = σ's 1. Pooled t test.

More information

The University of Chicago, Booth School of Business Business 41202, Spring Quarter 2009, Mr. Ruey S. Tsay. Solutions to Final Exam

The University of Chicago, Booth School of Business Business 41202, Spring Quarter 2009, Mr. Ruey S. Tsay. Solutions to Final Exam The University of Chicago, Booth School of Business Business 41202, Spring Quarter 2009, Mr. Ruey S. Tsay Solutions to Final Exam Problem A: (42 pts) Answer briefly the following questions. 1. Questions

More information

Analysis of the Influence of the Annualized Rate of Rentability on the Unit Value of the Net Assets of the Private Administered Pension Fund NN

Analysis of the Influence of the Annualized Rate of Rentability on the Unit Value of the Net Assets of the Private Administered Pension Fund NN Year XVIII No. 20/2018 175 Analysis of the Influence of the Annualized Rate of Rentability on the Unit Value of the Net Assets of the Private Administered Pension Fund NN Constantin DURAC 1 1 University

More information

Washington University Fall Economics 487. Project Proposal due Monday 10/22 Final Project due Monday 12/3

Washington University Fall Economics 487. Project Proposal due Monday 10/22 Final Project due Monday 12/3 Washington University Fall 2001 Department of Economics James Morley Economics 487 Project Proposal due Monday 10/22 Final Project due Monday 12/3 For this project, you will analyze the behaviour of 10

More information

Econ 371 Problem Set #4 Answer Sheet. 6.2 This question asks you to use the results from column (1) in the table on page 213.

Econ 371 Problem Set #4 Answer Sheet. 6.2 This question asks you to use the results from column (1) in the table on page 213. Econ 371 Problem Set #4 Answer Sheet 6.2 This question asks you to use the results from column (1) in the table on page 213. a. The first part of this question asks whether workers with college degrees

More information

MEMORANDUM. TO: Me FROM: Me RE: Memo containing output for SPSS practice exam #2

MEMORANDUM. TO: Me FROM: Me RE: Memo containing output for SPSS practice exam #2 MEMORADUM DATE: ovember 5, 2024 TO: Me FROM: Me RE: Memo containing output for SPSS practice exam #2 Task 3a. Below is bar graph of the number of cases for the variable beltfrnt. 40 30 20 10 0 o Seat Belt

More information

sociology SO5032 Quantitative Research Methods Brendan Halpin, Sociology, University of Limerick Spring 2018 SO5032 Quantitative Research Methods

sociology SO5032 Quantitative Research Methods Brendan Halpin, Sociology, University of Limerick Spring 2018 SO5032 Quantitative Research Methods 1 SO5032 Quantitative Research Methods Brendan Halpin, Sociology, University of Limerick Spring 2018 Lecture 10: Multinomial regression baseline category extension of binary What if we have multiple possible

More information

Determinants of FII Inflows:India

Determinants of FII Inflows:India MPRA Munich Personal RePEc Archive Determinants of FII Inflows:India Ravi Saraogi February 2008 Online at https://mpra.ub.uni-muenchen.de/22850/ MPRA Paper No. 22850, posted 22. May 2010 23:04 UTC Determinants

More information

3. The distinction between variable costs and fixed costs is:

3. The distinction between variable costs and fixed costs is: Practice Exam # 2 Dr. Bailey ACCT3310, Spring 2014, Chapters 4, 5, & 6 There are 25 questions, each worth 4 points. Please see my earlier advice on the appropriate use of this exam. Its purpose is to give

More information

The Gutenberg Approach to Financial Modeling & Equity Valuation

The Gutenberg Approach to Financial Modeling & Equity Valuation Introduction to Financial Modeling 1-1 The Gutenberg Approach to Financial Modeling & Equity Valuation Demonstration Video Series Chapter 1: Introduction to Financial Modeling Chapter 2: DCF Inputs (ERP,

More information

Topic 30: Random Effects Modeling

Topic 30: Random Effects Modeling Topic 30: Random Effects Modeling Outline One-way random effects model Data Model Inference Data for one-way random effects model Y, the response variable Factor with levels i = 1 to r Y ij is the j th

More information

$0.00 $0.50 $1.00 $1.50 $2.00 $2.50 $3.00 $3.50 $4.00 Price

$0.00 $0.50 $1.00 $1.50 $2.00 $2.50 $3.00 $3.50 $4.00 Price Orange Juice Sales and Prices In this module, you will be looking at sales and price data for orange juice in grocery stores. You have data from 83 stores on three brands (Tropicana, Minute Maid, and the

More information

CAN AGENCY COSTS OF DEBT BE REDUCED WITHOUT EXPLICIT PROTECTIVE COVENANTS? THE CASE OF RESTRICTION ON THE SALE AND LEASE-BACK ARRANGEMENT

CAN AGENCY COSTS OF DEBT BE REDUCED WITHOUT EXPLICIT PROTECTIVE COVENANTS? THE CASE OF RESTRICTION ON THE SALE AND LEASE-BACK ARRANGEMENT CAN AGENCY COSTS OF DEBT BE REDUCED WITHOUT EXPLICIT PROTECTIVE COVENANTS? THE CASE OF RESTRICTION ON THE SALE AND LEASE-BACK ARRANGEMENT Jung, Minje University of Central Oklahoma mjung@ucok.edu Ellis,

More information

Risk-Adjusted Futures and Intermeeting Moves

Risk-Adjusted Futures and Intermeeting Moves issn 1936-5330 Risk-Adjusted Futures and Intermeeting Moves Brent Bundick Federal Reserve Bank of Kansas City First Version: October 2007 This Version: June 2008 RWP 07-08 Abstract Piazzesi and Swanson

More information