Forecasting the US Dollar/Euro Exchange Rate Group B John Hottinger Jingyu Nie Katharina Denk Alex Brown Joel Demartini Yuanchen Wang Doug Skipper-Dotta.

Slides:

Advertisements

Similar presentations

DSCI 5340: Predictive Modeling and Business Forecasting Spring 2013 – Dr. Nick Evangelopoulos Exam 1 review: Quizzes 1-6.

Advertisements

Analysis of Sales of Food Services & Drinking Places Julianne Shan Ho-Jung Hsiao Christian Treubig Lindsey Aspel Brooks Allen Edmund Becdach.

Forecasting CPI Xiang Huang, Wenjie Huang, Teng Wang, Hong Wang Benjamin Wright, Naiwen Chang, Jake Stamper.

Time Series Building 1. Model Identification

Credit Costs TODAY YOU WILL... EXAMINE THE COSTS OF CREDIT. 1 ©2014 National Endowment for Financial Education | Lesson 2-2: Credit Costs.

How should these data be modelled?. Identification step: Look at the SAC and SPAC Looks like an AR(1)- process. (Spikes are clearly decreasing in SAC.

Business Forecasting Chapter 10 The Box–Jenkins Method of Forecasting.

Tutorial for solution of Assignment week 40 “Forecasting monthly values of Consumer Price Index Data set: Swedish Consumer Price Index” sparetime.

Take Home II: US Residential Natural Gas Price Analysis and 2011 Forecast Group E Lars Hult Eric Johnson Matthew Koson Trung Le Joon Hee Lee Aygul Nagaeva.

Price of Gold and US Dollar Index Dwarakamayi Polakam Jennifer Griffeth Ashley Arlotti Rui Feng Ying Fan Qi He Qi Li Group C Presentation.

1 Power Nine Econ 240C. 2 Outline Lab Three Exercises Lab Three Exercises –Fit a linear trend to retail and food sales –Add a quadratic term –Use both.

The effect of 9/11 on the airline industry ECON 240C – Project 2 Hao Jin ChingChi Huang Bryan Watson Vineet Sharma Hilde Hesjedal.

United States Imports Michael Williams Kevin Crider Andreas Lindal Jim Huang Juan Shan.

Global Warming: Is It True? Peter Fuller Odeliah Greene Amanda Smith May Zin.

1 Takehome One month treasury bill rate.

1 Lecture Eleven Econ 240C. 2 Outline Review Stochastic Time Series –White noise –Random walk –ARONE: –ARTWO –ARTHREE –ARMA(2,2) –MAONE*SMATWELVE.

Econ 240C Lecture Review 2002 Final Ideas that are transcending p. 15 Economic Models of Time Series Symbolic Summary.

Revenue Passenger Miles (RPM) Brandon Briggs, Theodore Ehlert, Mats Olson, David Sheehan, Alan Weinberg.

1 Identifying ARIMA Models What you need to know.

Data Sources The most sophisticated forecasting model will fail if it is applied to unreliable data Data should be reliable and accurate Data should be.

1 Power Nine Econ 240C. 2 Outline Lab Three Exercises Lab Three Exercises –Fit a linear trend to retail and food sales –Add a quadratic term –Use both.

1 Power Nine Econ 240C. 2 Outline Lab Three Exercises Lab Three Exercises –Fit a linear trend to retail and food sales –Add a quadratic term –Use both.

Assignment 2: Problem 1 Given the following data Forecast for Sep Using linear regression Using 5 period moving average Using exponential smoothing. Alpha.

Exchange Rate YuYuan Liu Han Yu Yang Dennis Yue Jessica Chen Jo-Yu Mao.

1 Takehome One Excaus:Price of US $ in Canadian $

1 Arch-Garch Lab Nine. 2 Producer Price Index for Finished Goods, 1982 =100, –

1 Term Structure of Interest Rates Project One 2007.

C HAPTER 13 EXCHANGE RATES AND THE FOREIGN EXCHANGE MARKET: AN ASSET APPROACH.

Global Analysts Eirik Skeid, Anders Graham, Bradley Moore, Matthew Scott Tor Seim, Steven Comstock.

Will There Be Jobs For All of Us Financial Econometricians? Ben Kallo Ben Kallo James Katavolos James Katavolos Luke Panzar Luke Panzar Ryan Carl Ryan.

Personal Savings as a Percentage of Disposable Personal Income Take Home II June 4 th, 2009 June 4 th, 2009 Marissa Pittman Morgan Hansen Eric Griffin.

Economists use Consumer Price Index [CPI] to estimate real wages and costs from nominal wages and costs.

Project Average Weekly Hours, Manufacturing.

1 ECON 240C Lecture 8. 2 Outline: 2 nd Order AR Roots of the quadratic Roots of the quadratic Example: change in housing starts Example: change in housing.

ARIMA Forecasting Lecture 7 and 8 - March 14-16, 2011

Economics 20 - Prof. Anderson

Riskless Interest in the Foreign Exchange Market Presented by Gregory Adams Samantha Gardner Brett Hanifin Ali Irktur Ryan Nabinger Xiaoyin Zhong.

Part II – TIME SERIES ANALYSIS C2 Simple Time Series Methods & Moving Averages © Angel A. Juan & Carles Serrat - UPC 2007/2008.

Forecasting World Wide Pandemics Using Google Flu Data to Forecast the Flu Brian Abe Dan Helling Eric Howard Ting Zheng Laura Braeutigam Noelle Hirneise.

1 Lab Four Postscript Econ 240 C. 2 Airline Passengers.

1 Power Nine Econ 240C. 2 Outline Lab Three Exercises Lab Three Exercises –Fit a linear trend to retail sales –Add a quadratic term –Use both models to.

He Loves Me, He Loves Me Not A Forecast of U.S. Jewelry Sales Alex Gates Ling-Ching Hsu Shih-Hao Lee Hui Liang Mateusz Tracz Grant Volk June 1, 2010.

Matt Mullens Gulsah Gunenc Alex Keyfes Gaoyuan Tian Andrew Booth.

Excel Data Analysis Tools Descriptive Statistics – Data ribbon – Analysis section – Data Analysis icon – Descriptive Statistics option – Does NOT auto.

Exchange Rates. Foreign Exchange Market Currencies are bought and sold on a foreign exchange market. The demand for a currency is a function of three.

BOX JENKINS METHODOLOGY

ADJUSTED EXPONENTIAL SMOOTHING FORECASTING METHOD Prepared by Dan Milewski November 29, 2005.

Foreign exchange risk, hedging, Speculation

Slides By John Dawson and Kevin Brady Begin Exchange Rates Interactive Examples Material from this presentation can be found in: Chapter 26 To navigate,

1 of 49 module: 43 >> Krugman/Wells ©2009  Worth Publishers Exchange Rates and Macroeconomic Policy.

Applications of Exponential Functions. Objectives To solve real-life application problems using the properties of exponents and exponential functions.

COMP 211 REQUIREMENTS CAPTURE 1 ASU Course Registration Acceptance Test Plan (Inception Phase)

Tutorial for solution of Assignment week 39 “A. Time series without seasonal variation Use the data in the file 'dollar.txt'. “

CONSUMER ARITHMETIC PROBLEMS. Check and discuss students’ homework on compound interest STARTER.

Assignment 2 Given the following data (a)Plot the data (b)Forecast for Sep. using linear regression (c)Forecast for Sep. using 5 period moving average.

1 Given the following data, calculate forecasts for months April through June using a three- month moving average and an exponential smoothing forecast.

Big Data at Home Depot KSU – Big Data Survey Course Steve Einbender Advanced Analytics Architect.

General Information OPEC Currency The 1973 Oil Crisis

Adding and Subtracting Money! Click on the dollar sign to begin!

Name of the War you are researching Name:. Who was the war with? The ____was with _____ Add a picture of the countries who were fighting in the war.

The Box-Jenkins (ARIMA) Methodology

The Traveling M&M’s Unit Prices and Exchange Rates.

Copyright 2011 John Wiley & Sons, Inc. 1 Chapter 11 Time Series and Business Forecasting 11.1 Time Series Data 11.2 Simple Moving Average Model 11.3 Weighted.

Exchange Rates: If you go abroad on holiday and the country you are visiting uses a different currency from the Pound in the UK, then you will have to.

FIN 370 Week 5 DQ 2 What is meant by foreign exchange risk? What specific problems does foreign exchange present in an organization? How could an organization.

Energy Consumption Forecast Using JMP® Pro 11 Time Series Analysis

Econ 240C Lecture 18.

DRQ #12 – November 15, 2011 DRQ12 is worth 5 pts

Forecasting - Introduction

BOX JENKINS (ARIMA) METHODOLOGY

Presentation transcript:

Forecasting the US Dollar/Euro Exchange Rate Group B John Hottinger Jingyu Nie Katharina Denk Alex Brown Joel Demartini Yuanchen Wang Doug Skipper-Dotta

Exchange Rates What are they? What are they? We will be focusing on the U.S. Dollar vs Euro Exchange Rate We will be focusing on the U.S. Dollar vs Euro Exchange Rate An exchange rate is how much one currency is worth compared to another currency An exchange rate is how much one currency is worth compared to another currency Current U.S./Euro i.e. it take $1.43 to buy one Euro Current U.S./Euro i.e. it take $1.43 to buy one Euro

Goal We want to forecast what the exchange rate up to 6 months in the future We want to forecast what the exchange rate up to 6 months in the future

A look at our data We gathered monthly exchange rate data from from May 2000 to May We gathered monthly exchange rate data from from May 2000 to May 2011.

A Trace of the Data

Things to note Substantial drop for the U.S dollar compared to the Euro from 2002 to 2008 Substantial drop for the U.S dollar compared to the Euro from 2002 to 2008 Reasons: September 11, The war in Iraq and Afghanistan, the housing bubble and the U.S. accumulation of massive debt. Reasons: September 11, The war in Iraq and Afghanistan, the housing bubble and the U.S. accumulation of massive debt.

The Histogram

The Correllogram

Unit Root test

What does this all mean The trace is evolutionary The trace is evolutionary In order to forecast or to have a meaningful forecast we need to make the data stationary In order to forecast or to have a meaningful forecast we need to make the data stationary We were able to make the data stationary by using the box jenkins method We were able to make the data stationary by using the box jenkins method

Step 1: First differencing

Whitened Histogram

The Whitened Correllogram

Whitened Unit Root Test

Alternate Models

Building our Final Model We decided to use an intervention model due to the drastic drop in the exchange rate in 2002 We decided to use an intervention model due to the drastic drop in the exchange rate in 2002

The Step Function Normal and First Differenced

We begin to make our final model

Actual Fitted Residual and histogram

Serial Correlation Test and Correllogram

Looking for Heteroskidasticity

Adding a MA(23)

The Correllogram

Add an MA(26)

Actual Fitted Residual and Histogram of Residuals

Correllogram of residuals and Serial Correlation Test

Time to forecast 6 month whitened forecast 6 month whitened forecast

Forecasted Values

Forecasting 6 Months Previous

Forecasted Values for Previous 6 Months

Re-colored Forecast for Following 6 Months

Re-Colored Forecast for Previous 6 Months

Just because We decided to forecast using exponential smoothing and see how are model would look We decided to forecast using exponential smoothing and see how are model would look

Results Exponential Model is very close to what our final model determined Exponential Model is very close to what our final model determined We will have to wait and see if our forecasts are correct We will have to wait and see if our forecasts are correct

Thank you!!