The exchange rate on a daily basis is an indispensable factor in the foreign exchange market as well as in international trade. Many traders make a profit based on the pip in the foreign exchange market. Moreover, inflation and deflation of a currency against another currency is the root of making a profit in the foreign exchange market. Even in the international trade many individual traders and multi-national corporations always carefully observes the fluctuation of the exchange rate in order to determine the exchange rate efficiently and accurately.
Because the more accurate the forecasted exchange rate is, the higher the chance becomes to make a profit only by investing a little amount of money in the foreign exchange market. The exchange rate has also significant impact on the export, import, foreign direct investment etc.
This paper pursues the goal to explain how an individual or an organization can formulate future exchange rate of any currency in an efficient and time effective way. To meet this demand, this paper utilizes the help of panel data and a regression model. As a sample, this paper considers USD/BDT for a forecast. It must be noted that, with different panel data of different currencies, the method will remain same if anyone wants to forecast exchange rates of different currencies.
Inhaltsverzeichnis (Table of Contents)
- 1. INTRODUCTION
- 2. METHODOLOGY
- 2.1. Identifying Variables:
- 2.1.1. Dependent Variable:
- 2.1.2. Independent Variables:
- 2.2. Model:
- 2.3. Data and Sample:
- 2.4. Scope of the Study:
- 2.1. Identifying Variables:
- 3. FINDINGS AND ANALYSIS
- 3.1. Regression Analysis:
- 4. FORECASTING EXCHANGE RATE
- 4.1. Regression equation:
- 4.2. Forecasting exchange rate for August 2015:
- 4.3. Comparison between Forecasted exchange rate and Actual exchange rate:
- 5. CONCLUSION
Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)
The main objective of this paper is to demonstrate an efficient and time-effective method for forecasting exchange rates, specifically focusing on the USD/BDT pair. It aims to achieve this by utilizing panel data and a regression model. The methodology is presented in a way that can be adapted to forecast other currency pairs.
- Exchange rate forecasting using panel data.
- Development and application of a regression model for exchange rate prediction.
- Analysis of the relationship between exchange rates and macroeconomic variables.
- Assessment of the accuracy of the forecasting model.
- Practical application of econometric techniques for financial forecasting.
Zusammenfassung der Kapitel (Chapter Summaries)
1. INTRODUCTION: This chapter introduces the significance of exchange rate forecasting in international trade and finance. It highlights the importance of accurate exchange rate predictions for profitable trading and investment decisions. The chapter sets the stage by explaining the complexities of exchange rates (direct, indirect, and cross rates), and establishes the paper's focus on forecasting the USD/BDT exchange rate using a regression model based on panel data.
2. METHODOLOGY: This chapter details the methodology employed in the study. It outlines the identification of key variables, including the dependent variable (change in USD/BDT) and independent variables (changes in inflation rate, bank interest rate, per capita income, and GDP growth rate). The chapter explains the construction of the OLS regression model used for forecasting and provides details on the data selection process (10 years of monthly data from 2005-2015). The scope of the study and its limitations are also clearly defined, such as the data range used and the selection of specific independent variables. The chapter thoroughly lays out the statistical approach that underpins the forecasting model.
3. FINDINGS AND ANALYSIS: This chapter presents the results of the regression analysis. While specific findings aren't provided in the excerpt, it's anticipated this section would detail the statistical significance of the independent variables, the R-squared value reflecting the model's explanatory power, and potentially diagnostic tests assessing the model's validity and the goodness of fit. Detailed output from the regression analysis would be presented and discussed to support the findings and their interpretation.
4. FORECASTING EXCHANGE RATE: This chapter applies the developed regression model to forecast the USD/BDT exchange rate for August 2015. It demonstrates the practical application of the model using the regression equation derived in the previous section, inputting relevant data points for the independent variables to generate a forecasted exchange rate for the specified date. A crucial element of this chapter is the comparison between the model's forecast and the actual exchange rate for August 2015, allowing for an assessment of the model's predictive accuracy and any potential sources of error or limitations.
Schlüsselwörter (Keywords)
Forecasting exchange rate, Panel data, Regression model, USD/BDT, Inflation rate, Bank interest rate, Per capita income, GDP growth rate, Econometric modeling, International trade, Foreign exchange market.
Frequently Asked Questions: Exchange Rate Forecasting using Panel Data
What is the main objective of this research paper?
The primary goal is to present a highly efficient and quick method for predicting exchange rates, specifically focusing on the USD/BDT pair. This is achieved through the use of panel data and a regression model, with the methodology designed to be adaptable for forecasting other currency pairs.
What methodology is used in this study?
The research employs a regression model built upon panel data. Key variables are identified, including the dependent variable (change in USD/BDT) and independent variables (changes in inflation rate, bank interest rate, per capita income, and GDP growth rate). An Ordinary Least Squares (OLS) regression model is constructed, and the data used consists of 10 years of monthly data from 2005-2015. The chapter thoroughly explains the statistical approach used.
What are the key themes explored in the paper?
The paper explores exchange rate forecasting using panel data, develops and applies a regression model for prediction, analyzes the relationship between exchange rates and macroeconomic variables, assesses the accuracy of the forecasting model, and demonstrates the practical application of econometric techniques in financial forecasting.
What variables are considered in the regression model?
The dependent variable is the change in the USD/BDT exchange rate. The independent variables include changes in the inflation rate, bank interest rate, per capita income, and GDP growth rate.
What is the time period covered by the data used in this study?
The study utilizes 10 years of monthly data, ranging from 2005 to 2015.
What specific exchange rate is being forecasted?
The research focuses on forecasting the USD/BDT (US dollar to Bangladeshi Taka) exchange rate.
How is the accuracy of the forecasting model assessed?
The accuracy is assessed by comparing the forecasted exchange rate for August 2015 (generated using the regression model) with the actual exchange rate for that same period. This comparison reveals the model's predictive power and identifies potential error sources.
What are the key findings of the regression analysis (Chapter 3)?
While the provided excerpt doesn't include specific numerical results, Chapter 3 would present the statistical significance of the independent variables, the R-squared value indicating the model's explanatory power, and diagnostic tests to evaluate the model's validity and goodness of fit.
What is the purpose of Chapter 4 (Forecasting Exchange Rate)?
Chapter 4 applies the developed regression model to predict the USD/BDT exchange rate for August 2015. It uses the regression equation to generate a forecast by inputting relevant data for the independent variables. Crucially, it compares this prediction with the actual exchange rate for August 2015 to evaluate the model's accuracy.
What are the keywords associated with this research?
The keywords include: Forecasting exchange rate, Panel data, Regression model, USD/BDT, Inflation rate, Bank interest rate, Per capita income, GDP growth rate, Econometric modeling, International trade, Foreign exchange market.
- Quote paper
- Sajjad Hossine Sharif (Author), 2015, Forecasting the exchange rate of currencies. A panel data approach, Munich, GRIN Verlag, https://www.grin.com/document/351362
