# TASK 1- decide on a PUBLICALLY LISTED company(Option2.1) or choose MACROECONOMIC

TASK 1- decide on a PUBLICALLY LISTED company(Option2.1) or choose MACROECONOMIC data (option 2.2) .
to analyse stock price of a pubklically listed company – eg Apple, Tesla etc (dont choose these common companies and end up having high plagirism with others. There 55214 publically listed companies in the world. All variables must cover calendar year 2023 at daily frequency (at least 200 observations). You can download the data for Option 1 using Bloomberg, Yahoo Finance, or any other financial database of your choice. As you will be online for the coming weeks the easiest way is to download the data from yahoo finance.
TASK 2- Constructing the dataset (I will describe this in detail in the week 7 online lecture class)
For your assignment analysis, you must construct a dataset including a continuous dependent variable (?),two continuous independent variables (?1 and ?2 ), and a dummy independent variable (?3 ). You choose any of the options below
Option 2.1: Time Series
To perform a time series analysis using Yahoo Finance and Excel with the specified variables, follow these steps:
check this link for video – https://youtu.be/S39Lx-Lh3fQ?si＝dyGmKTmPeOqG3HKF SAME as above
Go to Yahoo Finance.
Navigate to the ″Historical Data″ tab.
Set the time range to cover the calendar year 2023, daily
check this link for video – https://youtu.be/S39Lx-Lh3fQ?si＝dyGmKTmPeOqG3HKF SAME as above
Go to Yahoo Finance.
Search for a relevant stock market benchmark (e.g., S&P 500)
Navigate to the ″Historical Data″ tab.
Set the time range to cover the calendar year 2023, daily
download daily index in csv excel and calculate returns means – apply simple or log returns to the index (pt/Pt-1 or Ln(Pt/pt-1)
check this link for video- https://youtu.be/S39Lx-Lh3fQ?si＝dyGmKTmPeOqG3HKF SAME as above
Go to Yahoo Finance.
Search for a relevant currency or commodity (e.g., USD, oil)
Navigate to the ″Historical Data″ tab.
Set the time range to cover the calendar year 2023, daily
download daily currency / commodity in csv excel and calculate returns means returns- apply simple or log returns to the index (pt/Pt-1 or Ln(Pt/pt-1)
2.1.4 Create dummy variable: (X3)
calculate returns of Y, X1, X2 means – apply simple or log returns Yt,X1t and X2t in the format of (pt/Pt-1 or Ln(Pt/pt-1)
create a new column for the dummy variable.
Define the criteria for the dummy variable (e.g., positive or negative returns).
Use a formula or coding to assign 1 or 0 to the dummy variable based on the defined criteria.
you are yet to complete the last 2 steps in the weeks lectures so leave that for the time being
Option 2.2: Cross Section Data
Real GDP per capita growth (constant USD) in 2022.
?1: Log of GDP per capita (constant USD) in 2021.
?2: Macroeconomic indicator (e.g., inflation, unemployment, gross capital formation) in 2022.
?3: Dummy variable based on relevant geographic, development
Steps
Visit World Bank, IMF, or Other Economic Database: Go to the official websites of the World Bank (worldbank.org), IMF (imf.org), or another reputable economic database.
Locate the Databases or Data Repositories: Explore the sections of the websites that provide access to economic indicators and datasets.
Select the Variables: Look for the specific variables needed for your analysis (Real GDP per capita growth, Log of GDP per capita, Macroeconomic indicator for 2022, and relevant dummy variable).
TASK 3- Section A: Ordinary Least Squares (500 words, 15 marks)
LINEST – https://youtu.be/ghxARow323E?si＝lgaNPl5n37vMXB0B
data analysis tool pack- Excel Regression Analysis through the Toolpak (youtube.com)
Briefly discuss the dataset you have constructed and present relevant desсrіptive statistics (3 marks).
Provide a concise overview of the dataset, including the variables used in the regression analysis. Mention the source of the data and any preprocessing steps taken. Discuss the size of the dataset, the number of observations, and the countries included.
Present relevant desсrіptive statistics for each variable, such as mean, standard deviation, minimum, maximum, and any other statistics that help describe the central tendency and variability of the data.
Estimate the regression equation ? ＝ ?0 + ?1?1 + ?2?2 + ?3?3 + ? via ordinary least squares (2 marks).
Present the estimated regression equation: ? ＝ ?0 + ?1?1 + ?2?2 + ?3?3
Interpret all regression coefficients (including the constant) and assess their statistical significance using a T-test (4 marks).
Explain the role of each coefficient (?)
Interpret the regression coefficients ?0, ?1, ?2, ?3 in the context of the specific variables they represent.
Discuss the expected impact of a one-unit change in each independent variable on the dependent variable.
Discuss the explanatory power of the model using the R-squared and the F-test (2 marks).
Statistical Significance using T-test: Perform T-tests for each coefficient to assess their statistical significance. Discuss whether each coefficient is significantly different from zero.
Explanatory Power of the Model: Discuss the R-squared value to assess the proportion of variance explained by the model. Interpret the F-test to evaluate the overall significance of the regression equation.
Briefly explain the implications of documented relationships or lack thereof for theory and practice in context of relevant academic sources (4 marks)
Based on the regression results, discuss the implications for theory and practice. Relate the findings to existing academic sources or economic theories.
Highlight any relationships that are statistically significant and consider the practical implications of these relationships or the lack thereof.
Ensure that each section is presented clearly and concisely, providing enough detail to convey the key insights from the regression analysis and its implications.