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(solution) Assignment One: Multiple Regression Model Analysis MIT 601-WE01

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Assignment One: Multiple Regression Model Analysis


MIT 601-WE01 Introduction


Today?s stock market offers as many opportunities for investors to raise money as jeopardies to lose it


because market depends on different factors, such as overall observed country?s performance, foreign


countries? performance, and unexpected events. One of the most important stock market indexes is Standard


& Poor's 500 (S&P 500) as it comprises the 500 largest American companies across various industries and


sectors. Many people put their money into the market to get return on investment. Investors ask themselves


questions like how to make money on the stock market and is there a way to predict in some degree how the


stock market will behave? There are lots and lots of variables involved in how the stock market behaves at a


specific time. The stock market is in a way an information agency. Based on new information, whether good


or bad regarding almost everything from political issues to interest rates and inflation, the stock market can


go up or down. The market is anticipating economic occurrences pro-actively, ignoring already occurred


events that were predicted before. This way it is very hard to predict how it is going to move in the future. As


S&P 500 is considered to be the most reliable benchmark for the overall U.S. stock market, we decided to


study what factor has the most impact on it. We created two regression models and included the economic


indicators, such as Consumer Price Index, Producer Price Index, House Price index, Interest Rate,


Unemployment Rate,


and Gross Domestic Product of some countries.


First Regression Model Specifications and Data


How accurately can we predict the stock market behavior? People working in the finance industry have been


trying to estimate or predict the behavior of stock market for a long time, or maybe some of them already


have a very long and complex model of predicting the behavior of a stock market based on many factors and


variables. We decided to use the US economic indicators and the other countries? GDP. With this research we


are hoping to find a statistically significant model that would describe what affects the stock market. We used


the average annual data from 1980 to 2011 to track the influence on the US market. Our data is a time-series


data. It is very interesting since within these 31 years there were a lot of changes in the countries? economies,


financial regulations and policies.


At the very beginning, we assumed that the following factors may have influence on stock market: S&P500


(Percentage Change) = ?0 + ?1 * (Annual CPI) + ?2 * (Annual Average PPI) + ?3 * (Annual Average House


Price Index) + ?4 * (Annual Average Interest Rate) + ?5 * (Percentage Change of Annual Average GDP


of US) + ?6 * (Percentage Change of Annual Average GDP of Spain) + ?7 * (Percentage Change of Annual


Average GDP of Germany) MIT 601-WE01 - Canadian University Dubai ? Fall 2016/17 ?1: Consumer Price Index reflects the state of inflation in the country?s economy. That indicator is very


important in the assessment of the stock market performance. If inflation grows, the interest rate rises and


this prevents the companies to borrow money for further development of their businesses. This entire


situation may hurt the stock prices of the companies and that?s why we wanted to see how big the impact is.


We assume that this variable is going affect the dependent variable a lot. ?2: Producer Price Index indicates


early state of inflation. Therefore, if investors know that the PPI heralds a strong economy with no increase


in an interest rate, then they feel confident to invest in the businesses what means increased positive activity


in the market. We assume that this variable is going to have some impact on the dependent variable however;


it is not going to be crucial.


?3: House Price Index is an analytical tool for estimating changes in the rates of mortgages. If mortgage rates


are high, then housing market is weak because demand for houses drops due to expensive loans, therefore


HPI drops. In 2008 mortgage default affected stock market very severely because before that period house


prices went down because people couldn?t pay their mortgage payments and banks collapsed. Decrease in


house prices is one of the possible contributors to recession because the home owners lose their equity in


their houses. Considering such recession scenario, the stock market always becomes bearish. Additionally,


house market is considered more stable investment than stock market. When stock market drops, people are


willing in the houses and HPI goes up. We assume that HPI and stock market shouldn?t move in the same


direction thereby we don?t take into consideration the complex scenario of 2008.


?4: 10-Year Treasury Constant Maturity Rate impacts on the number of issued bond and is used as risk free


rate to calculate the excess return on the investment. It also has an influence on the stock market.


?5: Gross Domestic Product of the US is important for business profit and this can drive the stock prices up.


Investing in the stock market seems reasonable when the economy is doing well. If the economy is growing


fast then the stock market should be affected positively, the investors are more optimistic about the future and


they put more money into market more. This variable is crucial for the dependent one.


?6: Gross Domestic Product of Spain. Since Europe is currently in a recession, we wanted to include the


GDP of Spain, as one of the weakest economies in Europe now, to check if there is any relationship between


Spain?s economy and the US stock market performance. Very small percentage of US investments goes to


Spain. Compared to Germany, which is the 5th country the USA invests into, Spain is the 31st country on the


list. There should not be any correlation between these two variables, so we included Spain?s GDP into our


regression to check our hypothesis.


?7: Gross Domestic Product of Germany is an indicator of Germany is the 5th largest economy in the world


and is the largest European trade and investment partner of the US. Germany is the largest economy in


Europe and almost 1/5 of GDP of the European Union is that of Germany alone. We assume that this variable


has to have an impact on the US stock market. Second Regression Model


S&P500 (Annual Average) = ?0 + ?1 * (Annual CPI) + ?2 * (Annual Average House Price Index) + ?3 *


(Annual Average Interest Rate) + ?4 * (Average Annual Unemployment Rate) + ?5 * (Annual Average GDP


of US) + ?6 * (Annual Average GDP of Germany) + ?7 * (Annual Average GDP of China) After we run the


regression of the second model, it resulted in improving of our model accuracy. We excluded PPI, GDP of MIT 601-WE01 - Canadian University Dubai ? Fall 2016/17 Spain because it came out that these variables have no impact on the US stock market. Also, we added the


unemployment rate and GDP of China because it is the largest US business partner.


Explanation of the new variables Unemployment Rate is one of the most important factors of the economy?s performance. High


unemployment rate decreases the buyer power of the consumers. 2/3 of the US economy is consumer based


and it influences the stock market negatively. We assume that there is a relationship between these two




Gross Domestic Product of China affects the US economy because cheap export from China prevents


inflation in the US. China is a huge buyer of the US Treasuries. It lowers the interest rate and companies


borrow money to invest in development hence, it directly affects the stock market. We assume that GDP of


China and US stock market move in the same direction, meaning if China does well, it has money to buy US


Treasuries. Additionally, the US stock market increases because production of those US companies that is










Report Content


Suppose you have applied for a business analyst position at a prestigious firm and as part of their hiring


process, you have been requested by the Recruitment Panel to analyze the data for a presentation to be made


to the Panel.


Prepare a report that summarizes your analysis, including key statistical results, conclusions and


recommendations. Your report must also include a complete analysis and clear interpretation of each one of


the coefficients contained in the two studied models. Include any technical material that you feel is


appropriate in the appendix


Data Resources








10-year annual treasury constant maturity rate MIT 601-WE01 - Canadian University Dubai ? Fall 2016/17 US GDP


Other countries GDP


US Unemployment Rate




As mentioned in the course outline explained during the first day of classes, the written report would


represent 20% of your total course score.


Kindly check the below rubrics to ensure you understand how the case study assignment will be assessed.


Make sure you summarize all your data in an excel file that you will provide in the appendix at the


end of your report.


Although it?s a take home assignment, just be aware that plagiarism is a form of cheating. The penalty for


plagiarism is a mark of zero and possible expulsion from the course. As emphasized during the lecture, it is


an individual assignment. Good luck!


Grading Rubrics for Case Study Report Category of




Structure, format,




Clarity of ideas


Problem Statement


and Rationale


Literature Review or


references Research Design Description of Requirements


- Included all required parts


- Used proper format for cover page, table of


contents, figures, references


- The suggested format was used


- Ideas are conveyed efficiently and clearly


- Text is well written grammatically


- Problem statement is specific and clear


- Rationale is clear and logical


- Research objectives are clear and logical


- Hypotheses are clearly done


- Provided references are correctly used


- articles are relevant


- a critical analysis is done with proper comparison


- Properly explains research design


- Instruments and data collection plan are clearly




- Explains how data will be analysed


MIT 601-WE01 - Canadian University Dubai ? Fall 2016/17 Conclusion - Implication and limitations of the research is




- Conclusion is precise an summarizes the results


Total MIT 601-WE01 - Canadian University Dubai ? Fall 2016/17


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Sep 13, 2020





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