Discussion of the Results got from the Analysis
Discussion of the Results got from the Analysis
Calculation of percentage changes that have a likelihood of occurring in the stock is important. The percentage changes are influenced by some factors that exist in the stock market such as changes in the annual gross domestic product of countries, housing price index, and annual average interest rates among others. After an analysis of the data collected from 1980 to 2011 on factors that are known to have an influence on the stock market percentage change the following multiple linear regression lines was arrived at: S&P500 (Percentage Change) = 1.229 + 0.008 * (Annual CPI) + 0.039 * (Annual Average PPI) + 0.031 * (Annual Average House Price Index) + 0.371 * (Annual Average Interest Rate) + 0.00 * (Percentage Change of Annual Average GDP of US) + 0.00 * (Percentage Change of Annual Average GDP of Spain) + 0.001 * (Percentage Change of Annual Average GDP of Germany). It was exhibited by the results got from the analysis that the correlation coefficient between the tested variables was 0.949. The coefficient of determination was 0.901.
Second Regression ModelAfter running the regression model, the following results were got; S&P500 (Annual Average) = -248.692 + 0.033 * (Annual CPI) – 3.075 * (Annual Average House Price Index) – 28.139 * (Annual Average Interest Rate) + 60.828 * (Average Annual Unemployment Rate) + 0.169 * (Annual Average GDP of US) - 0.152 * (Annual Average GDP of Germany) -0.008 * (Annual Average GDP of China). Running the second multiple regression produced better results. The earlier assumption that house price index should be affecting annual average negatively is now true. A unit change in this independent variable will lead to a negative change in the annual average. PPI and Spain’s GDP were excluded because they did have a significant effect on the stock market. However, the added variables, which are unemployment rates and GDP of China, have a significant effect on the annual average stock prices. A unit change in the level of unemployment rates will lead to a whopping 0.60828 change in stock prices. On the other hand, in case there is a change in average annual GDP of China, the annual average stock prices in the US will decrease at 0.008. An increase in the annual CPI leads to an increase in the annual average stock prices, which benefit investors (Seattle.gov, 2015). On the other hand, an increase in HPI, annual average interest rates, average annual GDP of Germany and China affects the annual stock prices negatively (Agency, 2015). This model can be used by potential investors to ascertain the average annual returns from investing in stocks of a particular company given the above factors.
Recommendation
The United States needs to embark on special programmes that will enable it to increase employment rates across the country. This will lower the proportion of citizens in the country who are unemployed. Stock prices are affected by unemployment rates as established from the analysis conducted. Also, the country should ensure that its GDP at least conforms to the GDP growth in China. Through this, the nation will be able to stabilize S&P 500 prices.
Conclusion
The analysis clearly indicates that the analyzed economic factors affect the stock prices either positively or negative. The first multiple regression indicates that GDP of US and that of Spain do not have a significant influence on stock prices. Though, this does not remain the case when PPI is removed from the regression, unemployment in US and GDP of China included in the second regression. The higher the GDP of China as well as unemployment rates in China, the higher the percentage change in S&P prices.
References
Agency, U. (2015). All-Transactions House Price Index for the United States (USSTHPI).Research.stlouisfed.org. Retrieved 2 October 2015, from https://research.stlouisfed.org/fred2/series/USSTHPI/downloaddata
Statista, (2015). USA - annual changes of the Producer Price Index (PPI) 1990-2014 | Timeline. Retrieved 2 October 2015, from http://www.statista.com/statistics/193966/annual-changes-of-the-producer-price-index-for-commodities-in-the-us-since-1990/
Seattle.gov, (2015). Inflation - Consumer Price Index - Historical Data. Retrieved 2 October 2015, from http://www.seattle.gov/financedepartment/cpi/historical.htm
Appendices
