The images attached below are from an essay where stock prices of the company BP plc were analysed.
Can a finance professor explain to me, with guidance, how the stock prices in SPSS were analysed here?
Analysis of Variance (ANOVA) The analysis of variance was used to investigate the fitness of the model used. In this case, F's value was used to decide the fitness (Christensen, 2015). The value of F was large (1358.407). The significant value of F was smaller than the 0.05 level of significance (Significance F=1.1E-236). Therefore, it was concluded that the model was fit at a 95% level of significance. ANOVA df SS MS F Significance F Regression 7192.395 2397.465 1358.407 1.1E-236 Residual 489 863.0405 1.764909 Total 492 8055.435The coefficients were used to investigate the contributions of each of the variables on the stock prices. The coefficient also indicated whether the variables contributed negatively or positively to the stock prices in BP Plc. Case study, it was clear that there was a positive relationship between the FTSE and the stock prices. It was found that a unit increase in the FTSE contributed to a 0.009875 increase in the stock prices. The 10-Year Gilt Interest rates showed a positive relationship between the two variables (Anderson & Semmelroth. 2015). It was clear that a unit change in the 10-Year Gilt Interest rates contributed to 0.36785increase in the stock prices. The USD/GBP showed that there was a positive relationship between the two variables. A single increase in the USD/GBP resulted in a 19.0236 increase in stock prices. The three variables' P-values were less than 0.05 level of significance (Ekstrom & Sorensen, 2015). The null hypothesis was therefore rejected, and a conclusion was made that there was a significant relationship between the stock prices of BP Plc., the FTSE, gilt interest rate, and the US$/GBE exchange rates. Standard Lower Coefficients Error t Stat P-value 95% Intercept -57.284 1.736223 -32.9935 1.8E-126 -60.6954 FTSE 0.009875 0.000167 59.04876 1.2E-224 0.009547 10-Year Gilt Interest rates 0.36785 0.272028 1.352249 0.176921 -0.16664 GBP/USD 19.0236 1.09502 17.37282 5.27E-53 16.87207Descriptive statistics Descriptive statistics are used to investigate the measures of central tendency and dispersion of the data. After the data had been analyzed, the company's stock prices' mean value was $35.33. with a standard deviation value of 4.05. The standard deviation value was small, which indicated that the values were closely distributed to the mean. 0n the other hand, the company stock prices' maximum value was 27.64, while the maximum value was 43.60. Stock Prices Mean 35. 32892491 Standard Error 0.18223781 Median 34.830002 Mode 35.68 Standard Deviation 4.04633605 Sample Variance 16.37283543 Kurtosis -0.9T320171T Skewness 0.29938424 Range 1 5.959999 Minimum 27.639999 Maximu m 43. 599998 Sum 1741115998 Count 493 Research objective and question The objective of the research is to investigate the relationship between the stock prices of BP Global, the FTSE, gilt interest rate, and the US$iGB exchange rate. Once data has been collected. it will be analyzed. and a conclusion will be made from the analysis. In this case, a research question will be used to help meet the research's objective. The research question in this study is if there is a signicant relationship between the stock prices of BP Global, the FTSE, gilt interest rate, and the US$iGB exchange rate. Research hypothesis The research hypothesis is based on the research question. The null and alternative hypotheses are tested after the analysis of the data. The null hypothesis is used to conclude the data. By either rejecting or accepting the null hypothesis, a conclusion will be made. The two hypotheses to be tested are: . The null hypothesis: There a no signicant relationship between stock prices of BP Global, the FTSE, gilt interest rate, and the US$iGB exchange rate I The alternative hypothesis: There a signicant relationship between the stock prices of BP Global, the FTSE, gilt interest rate, and the US$GB exchange rate. Research methods The research deals with quantitative data that is collected from secondary sources (investing.com, 2020). The collected data will be put in MS Excel software and SPSS that will be used to gramme data. The research aims at investigating the relationship between four variables. In this case, one is the dependent variable, while the other three are the independent variables. The stock prices are the dependent variable, while the FI'SE, gilt interest rate, and the US$iGB exchange rate are the independent variables. Multiple regression analysis will be used in this case to come up with the relationship between the two variables (Cameron 3. Trivedi, 2010). The data analysis will also include an Analysis of Variance that will test the prediction model's tness that will be used in the study. Regression analysis Multiple regression analysis was used in this case due to the number of variables under study. There were three independent variables whose relationship with the stock prices were investigated. Summary output The regression summary out comprised of the R-square value and the adjusted value of R Square. The value of R-square explains the contribution of the independent variables on the dependent variable. According to the R-Square value, it was clear that there was a large contribution of the independent variables on the dependent variable. The value of R- square was 0.892862. The value showed that the independent variables explained 89.29% ofthe dependent variable changes. It was evident that the stock prices were highly inuenced by the FTSE, Gilt interest rate, and the US$iGB exchange rate. Regression Statistics Multiple R 0.944914 R Square 0.892862 Adjusted R Square 0.892205 Standard Error 1.328499 Observations 493 Stock prices and BGPIUSD The relationship between the BGPIUSD was investigated in the paper through a scatter plot with the stock prices on the y-axis. The relationship between the two was evident from the positive gradient shown by the trend line equation (y = 14.1641 + 14.713). 0n the other hand, R-square's value was small, which showed that the BGP/USD could be used as a predictor of the stock prices (0.1285). It was clear that the BGPIUSD changes explained 12.85% of the changes in stock prices. Stock prices vs GBP/USD Stock prices and 10-Year Gilt Interest rates The analysis of the data, in this case. was done using a scatter plot to investigate the relationship between the two variables. The stock prices were the dependent variable, while the 18-Year Gilt Interest rates were the independent variable. The scatter plot showed a positive relationship between the two variables. The study showed that the trend line equation was y = 2.85973: + 30.91, which showed a positive relationship between the two variables as shown by the gradient. The value of R-square was 8.0848. The value indicated that there was a relationship between the two variables. From the value of R- square value. it was clear that the independent variables explained 8.48% of the dependent variable changes. Stock prices and FTSE This scatters plot was used to investigate the relationship between the FTSE and the stock prices of BP Plc. It was found that different factors affected stock prices. FTSE and the stock prices were investigated in this part of the study. From the dataI a scatter plot was used to investigate the relationship. It was clear that there was a positive correlation between the two variables. The trend line equation y = 0.0089): - 22.495 showed a positive correlation, as shown by the line's gradient value (0.0089). The value of R-square from the analysis was 0.6374. It indicated that the FTSE could be a good predictor of stock prices as 63.74% of the changes in stock prices were explained by the FTSE changes. Stock Prices vs FTSE 4.5 43 41 38 v=0,0089x22,495 E 3}. R2=0,6374 .5 35 33 m 31 27 0 . Series "Stock prices" Pomt "55' 25 . (6693,95, 33,18) 50m 5501] FTSE I Stockpn'cs Linear[Stock price} Trend Line The trend line was used to investigate the trend of the prices' changes over time under study. From the data, a trend line was tted to the plotted data. It was clear that there was a decreasing trend in the stock prices of the company. This information would be essential for the investors. and it was clear that the prices would have dropped further (may, 2015). The largest prices are found to have been experienced between December 2014 and July 2015. The smallest prices are found between December 2015 and May 2016. Since June 2015I it can be seen from the graph that there has been an increase in the value of the stock prices. The overall trend shown by the tted trend line is decreasing. Trend BP PLC Stock prices 50 45 40 35 ii] 30 I.) E 25 Stockpr'ica 31 21] Expm. [Stack prim} 15 m Plot Area 5 "" 0 393" 15950 ~59" a?" 53* 9b a"? 96 19) 9'6 19; 1939 0: q} b} b ? NW 0y 1:, by "5-" b? '9')
