There is no pages or words limit and its a basic assignment. If you hav any questions please let me know. Thank you

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There is no pages or words limit and its a basic assignment. If you hav any questions please let me know. Thank you


Microsoft Word - MBAF502_ProjectI PROJECT I Course Name and Number: MBAF 502: Quantitative Reasoning & Analysis Project 1: Descriptive Statistics and Comparative Analysis Weight = 25% Due May 20, 2022, at 23:59 pm. DESCRIPTION In this assignment, students will collect data on the stock performance of a specific company/asset (approved by the instructor). This group project will focus on learning how to navigate and analyze data using Microsoft Excel and its embedded Visual Basic for Applications (VBA) programming language and Gretl. Students will apply statistical techniques to financial and business models to develop and solve or simulate the core issues. Under Part 1 of this project, students will perform basic analytics and descriptive statistics. Under Part 2 of this project, data sets collected in Phase I will be utilized to explore central and variation tendencies, create index numbers, and write analytics report that will compare the above data for statistically significant differences. PART 1: Data Collection and Descriptive Statistics INSTRUCTIONS Step 1. Install Excel onto your computer using your myucw.ca credentials. Excel Add-ins: Load Excel Analysis ToolPak for visual basic analytics and Solver, where necessary. Step 2. Download and install programing language Gretl (or a statistical tool of your preference); Gretl is available at http://gretl.sourceforge.net , GNU GPL licence, crossplatform. Step 3. Financial Markets Analysis: Extract stock market data of the selected company, or asset (digital asset like cryptocurrencies) for the analysis for a selected time period. Step 4: Define the measure of central tendency. What does each measure tell us? Step 5: Provide a summary statistics and reflect on the major indices from your summary statistics (mean, median, mode, minimum value, maximum value, range, standard deviation, etc.) Step 6. Check the visualizations of the stock price vs time, histograms, and boxplots. Step 7. Write 1000 words report describing the results that you have observed in the analysis of data from Step 5: 5.1 What data were used? 5.2 How were the data acquired? 5.3 How were the data processed? 5.4 How were the visualizations constructed? 5.5 What were the major events observed from 1 year of data? 5.6 What were the major events that happened for the selected company in the same period? (For example, change of executive manager, new policies, products, marketing campaigns, operational changes, market crashes, market bubble, trends, mass adoption, hype, or any socio-political business and nun-business environment dynamics that affected the performance of the stock market) 5.7 How did these major events reflect in the data visualizations? PART 2: Comparative Analysis Here you will perform a comparative analysis using the performance indices. Follow the following instruction for this part of the project. INSTRUCTIONS Step 1. Acquire and visualize data for another related company/asset like the one acquired under part 1. The time interval for the Step 2. What were the major events that have occurred in the market (for example, market rallies, market crashes, changes in government policies, economic situation)? Step 3. How did these major events reflect in the behaviour of the company/asset chosen above? Step 4. Write 1000 words report comparing the performance of S&P500 with the company selected in Phase 1: 4.1 Which of the compared items exhibited higher returns. 4.2 Which of the compared items exhibited higher volatility. 4.3 Using the hypothesis test framework, analyze whether the differences in returns are statistically significant. 4.4 Using the hypothesis test framework, analyze whether the differences in volatilities are statistically significant. Note 1 Variance_ Example (Gretl Sample Data) Bartlett and Levene tests for homogeneity of variance across groups. From the Gretl sample file, use the data on aNIST data for variance tests to work on the following data analysis. (Hint: to access the data, go to Gretl File> Sample File > Gretl > NIST data for variance tests) (Sample data from NIST http://www.itl.nist.gov/div898/handbook/eda/section3/eda3581.htm ) Note 2 Do make use of additional sources to support your argument wherever necessary. Please cite any additional sources you might use. Your work is evaluated based on the content organization, originality, substance and analytical skill you bring in as it is reflected in the quality of the final output. Make sure you create a clear distinction between each section and subsection of the work with a proper flow and transition across. P.S: Please, provide a proper citation (both in-text citation and reference list) of any resource used in this work. Use APA Standard for the format of your final submission ------------------------------------------------------------------------------------------------------------------------------------------------------------
Answered 4 days AfterMay 17, 2022

Answer To: There is no pages or words limit and its a basic assignment. If you hav any questions please let me...

Mohd answered on May 18 2022
79 Votes
Summary Statistics of Intel Stock price:
     
    Open_intel
    High_intel
    Low_intel
    Close_intel
    Adj_Close_intel
    Volume_intel
     
     
     
     
     
     
     
    Mean
    53.42
    54.05
    52.76
    53.39
    51.74
    31851907.13
    Standard Error
    0.25
    0.25
    0.24
    0.25
    0.23
    740635.27
    Median
    53.20
    53.85
    52.67
    53.21
    51.49
    28351000
    Mode
    49.26
    49.90
    58.12
    60.40
    52.62
    #N/A
    Standard Deviation
    5.53
    5.62
    5.43
    5.53
    5.09
    16643707.68
    Sample Variance
    30.59
    31.54
    29.48
    30.60
    25.87
    277013005455340
    Kurtosis
    -0.62
    -0.60
    -0.67
    -0.62
    -0.55
    18.46
    Skewness
    0.39
    0.43
    0.35
    0.39
    0.35
    3
.27
    Range
    25.47
    25.58
    24.62
    25.43
    23.88
    170404300.00
    Minimum
    42.73
    42.91
    42.01
    42.83
    42.03
    11865600.00
    Maximum
    68.20
    68.49
    66.63
    68.26
    65.91
    182269900.00
    Sum
    26977.50
    27294.09
    26646.30
    26962.70
    26129.11
    16085213100.00
    Count
    505.00
    505.00
    505.00
    505.00
    505.00
    505.00
    Confidence Level(95.0%)
    0.48
    0.49
    0.47
    0.48
    0.44
    1455112.79
What data were used?
We have collected two-year daily stocks price data from May 18, 2020 to May 18, 2022. We have used historical stocks data of Intel and AMD from the Yahoo finance website.
5.2 How were the data acquired?
We have downloaded historical stocks data of Intel and AMD from the Yahoo finance website.
5.3 How were the data processed?
We have downloaded csv file format of dataset and import that data into excel.
5.4 How were the visualizations constructed?
All visualization(bar, line, histogram and boxplot) were created in Microsoft excel. In boxplot fluctuation observed as outliers and in case of line chart its spike.
5.5 What were the major events observed from 1 year of data?
5.6 What were the major events that happened for the selected company in the same period?
(For example, change of executive manager, new policies, products, marketing campaigns, operational
changes, market crashes, market bubble, trends, mass adoption, hype, or any socio-political business and non-business environment dynamics that affected the performance of the stock market)
The launch of new processor and shortage in GPU chips has increased the stock price of AMD significantly. On the contrary Intel has stagnant growth. Both have faced global chip shortage. Increasing the acceptance of AMD processor over intel has caused significant increase in stock price.
5.7 How did these major events reflect in the data visualizations?
In the form of spikes (increase in stock price will result into spike in graph).
We have downloaded csv file format of dataset and import that data into excel. All visualization(bar, line, histogram and boxplot) were created in Microsoft excel. In boxplot fluctuation observed as outliers and in case of line chart its spike.
Which of the compared items exhibited higher returns.
AMD has exhibited higher return than intel in past two year.
4.2 Which of the compared items exhibited higher volatility.
AMD also has higher volatility in return(standard error is higher than intel).
4.3 Using the hypothesis test framework, analyze whether the differences in returns are statistically
significant.
From the t-test,
Null hypothesis: The differences in returns are not statistically significant.
Alternative hypothesis: The differences in returns are statistically significant.
As we can see from t-test output P-value >0.05 which implies null hypothesis will be accepted and alternative hypothesis will be rejected. Hence, there is enough evidence to claim that the differences in returns are not statistically significant at five percent significance level.
The volatility in stock price are not statistically significant at five percent significance level.
Line chart:
Boxplot:
Histogram:
Summary statistics of returns:
    
     Intel return
    
    AMD_return 
     
     
     
     
    Mean
    -0.00036
    Mean
    0.00176
    Standard Error
    0.00095
    Standard Error
    0.00144
    Median
    0.00000
    Median
    -0.00019
    Mode
    0.00000
    Mode
    0.00000
    Standard Deviation
    0.02145
    Standard Deviation
    0.03233
    Sample Variance
    0.00046
    Sample Variance
    0.00104
    Kurtosis
    9.83258
    Kurtosis
    1.87039
    Skewness
    -1.53158
    Skewness
    0.43800
    Range
    0.23210
    Range
    0.26512
    Minimum
    -0.16242
    Minimum
    -0.10010
    Maximum
    0.06968
    Maximum
    0.16502
    Sum
    -0.18083
    Sum
    0.89107
    Count
    505
    Count
    505
    Confidence-Level(95.0%)
    0.00188
    Confidence Level(95.0%)
    0.00283
Hypothesis testing:
    t-Test: Two-Sample Assuming Equal Variances
    
    
    
    
    
     
    Intel return
    AMD_return
    Mean
    -0.00036
    0.00176
    Variance
    0.00046
    0.00104
    Observations
    505
    505
    Pooled Variance
    0.00075
    
    Hypothesized Mean Difference
    0.00000
    
    df
    1008
    
    t Stat
    -1.22957
    
    P(T<=t) one-tail
    0.10957
    
    t Critical one-tail
    1.64637
    
    P(T<=t) two-tail
    0.21914
    
    t Critical two-tail
    1.96232
     
    
    
    
    
    
    
    t-Test: Two-Sample Assuming Unequal Variances
    
    
    
    
    
     
    Intel return
    AMD_return
    Mean
    -0.00036
    0.00176
    Variance
    0.00046
    0.00104
    Observations
    505
    505
    Hypothesized Mean Difference
    0
    
    df
    876
    
    t Stat
    -1.22957
    
    P(T<=t) one-tail
    0.10959
    
    t Critical one-tail
    1.64659
    
    P(T<=t) two-tail
    0.21919
    
    t Critical two-tail
    1.96268
     
Conclusion:
We have collected two-year daily stocks price data from May 18, 2020 to May 18, 2022. We have downloaded historical stocks data of Intel and AMD from the Yahoo finance website. We have collected two-year daily stocks price data from May 18, 2020 to May 18, 2022. We have downloaded csv file format of dataset and import that data into excel. All visualization(bar, line, histogram and boxplot) were created in Microsoft excel. In boxplot fluctuation observed as outliers and in case of line chart its spike. AMD has exhibited higher return than intel in past two year. AMD also has higher volatility in return(standard error is higher than intel).
From the t-test,
Null hypothesis: The differences in returns are not statistically significant.
Alternative hypothesis: The differences in returns are statistically significant.
As we can see from t-test output P-value >0.05 which implies null hypothesis will be accepted and alternative hypothesis will be rejected. Hence, there is enough evidence to claim that the differences in returns are not statistically significant at five percent significance level....
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