This paper’s objective is to investigate the influence of external factors to the Mexican economy on the Mexico’s “Índice de Precios y Cotizaciones” (S&P/BMV IPC), the principal index of the Mexican Stock Exchange. The sampling period of this study is from January 2015 to December 2019. We use multiple linear regression and cointegration approaches to test the existence of relationship between S&P/BMV IPC and the exogenous variables.
Findings from the multiple linear regression model suggest that exchange rate has a negative influence in S&P/BMV IPC value, while cointegration approach suggests that only the index value of the previous period has influence in the index value of the subsequent period.

1. Introduction 1
1.1. Background 1
1.2. Research Questions 5
1.3. Research Objective 5
1.4. Limitation of Research 5
2. Literature Review 6
2.1. Mexican Stock Exchange 6
2.1.1. History 6
2.2. Índice de Precios y Cotizaciones S&P/BMV IPC 7
2.3. Factors that Influence S&P/BMV IPC 8
2.3.1. International Crude Oil Price 8
2.3.2. S&P 500 9
2.3.3. Exchange Rate USD/MXN 9
2.3.4. Donald Trump Tweets 10
2.4. Previous Research on Factors affecting the S&P/IPC BMV 11
3. Data and Methodology 12
3.1. Research Method 12
3.2. Object of Research 12
3.3. Types and Sources of Data 12
3.4. Variable Definition 12
3.4.1. S&P/BMV IPC 12
3.4.2. International Crude Oil Price 13
3.4.3. S&P 500 Index 13
3.4.4. Exchange Rate USD/MXN 13
3.4.5. Donald Trump Tweets 13
3.5. Methodologies 14
3.5.1. Multiple Linear Regression Model 14
3.5.2. Linear Regression Assumptions 14
3.5.3. Hypothesis Testing MLR 15
3.5.4. ARDL Bound Co Integration Test 15
3.5.5. Diagnostic Tests ARDL 17
3.5.6. Hypothesis Testing ARDL 18
4. Results and Discussions 19
4.1. Multiple Linear Regression 19
4.1.1. Descriptive statistics 19
4.1.2. Correlation Matrix 19
4.1.3. Multiple Linear Regression Equation 20
4.1.4. Hypotheses Test Result MLR 20
4.1.5. Overall Significance Test MLR 21
4.1.6. Assumptions Test MLR 23
4.2. ARDL Bound Co Integration Test 24
4.2.1. Descriptive statistics 24
4.2.2. Correlation Matrix ARDL 26
4.2.3. Unit Root Test ARDL 26
4.2.4. ARDL Co Bound Integration Test 27
4.2.5. Long Run Equation ARDL 28
4.2.6. Error Correction Model ARDL 28
4.2.7. Hypotheses Test Result ARDL 29
4.2.8. Overall Significance Test ARDL 30
4.2.9. ECM Diagnostics tests 31
5. Conclusions 33
6. References 34
7. Appendix A 37

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