Limitation of Research

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the U.S. dollar-Mexican peso exchange rate became associated with the term the "Trump trade"

(FXCM, 2017). The major interest of this research is to determine whether Trump’s announcements through Twitter, a mayor communication channel of U.S. president, have impacts on S&P/BMV IPC.

Source: finance.yahoo.com

Figure 4: MXN/USD’s Record Low after Trump’s Announcement of Major Tax Border

1.2. Research Questions

1. Does the international crude oil price influence the S&P/BMV IPC?

2. Does S&P 500 influence the S&P/BMV IPC?

3. Does the exchange rate between the USD and the MXN influence the S&P/BMV IPC?

4. Do Donald Trump’s tweets influence the S&P/BMV IPC?

1.3. Research Objective

Find the impact of international crude oil price, S&P 500, USD/MXN exchange rate and Donald Trump’s tweets on S&P/BMV IPC used as a proxy of the Mexican Stock Exchange (BMV).

1.4. Limitation of Research

The limitation of research is defined to focuses on S&P/BMV IPC that is influenced by international crude oil price, S&P 500, USD/MXN exchange rate and Donald Trump’s tweets period from January 2015 to December 2019.

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The Mexican Stock Exchange (BMV) is a public institution that operates under a concession granted by the Ministry of Finance (SHCP) and observes the Mexican Securities Law. It is one of two stock exchanges in Mexico with the other being BIVA – “Bolsa Institucional de Valores”.

BMV is the second largest stock exchange in Latin America with a total market capitalization of over US$ 530 billion. It is the physical place where the trades made by the brokerage firms are executed and registered. Investors buy and sell stocks and debt securities through intermediaries, called brokerage firms. Its principal index is “Índice de Precios y Cotizaciones”

S&P/BMV IPC.

The Mexican Stock Exchange (BMV) is a forum where the organized securities market transactions are held. Its main objective is to facilitate the securities transaction, market development and competitiveness.

The companies that require monetary resources (money) to finance its operations or expansion projects, might find it at the securities market, by issuing securities (stocks, bonds, commercial paper, etc.) to the investors (issued) that are traded (bought and sold) at the Mexican Exchange, in a transparent and free competitive market with equal opportunities for all participants.

The stock exchanges worldwide are established institutions by the society for its own benefit. Investors go to them as an option to protect and increase their monetary savings while supply monetary resources that in turn allow corporations and governments to finance productive and development projects that in turn generate jobs and wealth. In this sense, the Mexican Exchange encourages the development of the country since; it also helps to allocate savings into productive investments that is the source of growth and employment in Mexico.

2.1.1. History

From 1880 to 1900, Mexico City’s downtown streets, held meetings where brokers and entrepreneurs bought and sold all sorts of assets. Later, exclusive groups of stockholders and issuers involved themselves, trading behind closed doors in different parts of the city. On June 14, 1895, a group of brokers formed a partnership under the name Bolsa de Valores Mexico

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(Mexico’s Stock Exchange).

On August 28, 1933, the deed and statutes of the Bolsa de Valores de Mexico, S.A. were approved in accordance with the concession authorized, which for the first time included the stock exchanges. The exchange is supervised by the National Council on Securities (nowadays the National Banking and Securities Commission).

By 1975 the Securities' Market Law, prompted the Bolsa de Valores de México to change its name to Bolsa Mexicana de Valores (Mexican Stock Exchange). On 19 April 1980, the S&P BMV/IPC was first published.

In 2006, the Mexican securities market was opened to foreigners through the MexDer system for them to operate from anywhere in the world (BMV Group, 2015).

2.2. Índice de Precios y Cotizaciones S&P/BMV IPC

A reference index aims to represent the performance of a stock market, assets or market segment.

As mentioned before in this research, the S&P/BMV IPC aims to measure the performance of the 35 biggest and greatest liquidity stocks listed in the Mexican Stock Exchange. Similar to other indexes in the world, the S&P/BMV IPC can be regarded as an economic indicator since the stock market has a strong relationship with the economic variables. According to Sanchez 2018, the correlation between the annual variation of Mexican GDP and that of the S&P/BMV IPC is 57% during the period from 1979 to 2017.

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Figure 5: S&P/BMV IPC vs. Mexico GDP

2.3. Factors that Influence S&P/BMV IPC

2.3.1. International Crude Oil Price

In 2018, worldwide energy consumption was 13,978 millions of tons of oil equivalent [Enerdata, 2019], being oil the major source of energy accounting for 32% as show in figure 6 below.

Figure 6: Energy Consumption by Type, 2018 ,

32%

9% 23%

26%

10%

Energy Consumption by Type 2018

Oil Gas Electricity Coal Biomass

Source: Sánchez 2018

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The price of oil refers to the spot price of a barrel of benchmark of oil, a reference for buyers and sellers, benchmarks such as Brent Crude, West Texas Intermediate (WTI) and Isthmus. The price of barrel varies according its grade, heavier crude oils are more expensive than lighter crude oils. WTI is the benchmark for the Mexican crude oil. Even though the oil price is subject to the supply and demand dynamic, the Organization of Petroleum Exporting Countries, OPEC, an intergovernmental organization of 14 nations that account for 44 percent of global oil production and 81.5 percent of world’s proven oil reserves have a major influence on global oil prices, acting as a cartel to reduce market competition. In 2019, Mexico was the 12^th largest crude oil producer [U.S. Energy Information Administration, 2020], 2.71 percent of global production, however, the country is not part of the OPEC.

2.3.2. S&P 500

The S&P 500 measures the stock performance of 500 large companies listed on the stock exchange in the U.S. It is a market value-weighted index; its components are weighted according to the total market value of their outstanding shares. Due to the large number of companies across all sectors included in the S&P 500, investors perceive it as the most representative stock index in the U.S.

The U.S. is over one-half of the global stock market, according to S&P Global BMI measure.

As the U.S. economy grows, it propels the stock markets of all other countries—and the U.S.

stock market is largely driven by consumer spending. Therefore, the more a country exports to the U.S., the more sensitive it becomes to U.S. growth (Gunzberg & Edwards, 2018).

2.3.3. Exchange Rate USD/MXN

Exchange rate is regarded as the value of one country's currency in relation to another currency [O'Sullivan, 2003]. Aside from interest rate and inflation, the currency exchange rate is one of the most important factors of a country’s economic health level.

Several factors influence the exchange rate changes:

- The supply and demand dynamic between the currency of two countries, appreciating or depreciating the price of nation currency relatively to other country’s currency.

- Officially devaluation of national currency conducted by the government of a country.

- Officially revaluation of national currency conducted by the government of a country.

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- Foreign currency supply and demand, supply coming from goods export, capital import.

Demand coming from goods imports, capital export.

- Differentials in inflation, a country with a consistently lower inflation rate exhibits a rising currency value, as its purchasing power increases relative to other currencies.

- Differentials in interest rate, by manipulating interest rates, central banks affect inflation and currency values. Higher interest rates offer lenders in an economy a higher return relative to other countries. Therefore, higher interest rates attract foreign capital and cause the exchange rate to rise. The opposite phenomena occurs when the central banks decreases the interest rate.

- Public deficit, a country government can get monetary resources to pay for public sector projects and governmental funding by borrowing money. This stimulate the domestic economy but large debts encourage inflation, decreasing the exchange rate of the country.

- Position of balance of payments, the balance of payments is a statement of the prices of imports and exports of goods, services and capital between a country and the rest of the world. If the price of exports is smaller than that of its imports,the currency's value will decrease in relation to its trading partners.

2.3.4. Donald Trump Tweets

Donald Trump opened his twitter account @RealDonaldTrump on May 4, 2009. He initially used to draw attention to his book, “Think Like a Champion”. From 2013 onwards, Trump's Twitter activity pattern significantly increased in the volume of his tweets and the rate of politically charged rhetoric [Fandos, 2017]. For the 2016 presidential campaign, Donald Trump used its twitter account as an important political communication channel. Political analysts consider that the use of twitter contributed for his victory in the 2016 U.S. presidential elections [Ingram, 2017].

Even though there is an official tweeter account for the U.S. President, @POTUS, President Donald Trump prefers to use his personal twitter account to issue major announcements himself over social media, bypassing the White House Press Secretary. President Donald Trump’s tweets are a great way to know what the president is thinking, doing or thinking of doing, they are also a great source of conflict and controversy. His tweets have effect in the stock market,

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for example, on August 17, 2017 post on Amazon: ‘Amazon is doing great damage to tax paying retailers. Towns, cities and states throughout the U.S. are being hurt - many jobs being lost!

[Trump, 2017] Afterwards, the market capitalization of Amazon declined by $6 billion [Chapman, 2017].

2.4. Previous Research on Factors affecting the S&P/IPC BMV

Lopez-Juaréz, Ladrón de Guevara-Cortés and Madrid-Paredones (2019) in their research about a set of macroeconomic variables that could explain the behavior of the stock market in Mexico, they select the S&P/IPC BMV as the market proxy. The results showed that the international oil price and the exchange rate are factors that influence the S&P/IPC BMV behavior during the period from January 02, 2008 to December 31, 2015. Their research also included the Banco de Mexico interest rate but according to their results, there was not sufficient statistical evidence to support the interest rate’s influence on S&P/IPC BMV.

Singhal, Choudhay, Biswal (2019) investigate the dynamic relationship among international oil prices, international gold prices, exchange rate and stock market index in Mexico. Findings of their study suggest that oil price negatively in the long-run influence the stock market index, exchange rate and gold prices are significantly correlated with stock prices, tending to move in the same direction. They used daily data from January 2006 to April 2018 for their study.

Sardy, Cova (2019) findings show that Trumps tweets influence financial markets, using S&P 500 index as the market proxy, at daily returns level. They first collect all economy related Trump’s tweets per day, subsequently, they assign one of three sentiment labels, positive, neutral or negative, determined by whether President Trump had worded in a positive, neutral or negative tone. The daily tweet sentiment was then calculated by assigning each sentiment label with a score; positive: +1, neutral: 0, negative -1, and summing the sentiment of each economy-related tweet of the day. Regarding Trumps tweets effect in foreign markets Guo, Jiao, Xu (2019) research paper analyze their influence on the Chinese stock market. Their findings suggest that after his presidential inauguration, Trumps tweets containing positive sentiment towards China increase the stock prices of Chinese manufacturing companies listed on the Shanghai Stock Exchange and the Shenzhen Stock Exchange.

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3. Data and Methodology 3.1. Research Method

This research focuses on the influence of international crude oil price, S&P 500, exchange rate MXN/USD and Donald Trump’s tweets on S&P/BMV IPC. This research uses two models, multiple linear regression approach (MLR) auto regressive distributed lag model approach (ARDL). The analysis uses more than one independent macroeconomic variable to explain the factors influencing S&P/BMV IPC.

3.2. Object of Research

The object of this research is the price of S&P/BMV IPC as dependent variable. Meanwhile, international crude oil price, S&P 500, exchange rate USD/MXN and Donald Trump’s tweets as independent variables. The observation is conducted by time series data amounted 60 months from June 2015 to December 2019.

3.3. Types and Sources of Data

The source of data are secondary data from Thomson Reuters platform EIKON and Trump twitter archive website. The research uses monthly S&P/BMV IPC value, international crude oil price, S&P 500 value, exchange rate USD/MXN and Trump’s tweets sentiment from January 2015 to December 2019.

3.4. Variable Definition

3.4.1. S&P/BMV IPC

S&P/BMV IPC measure the performance of the 35 biggest and greatest liquidity stocks listed in the Mexican Stock Exchange; therefore, we use it as a benchmark of the market movement in Mexico. We use price data; price is given by the formula below:

It = Index in period t

Pit = Stock price of company i in period t

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Qit = Stocks of company i in period t Fi = Adjust factor

i = 1, 2, 3… 35

It is represented by IPC in our research. For multiple linear regression analysis, in order to ensure the stationarity we use the return of S&P/BMV IPC:

Return IPCt = (IPCt – IPCt-1) / IPCt-1

3.4.2. International Crude Oil Price

This research uses West Texas Intermediate (WTI) price as a proxy for international crude oil price movements. It is measured in USD/barrel and represented by ReOIL. For multiple linear regression analysis, in order to ensure the stationarity we use the WTI crude oil return:

ReturnOILt = (OILt – OILt-1)/ OILt-1

3.4.3. S&P 500 Index

The S&P 500 index is widely considered as the best representation of the U.S. stock market. It is represented as SP500 in our research. For multiple linear regression analysis, in order to ensure the stationarity we use the return of S&P 500:

ReSP500t = (SP500t – SP500t-1) / SP500t-1

3.4.4. Exchange Rate USD/MXN

Majority of the export and import from Mexico is done in US Dollars, therefore for exchange rate movements the Mexican peso (MXN) and US dollar (US $) currency pairs is used. They are measured as USD/MXN and represented by ReEX. For multiple linear regression analysis, in order to ensure the stationarity we use the exchange rate difference between periods:

ReturnEXt = (EXt – EXt-1) / EXt-1

3.4.5. Donald Trump Tweets

Consists of the Tweets posted by Donald Trump from his personal twitter account

@RealDonaldTrump, and the sentiment of each Tweet. The data was collected from Trump

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Twitter Archive website (http://www.trumptwitterarchive.com/archive), contained the date and content. In the 60-month period of study, Trump wrote 266 tweets related to Mexico.

We determined a sentiment for each tweet. Sentiment was evaluated according to Trump’s sentiment towards Mexico; we assigned each tweet with one of three sentiment labels, positive, neutral, or negative, determined by whether he had worded it in a positive, neutral, or negative tone. The monthly tweet sentiment was then calculated by assigning each sentiment label with a score; positive: +1, neutral: 0, negative -1, and summing the sentiment of each Mexico-related tweet. It is represented by TRUMP in our model.

3.5. Methodologies

3.5.1. Multiple Linear Regression Model

The first approach this research uses is multiple linear regression analysis; its aim is to measure the impact of different factors on S&P/BMV IPC. The multiple regression equation is:

ReIPC =  +1 ReOIL + 2 RetSP500 + 3 ReEX + 4 TRUMP + 

Where:

ReIPC: Return on S&P/BMV IPC.

: Constant coefficient.

1 - 4: Regression coefficient of each independent variable.

ReOIL: Return in international price of oil.

ReSP500: Return of S&P500 index.

ReEX: Return Change in exchange rate USD/MXN.

TRUMP: Sentiment of Donald Trump’s tweets towards Mexico.

: Standard error.

3.5.2. Linear Regression Assumptions

Multiple linear regression makes several key assumptions:

1. Linear: Predictor variables in the regression have a straight-line relationship with the outcome variable. Scatterplots can show whether there is a linear or curvilinear

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relationship, another method is by complying with the normality and homoscedasticity assumptions, if the residuals are normally distributed

2. Normality: Multiple regression assumes that the residuals are normally distributed.

3. No Multicollinearity: Multiple regression assumes that the independent variables are not highly correlated with each other. This assumption is tested using variance inflation factor (VIF) values. If the VIF values are under 5 it means the variables are not highly correlated.

4. Homoscedasticity: This assumption states that the variance of error terms are similar across the values of the independent variables. A plot of standardized residuals versus predicted values can show whether points are equally distributed across all values of the independent variables. When the scatter plot shows no pattern, it means homoscedasticity assumption is met.

3.5.3. Hypothesis Testing MLR

Ho1: 1 = 0; There is no influence of international price of oil on S&P/BMV IPC.

Ha1: 1 ≠ 0; There is influence of international price of oil on S&P/BMV IPC.

Ho2: 2 = 0; There is no influence of S&P 500 index on S&P/BMV IPC.

Ha2: 2 ≠ 0; There is influence of S&P 500 index on S&P/BMV IPC.

Ho3: 3 = 0; There is no influence of exchange rate USD/MXN on S&P/BMV IPC.

Ha3: 3 ≠ 0; There is influence of exchange rate USD/MXN on S&P/BMV IPC.

Ho4: 4 = 0; There is no influence of Trump’s tweets about Mexico on S&P/BMV IPC.

Ha4: 4 ≠ 0; There is influence of Trump’s tweets about Mexico S&P/BMV IPC.

3.5.4. ARDL Bound Co Integration Test

In order to test the relationship and measure the impact of different factors on S&P/BMV IPC this research uses ARDL analysis to compare its findings with MLR analysis. The co integration concept surges in order to know if variables are indeed, related. The ARDL approach has several advantages:

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1. ARDL model contains the lagged value(s) of the dependent variable, the current and lagged values of regressors as explanatory variables.

2. It uses a combination of endogenous and exogenous variables. Explanatory variables are also used as dependent variables.

3. Unlike other methods of testing co integration, ARDL bound can be used irrespective of whether the variables of the study are I(0) or I(1) or a combination of both. However, the series must not be I(2), otherwise we cannot use ARDL bound test.

4. Once the lag order of the model is identified, co integration can be tested using bound test procedure of ordinary least square (OLS). From the bound test result, if variables are cointegrated, it is necessary to specify both short-run (ARDL) and long run (VECM) models. If they are not cointegrated it is necessary to specify the short-run (ARDL) model only.

5. This model performs better and avoids issues of weak power in modelling the co-integrating relationship with small samples (Romilly et al., 2001; Pesaran, 1997).

Initially unit root test (ADF and Phillip Person) are applied on both the series at the levels and at the first difference to check the stationary of the variables and to ensure that none of the variables is integrated of order (2). In the second step, we develop the ARDL model according to specifications based on the Akaike information criterion (AIC). This is followed by bounds testing to check for a co-integrating relationship between the dependent and the explanatory variables.

Regressions are estimated as following:

IPCt =  +1IPCt-1 + 2OILt-1 + 3SP500t-1 + 4EXt-1 + 5TRUMPt-1 + ∑^𝑛_𝑖=1∝₆IPCt-1 +

∑^𝑛_𝑖=1∝₇OILt-1 + ∑^𝑛_𝑖=1∝₈SP500t-1 + ∑^𝑛_𝑖=1∝₉EXt-1 + ∑^𝑛_𝑖=1∝₁₀TRUMPt-1 + 1t

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OILt =  +1IPCt-1 + 2OILt-1 + 3SP500t-1 + 4EXt-1 + 5TRUMPt-1 + ∑^𝑛_𝑖=1β₆IPCt-1 +

∑^𝑛_𝑖=1β₇OILt-1 + ∑^𝑛_𝑖=1β₈SP500t-1 + ∑^𝑛_𝑖=1β₉EXt-1 + ∑^𝑛_𝑖=1β₁₀TRUMPt-1 + 2t

SP500t =  +1IPCt-1 + 2OILt-1 + 3SP500t-1 + 4EXt-1 + 5TRUMPt-1 + ∑ⁿ_i=1γ₆IPCt-1 +

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∑ⁿ_i=1γ₇OILt-1 + ∑ⁿ_i=1γ₈SP500t-1 + ∑ⁿ_i=1γ₉EXt-1 + ∑ⁿ_i=1γ₁₀TRUMPt-1 + 4t

EXt =  + 1IPCt-1 + 2OILt-1 + 3SP500t-1 + 4EXt-1 + 5TRUMPt-1 + ∑ⁿ_i=1μ₆IPCt-1 +

∑ⁿ_i=1μ₇OILt-1 + ∑ⁿ_i=1μ₈SP500t-1 + ∑ⁿ_i=1μ₉EXt-1 + ∑ⁿ_i=1μ₁₀TRUMPt-1 + 3t Where:

IPC: S&P/BMV IPC value

IPC: Difference of S&P/BMV IPC value

OIL: International price of oil

OIL: Difference in international price of oil

ReSP500: S&P 500 value

SP500: Difference of S&P 500 value

EX: Exchange rate USD/MXN

EX: Difference of exchange rate USD/MXN

TRUMP:

Sentiment of Donald Trump’s tweets towards Mexico.

TRUMP: Difference of sentiment of Donald Trump’s tweets towards Mexico

: Standard error

Sentiment of Trump’s tweets is treated as an exogenous variable, it does not respond to the return of IPC, international oil price, return of S&P 500 nor the exchange rate USD/MXN.

Sentiment of Trump’s tweets is treated as an exogenous variable, it does not respond to the return of IPC, international oil price, return of S&P 500 nor the exchange rate USD/MXN.

在文檔中 影響墨西哥S&P/BMV IPC的外部因素 - 政大學術集成 (頁 14-0)