the collective wisdom behind behavioral finance in ... · that is spread culturally, sometimes...

Revista de Investigación en Humanidades UFM - RIHU, vol. 5, Universidad Francisco Marroquín, Guatemala, noviembre 2018

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The Collective Wisdom Behind Behavioral Finance in Guatemala´s Foreign Direct Investment

María Isabel Monzón

Abstract

Collective wisdom, also referred to as group co-intelligence, arises from a number of humans

sharing information and learning from one another with sufficient accuracy. In behavioral

finance however, the existence of collective wisdom is quite more complex. This paper aims

to provide solid evidence of such collective wisdom and trace its existence regarding financial

decisions and behavior, specifically those concerning an emerging economy such as that of

Guatemala in Latin America. It was performed by evaluating the thesis which states that

collective wisdom exists amongst investors and that corresponding behaviors can be observed

even before any changes or updates in credit ratings, such as Standard & Poors, Moodys, and

Fitch happen; whilst also providing sound evidence supporting the efficient market

hypothesis. Is there a correlation between the foreign direct investment and the previously

mentioned rankings or are such fluctuations based on collective intelligence?

Keywords

Collective Wisdom, Financial Behavior, Foreign Direct Investment, Guatemala.

Introduction

In social institutions, individuals in high hierarchic positions are often perceived as more

intelligent and experienced than others. In line with the PNAS journal, ¨The position

individuals occupy in the social hierarchy has a marked influence on their cognition and

behavior¨ (Ana Guinote). This may be true since thanks to their position, they have easier or


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better access to greater information and resources, thus making them propitious to take

informed and, consequently, better choices. Nonetheless, these individuals can be shown to

be wrong from time to time.

In contrast, common or collective intelligence is inclined to less mistakes. One explanation is

that collective intelligence gathers knowledge of larger groups, creating a form of unbiased,

and often correct, information. As James Surowiecki states in The Wisdom of Crowds:

¨Western society is focused on the power of the individual mind, but under the right

circumstances, groups can actually make better decisions than even the smartest person

within them¨ (Surowiecki, 2005). Subsequently, a new term arises. Collective wisdom, also

referred to as group co-intelligence, arises from a number of humans sharing information and

learning from one another with sufficient accuracy. As stated by Joseph Henrich, ¨This

¨collective brain¨ makes us smarter as a species as it enables us to accumulate information

that is spread culturally, sometimes without even knowing the real cause or proper

explanation¨ (Henrich, 2016).

However, the existence of said collective wisdom in financial behavior is more complicated

than that. According to the Investopedia, there are certain ¨strategies¨ an investor can use in

order to find the best possible investment option (Investopedia, 2017). These often take into

account risk tolerance, future needs for capital, among other factors. Can there be collective

wisdom in such decisions? Are the investors’ actions already reflected in interest rates and

expected returns of investment? The best approach towards resolving these inquiries is

through behavioral finance, which is the study of how psychology affects finance decisions,

providing plausible explanations for why people may make irrational financial decisions.

Albert Phung clearly states in his article for Investopedia, the presence of such anomalies in

conventional economic and financial theory is very regular, hence conventional financial

theory does not cover every situation that can happen in the real world. He explains that:

¨This is not to say that conventional theory is not valuable, but rather that the addition of

behavioral finance can further clarify how the financial markets work¨ (Phung). Following this


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line, Paul Laudicina approached this fascinating concept trying to explain apparent

discrepancies between the 2016 Foreign Direct Investment confidence index and the actual

investments in US and UK economies.

For this matter, it is intended to observe market trends and tendencies triggered by investors

in critical economy sectors like manufacturing, commerce, energy, banks & insurance,

telecommunications, agriculture, petrol and mines for the Guatemalan Foreign Direct

Investment (FDI) market. Paul expressed that ¨The all-too-visible hand of political risk is on full

display in how investors determine where to invest¨ (Laudicina, 2017). Similar to Paul’s

findings, Guatemala´s former financial analysis director of the public finance ministry, Víctor

Ramírez, also expresses a parallel belief in one of his last reports. He writes that there is

¨robust evidence¨ that correlates FDI with external factors like corruption, political instability

and institutional quality (Ramírez, 2013). Like Jeff Abbott writes, the challenges to peace

remain after two decades of the end of the violent internal armed conflict. Subsequently, a

socio-political and economic investigation had to be done for Guatemala in the period from

1997 to 2017. This was in order to gain further understanding in Guatemala´s past and current

situations and therefore provide enough background for speculation in the FDI´s market. Data

from the World Bank and the Central Bank of Guatemala was used, altogether with historical

information regarding the Standard & Poors’, Moodys’, and Fitch´s rankings (See figure 1) and

economic, social and political context for Guatemala.

This paper aims to prove the existence of said collective wisdom regarding financial decisions

and behavior, specifically those concerning an emerging economy such as that of Guatemala

in Latin America. This was done by providing evidence and hints that support the thesis which

states that collective wisdom not only exists amongst investors, but that corresponding

behaviors can be observed in the market, even before any changes or updates in credit ratings

for Guatemala. Considering this, it is understood that collective wisdom is present

everywhere; henceforth, additionally providing solid evidence that would support the


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Efficient Markets Hypothesis (EMH). The EMH establishes that all known and relevant

information about assets or investment securities, such as stocks, is already factored into the

prices of those same securities, so, it is reflected in its price. According to Sebastian Harder,

an active investor cannot continuously beat the market (and a passive investor cannot

continuously lose to the market), since, overall, market values are always true and future

prices are random depending on incoming information (2008). Therefore, no amount of

analysis can give an investor an edge over the others, as the market works as a whole and it

regulates itself henceforward making wisdom of the crowds the explanation of how imperfect

& irrational players in a free market are still able to allocate resources efficiently or move

towards that desired efficiency.

Hypothesis

Assumptions

Modern finance theory assumes rational solutions to every-day problems as the base to

comprehend investing behaviors. Given the socio-political situation currently lived in

Guatemala as expressed by Maureen Taft-Morales, the specialist in Latin American affairs for

the US congress. Maureen suggests it would be expected to observe some decline in the direct

foreign investment, regardless of the industry. She also believes Guatemala faces many

political and social challenges in the near future, in addition to the present and widespread

corruption and impunity (Taft-Morales).

Last October (2017), according to the World Bank, Moody’s Investors Service1 changed the

perspective for the future as less favorable (negative outlook) in human development, given

the high social needs and the low levels of infrastructure, plus the lack of juridical certainty

among other issues that increase credit exposure. As a consequence, it would be expected to

observe a decline in the foreign direct investment (FDI) in Guatemala´s economy.

1 Standard & Poors confirmed this perspective for the future a few days later (Ministerio de Finanzas Publicas, 2017) / (The World Bank, 2017)


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Nevertheless, it is possible that the decline had already started, giving clear signs of collective

wisdom allocating resources more efficiently in the market. As expected, many other updates

in the rankings have taken place in the last 20 years.

For such matters, an analysis of the FDI net amounts from the years 1997-2017 was matched

against the ratings these services provided in order to assess correlations and causality. For

further analysis, the percent rate variations in yearly FDI was also studied in control charts,

judging the market process behavior of those 20 years.

Problem

It is believed that the market can correctly predict changes in the different investors services’

rankings, hence becoming just a confirmation of a tendency already observed in the market.

But, is there enough evidence to explain market behaviors such as trends and tendencies

towards less or more investment, indicating the collective intelligence behind the accurate

allocation of resources for the Guatemalan market, concerning the FDI?

Hypothesis Approach

Collective wisdom doesn’t exist among investors and corresponding behaviors cannot

be observed even before any changes or updates in credit ratings for Guatemala.

Methodological Framework

The Political and Economic Context of Guatemala

Guatemala is a third world country located in the middle of the American continent. More

than twenty years ago (1996), Guatemala finally came to the end of a cruel and bloody 36

year-long internal civil war. The internal armed conflict turned Guatemalans against each

other and claimed over 200 thousand lives. After years of efforts trying to reach peace talks

between military forces and the guerrilla members, and with the support (and pressure) of

the United Nations, peace was ultimately declared.


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Nonetheless, the peace agreements were not met from both parties, and more than 20 years

after, problems remain constant: poverty has not been eradicated and the country still faces

very high insecurity and violence rates. In accordance with data from the World Bank (2015),

Guatemala is also one of the poorest countries in the world with 59.3% of its population living

in poor conditions and 9.5% in extreme poverty. Due to its geographic location, it also remains

a major drug trafficking transit country to the USA and drug trafficking has become another

national security issue for the authorities, both local and regional.

More recently (2015), Guatemala started an unprecedented and frontal fight against

corruption which remains widespread at many levels. From the highest political positions in

the Executive, Legislative and Judicial branches, to providers and other civilians. The Attorney

General, Thelma Aldana, and part of the justice department with the help of the International

Commission Against Impunity in Guatemala (CICIG) and the Commissionaire Iván Velásquez,

are bringing former presidents, vice-presidents, judges, congressmen and woman, to face

justice processes for the first time in the history of the country. Ever since, several corruption

scandals have been including former president Perez Molina and former vice president

Roxana Baldetti, amid other high-level officials. As reported by Kiran Alwani and Corrin Bulmer

of The Washington Post, Guatemalans are pushing for a stronger rule of law and a more

independent justice system. Civil society actors are gaining power and momentum towards

its anti-corruption crusade. In their words, ¨There have been some promising signs of

accountability, rule of law and public participation in governance. But this remains countered

by a violent past, continued military presence and low voter turnout in the previous election¨

(Alwani & Bulmer, 2016).

Meanwhile, Guatemala has pursued macroeconomic stabilization with reforms that attract

foreign investment, making it the larger economy in Central America. The services sector

represents the largest part of the GDP but with plenty natural resources and tropical weather,

agriculture remains the most important sector in its economy. Guatemala is the 80th

exportation economy in the world as expressed in the Economic Complexity index (2016).


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Some of the principal exportation products are coffee, plantain, sugar, various minerals and

cardamom. In agreement with the data provided by the Observatory of Economic Complexity,

exportation alone constitutes around 12% of its GDP (2016) and employs almost 19% of all

population. Given that Guatemala´s principal destiny of exportation is the United States

(accounting for 40% of the country’s exports), the country has benefited from the recovery of

the U.S. economy.

In 2016, the country’s growth reached 3.1% of the GDP and public debt is under 25% of the

GDP as stated by the Central Bank of Guatemala (Banguat, 2018). Even though inflation is low

(4.4% in 2017 in consonance with the World Economic Outlook Database- IMF), its business

climate has deteriorated. Regardless of its free trade agreements with the U.S. and the EU,

together with the geographic advantages and high potential for tourism, agriculture, mining,

hydroelectric and geothermal energy, Guatemala´s risk spiked anew with the current social

and political instability plus its poor infrastructure. In accordance with the risk assessment

done by Coface, ¨Guatemala is driven by external trade and private consumption besides

having weak fiscal revenues in the absence of reforms and is currently facing a very tense

political climate against a background of corruption¨ (2018).

Guatemala’s Currency

The Oxford Dictionary defines currency as the system of money in general use in a particular

country, being the asset that allows or facilitates the exchange of other goods and services.

Guatemala’s currency is the Quetzal and its currently valuated at around 7.3GTQ to 1$.

However, it has not always been like this. According to Guatemala’s currency’s historical

review, done by Banguat, the Quetzal was created as a new monetary unity in November 24th

of 1924. As a new currency, it was linked to the gold standard and in parity with the US dollar.

The entity in charge had to be created, it was called the central bank of Guatemala and it was

backed with mixed capital. Finally, by July of 1946, Guatemala’s economic-financial life had

begun.


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As it was stated, Guatemala’s exchange system was fixed. In this case, the monetary policy is

ancillary to the exchange policy and the adjusting variables are the international monetary

reserves (IMR). It remained this way, until 1985, where a regularization of convertibility

started, giving place to the liberation of the exchange rate in 1990. A free exchange system

implies that the relationship between national and international currencies is determined by

interaction in the currency exchange market. Now the exchange policy is subordinate to the

monetary policy.

In the process of going from a fixed exchange system to a free one, Guatemala chose a

managed floating regime. For this kind of management, authorities limit the exchange rate

fluctuations in the short run via interventions in the exchange market and by doing

adjustments in the monetary policy with no political compromise to a certain exchange rate.

This period of adjustment went from 1990 to 1998, in the sake of creating stable conditions

and eliminating potential prejudicial effects of excessive volatility. The exchange rate finally

stabilizes in between 1999 and 2000 at roughly GTQ7.7 to US$1.

Later on, in 2005, Guatemala’s Central Bank adopted an explicit inflation goal scheme. This

pursues to anchor inflationary expectations while maintaining a flexible exchange rate and

allowing to absorb external shocks by moderating the exchange rate volatility. Once

consolidated, the use of exchange regulation can be eliminated as long as the need of

intervention of the central bank in the exchange market minimize. More than 10 years later

the exchange rate remains very stable and is expected to continue that way (see Figure 2).

Collective Wisdom and Behavioral Finance

The concept of ¨Collective Wisdom¨ can be traced back all the way to Aristotle, who had the

idea that ¨If the many are not to be trusted, it remains true that many heads are better than

one¨ (Ryan, 2013). He is credited as the first person to write about the concept of the ̈ wisdom

of the crowd¨ in his work titled ¨Politics¨ (1952). The idea has now resurfaced in the words of


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modern authors such as James Surowiecki in the New York Times´ best seller: ¨Wisdom of

crowds¨, and later with Joseph Henrich in ¨The Secret of Our Success¨ in which he discusses

the term as ¨Collective Brain¨. Plenty of literature has arisen ever since, especially with its

connotations to business, management or finance.

Formally, collective intelligence is a form of consensus-driven decision making. It can be

described as a phenomenon of collective learning over time. As acknowledged by the authors

of the power of collective wisdom, ¨The potential of all groups and is marked by an experience

of deepening connections within ourselves, with each other, and to larger natural forces

involving nature, spirit, and our place in the cosmos¨ (Briskin, et al., 2009). In the same line,

Iain Couzin from Princeton University found a very particular example where a group solves a

problem that none of its members is even aware of. With this, he affirms that simply by

moving together, the group gains new abilities that its members lack as individuals (Couzin, et

al., 2018).

Nowadays, collective wisdom is easier since communication is broader than it was hundreds

of years ago. With the internet-based technological revolution of the past twenty years is

changing not only the way humans view and interact with each other and the world, but the

reality of human affairs itself. That’s why it’s a concept that can be applied to many other

sciences, like financial markets. Since the idea that large groups of people are collectively

smarter than even individual experts (when it comes to decision making) can certainly prove

itself useful when it comes to explaining what makes markets, in terms of its type of crowd

and its efficiency. In the end, and as it was pointed out before, that’s what behavioral finance

is, the study of how psychology affects finance decisions in the real world and not in theory.

According to Surowiecki´s definition, there should be a right set of circumstances for wisdom

to emerge. He explains that the group should be ¨Appropriately diverse, independent and

decentralized¨ (Surowiecki, 2005). According to Austrian economics, a free market should

have no entry barriers, and anyone should be able to, freely, get in or get out. It can be

assumed that it is going to be diverse, independent and decentralized. So, if market


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participants have those characteristics, placing the financial market per se under the right set

of circumstances, and their incentives are high enough; then markets should be efficient. It

also implies that investors (market participants) should be able to behave in a consistent way

with the market.

Foreign Direct Investment Data

The data used for the statistical analysis was retrieved from the world bank’s dataset (see

figure 3). The variable is called Foreign Direct Investment, net inflows (Balance of Payments,

current US$). It refers to the direct investment equity flows in the reporting economy. It is the

sum of equity capital, reinvestment of earnings, and other capital. The world bank defines it

as a category of cross-border investment associated with a resident in one economy having

control or a significant degree of influence on the management of an enterprise that is

resident in another economy. Its periodicity is annual, from 1997 to 2017. It is important to

note that the FDI does not include capital raised locally and it omits non-equity cross-border

transactions like intra-unit flows of goods and services.

Data on equity flows are based on balance of payments data reported by the International

Monetary Fund (IMF). The framework for direct investment relationships provides criteria for

determining whether cross-border ownership results in a direct investment relationship,

based on control and influence. FDI is made to establish a lasting interest in or effective

management control over an enterprise in another country.

Credit ratings background and definitions

The analysis includes the rating and forecast for Guatemala´s investment market by the firms

known as Standard and Poor’s, Moody’s, and Fitch. Credit rankings are usually used by

sovereign wealth funds, pension funds and other investors to gauge the credit worthiness of

every country and its believed to have a big impact on the country’s borrowing costs. Such

ratings vary in their scales of ̈ categories”. That’s why it was necessary to normalize the ratings


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by giving it a numerical equivalent, provided by the Trading Economics (TE) website (see figure

4). By using this, Guatemala’s historical ratings can be compared between the firms and the

proper analysis can be made. The forecast was also converted to a numeric way, being a +1

for positive, 0 for stable, and -1 for negative. For example, if the ranking was AAA for Moody’s

with positive outlook for the future, then its numerical equivalent would be 100 (AAA) + 1

(positive) = 101.

Statistical Data and Analysis

For the statistical analysis, it is vital to understand the relationship between the FDI and the

rankings, including the forecast. To do this, several different models were matched to evaluate

its validity. In addition, the speculative part of looking for the causes of the changes and

variations in the FDI were proved with correlations.

First of all, the Foreign Direct Investment was examined on its own to understand how the

variable works and to understand its fluctuation in time. The objective was to explain, as much

as possible, why it behaved the way it did in the last 20 years. According to Joseph L. Doob, in

probability theory, a stochastic process is a mathematical object defined as a collection of

random variables associated with points in time (Doob, 1953). There are certain common

causes of variation in all processes, especially those surrounding economic and political cycles.

These common causes are those that affect all outcomes related to the process, even if the

magnitude of such effects is different. These causes are part of the model and are, in some

way, expected to happen. For example, some irregularity in imports and exports due to

government change. In the other hand, there can also be special causes. These special causes

are factors that only affect one or part of the outputs of the process. These triggers are not

part of the model and are certainly not expected. For example, inflation in prices of

commodities as a consequence of an earthquake. Control limits are used to evaluate whether

the fluctuation was caused by a common cause or a special cause. If the flux remains inside


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the limits, then it was prompted by common causes; if it goes outside the limits then it was

produced by a special cause. These limits are determined by:

𝑅𝑀̅̅̅̅̅ = ∑|𝑌𝑡 − 𝑌𝑡−1|

𝑇

𝑡=2

And,

�̅� = ∑𝑌𝑡

𝑇

𝑇

𝑡=1

So,

𝑈𝐶𝐿 = �̅� + 2.66 ∗ 𝑅𝑀̅̅ ̅̅̅

𝐿𝐶𝐿 = �̅� − 2.66 ∗ 𝑅𝑀̅̅ ̅̅̅

That being said, a stable process is a type of stochastic process that includes stable probability

distributions. This means that the process its subject to common causes of variation and its

fluctuation lies within the limits of control and its behavior is somewhat predictable. This can

be measured with a control chart, also known as Shewhart charts, which are graphs used to

study how certain process changes over a period of time. According to Nancy R. Tague, control

charts have a central line for the average, and both the upper and lower limits. When a point

falls within the limits established, it is appropriate to determine if the results with the special

cause are better or worse than the results from common causes alone, and, consequently

eliminate the problem or purposefully retain the special cause.

In statistical quality control, this moving-range chart is called Shewhart individuals control

chart. It was originally proposed by Walter A. Shewhart, for data for which the normal

distribution is not assumed nor required in the calculation of control limits, thus making it a

very robust tool. Douglas C. Montgomery (2004) states that the ¨chart¨ consists in the display


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of the individual measure values and the moving range showing the difference from one point

to the next. This enables the user to monitor the whole process, looking out for shifts that

may alter the mean or variance.

The Efficient Market Hypothesis

Investors consistently try to beat the market in order to gain more money per transaction.

Yet, according to the efficient market hypothesis (EMH) such endeavor is impossible. In simple

terms, by the authors of ¨The Efficient Market theory and Evidence¨, the EMH theory asserts

that, at all times, the price of a security reflects all available information about its fundamental

value (Ang, et al., 2010). Thus, prices are averagely accurate and financial markets are

efficient. This means that if an investor happens to beat the market, it’s a consequence of

random processes since it should not be possible to either purchase undervalued stocks or

sell them for inflated prices.

The concept was formalized by Eugene Fama in 1965, by extending the argument using the

law of iterated expectations. He also defined three forms of market efficiency (Fama, 1970) -

the weak form, the semi-strong form and the strong form. The weak one implies that past

returns cannot predict future excess returns. The semi-strong one states that public

information cannot be used to predict future excess returns. Finally, the strong one stablishes

that no information can be used to predict future excess returns.


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Results

Guatemala´s Foreign Direct Investment Control Chart

Guatemala´s FDI has remained constant and within the limits for all but 1 year (2003), in the

lapse from 1997 to 2017. The average change in FDI its 72% and 𝑅𝑀̅̅̅̅̅ = 276%, with limits found

at 806% and -661%. Guatemala´s FDI is, therefore a stable process, which means that it is

statistically normal and that 99.73% of all points will fall between the control limits. The

special-cause variation present in the chart (point in 2003) requires further investigation

which will be discussed later on. Also, in regard to the chart, even though Guatemala´s FDI has

remained constant, its concerning that there is a tendency towards lower rates over the last

3 years. 2017 is drastically alarming as the FDI was reduced to less than half of the year before.

-1000%

-500%

0%

500%

1000%

1500%

2000%

Dat

e

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97

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98

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99

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00

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01

20

02

20

03

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Ch

ange

pe

rce

nta

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f FD

I

Shewhart Control Graphic

Cambio en inversion inversion promedio LSC

2s 1s -1s


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In this graph, it is possible to perceive certain tendencies of the FDI’s behavior through the

years while comparing its fluctuations with the updates done to the rankings by all three

agencies. The updates are in different colors, according to the agency and the new

qualification can be read on top of each line. As can be spotted in simple sight, the updates

seem to follow no particular trend and the change remains mostly unchanged after it.


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Correlations between Agency Ratings in its numerical equivalent and FDI

A series of correlations were done in order to study the relationship between the rankings´

behavior (independently) and the actual FDI. The first 3 regressions represent the relationship

between the ranking in its numerical equivalent with the net foreign direct investment of each

year (See figure 5 for value tables). Since the rankings are not updated periodically, the

numerical equivalent remained constant (yearly) until the moment of an update.

Regression Statistics Ranking S&P

Multiple R 0.35230289

R Square 0.12411733

Adjusted R Square 0.014632

Standard Error 0.69407166

Observations 10

Regression Statistics Ranking Moodys


R Square 0.13147704



Observations 10

Regression Statistics Ranking Fitch

Multiple R 0.590307

R Square 0.34846236



Observations 10

Correlations between numerical equivalent of the agency´s qualification and the FDI


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Data from (World Bank, 2015)

In keeping with Dawn Porter and Damodar Gujarati´s explanation, in statistics, the coefficient

of determination (R squared) is the proportion of the variance in the dependent variable that

is predictable from the independent variable (Porter & Gujarati, 2008). In line with this, it is

evident that there exists very low correlation between the variables previously explained. The

largest R square was obtained by the agency Fitch, with a total of 34.8% of the variations (in

FDI) being explained by the independent variable (ranking). This implies that the market is

influenced very little by the ratings and that its significantly affected by other factors.

The next set of regressions was made with the outlook in numerical form against the net

amounts of FDI. Once again, since the rankings nor the outlooks are updated periodically, the

numerical equivalent stayed constant (yearly) until the next update (see figure 6 for values).


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Regression Statistics Outlook S&P


R Square 0.12411733



Observations 10

Regression Statistics Outlook Moodys


R Square 0.62358238



Observations 10

Regression Statistics Outlook Fitch


R Square 0.348462359



Observations 10

Correlations between numerical equivalent of the agency´s outlook and the FDI

Data from (World Bank, 2015)

Even though we obtained higher R squares, it is still quite low and would explain just a small

portion of the total investments. This means that while outlooks are quite better at explaining

the market’s reality, it is still too low to consider the agency’s ranking a major factor when


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deciding where to invest. This can be considered a starting point in the search for solid

evidence that proves the initial thesis.

Discussion

Guatemala´s Foreign Direct Investment Control Chart

Although many factors might have influenced the variations observed from 1997 to 2003, it is

strongly supposed that the Hurricane Mitch abruptly initiated the fall in the FDI market.

According to local news reports, Hurricane Mitch was one of the deadliest in Central America.

As communicated by the preliminary report, due to the significant damage to agriculture and

municipal infrastructure, it is estimated to have costed US$750 Million (Consultative Group

for the Reconstruction and Transformation of Central America, 2000). Also, since Guatemala´s

economy is greatly influenced by that of the United States, it is also speculated that the Enron

scandal and its economic repercussions could have also partially swayed the fall. Then, it is

important to recall the exchange rate had just finished stabilizing. Following that, in 2002, the

law for banks and financial groups was implemented (Super Intendencia de Bancos -SIB, s.f.),

which, allegedly, helped in the recovery of the national economy and led it towards the new

inflation goal scheme that was adopted in 2005. Such law was needed mostly to regulate all

related to creation, organization, fusion, activities, operations, suspension of operation and

liquidation of banks and financial groups. By last, it is imperative to remember that this is pure

speculation and that there is no way to know with 100% certainty what caused the fall and its

latter recovery.

Correlations between Agency Ratings in its numerical equivalent and FDI

The correlations were not conclusive, which supports the initial thesis stating that collective

wisdom does exist among investors. This means that most of said investment decisions are

affected by other aspects rather than the different ratings. However, this paper only provides

some indications that the hypothesis is correct. Therefore, it should also imply hints


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supporting the validity of the Efficient Market Hypothesis in this particular case. Nonetheless,

it seems appropriate to continue with further analysis since this can be interpreted just as

initial hints towards something more significant. Similarly, it’s important to consider the

possibility that the rankings actually take into consideration observable trends and are, hence,

consequences of the market´s fluctuation per se.

Conclusions and Recommendations

Guatemala´s economy has proven to be somewhat stable and to fluctuate within normal

limits. While it’s true that there have been a lot of political crisis, the economic panorama

seems to remain unbothered. Throughout the series of analysis done, valid evidence is shown

that rejects the null hypothesis; thus, providing proof towards the existence of collective

wisdom within the financial agents in the foreign direct investment´s market. The correlations

also give the impression that such collective wisdom is superior to the agency´s qualifications

when it comes to accounting for the FDI´s variations. It is clear that investors take other factors

into account when deciding when and where to invest. With this, signs validating the efficient

markets hypothesis can also be found in the prices of the stock markets. Since all the

information needed is aggregated and reflected by the price, then the rankings are impractical

as they cannot provide any more insight about the market.

It is worth mentioning that at any point in this investigation, the analysis done are subject to

certain level of speculation. The agencies and their rankings were not subject to any further

investigation, subsequently it still remains unknown how such rankings are calculated or to

what factors they are linked. For all its known, rankings could study trends and act upon what

was observed in market trends, thus relying in the crowd’s wisdom.

Similarly, its recommended to study analogous scenarios and compare behaviors amid

different markets in similar countries, such as Honduras or El Salvador, and contrast with more

stable and growing markets like Panama´s in Central America. Also, it is strongly

recommended to add complementary sentiment analysis around investors in different


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moments in the FDI´s market, since it was not taken into consideration for this paper´s focus.

Finally, it’s important to consider the possibility of mere coincidences within the market and

its variability´s factors and perhaps there is a more significant one that has not been pointed

out yet.

Appendix


22

Figure 1

Guatemala’s Historical Changes in Ratings

Obtained from (IEconomics, 2017)


23

Figure 2

Guatemala’s Exchange Rate’s fluctuation from 1990-2015


24

Obtained from (Trading Economics, 2018)

Figure 3

Guatemala’s FDI from 1995-2016

Obtained from (The World Bank, 2017)


25

Figure 4

Numerical Equivalent to Ratings

Obtained from (Trading Economics)


26

Standard & Poors Moodys

Fitch

Figure 5

Table of the FDI per year and the numerical equivalent ratings


27

Standard & Poors Moodys

Fitch

Figure 6

Table of the FDI per year and the numerical equivalent ratings


28

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