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2022 | Buch

Financial Technologies in the Emerging Markets Kapitel lesen Erstes Kapitel lesen

Data Analytics Applications in Emerging Markets

herausgegeben von: José Antonio Núñez Mora, M. Beatriz Mota Aragón

Verlag: Springer Nature Singapore

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Wirtschaft" , Springer Professional "Technik"

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Über dieses Buch

This book analyzes the impact of technology in emerging markets by considering conditions and the history of how it has changed the way of working and market development in such contexts. The book delves into key areas such as fintech enterprises, artificial intelligence, pension funds, stock markets, and energy markets though applied studies and research. This book is a useful read for practitioners and scholars interested in how technology has and continues to change the way in which development is defined and achieved, particularly in emerging markets.

Inhaltsverzeichnis

Frontmatter
Financial Technologies in the Emerging Markets
Abstract
Innovations in financial technology are probably the most meaningful milestone in human development of the twenty-first century. The reasons vary, from user convenience to financial inclusion in rural areas where access to a bank account was utterly precarious. Financial technology has transformed the way users interact with their financial institutions, and these new interactions are the subject of study by academics and practitioners. The asymmetries of technology worldwide have caused fintech to develop at different speeds in each geography; for this reason, this chapter covers development in emerging markets and the impact of their presence on the economy and infrastructure of these markets. Authors review this market’s demographic profile and the challenges of adopting the implicit technology in fintech developments. Finally, due to its importance in the fintech scene, the state of the Mexican ecosystem is reviewed, and the impact of regulation on financial technology, highlighting how legal provisions shape this market that continues to innovate.
Pamela Soledad Moncayo Mejia, Pilar Madrazo Lemarroy
Financial System: Challenges and Opportunities of Digital Transformation in Mexico
Abstract
This work aims to understand the implications that financial technology represents for the Mexican financial system. Considering that the adoption of new technologies in the financial system (Fintech) is increasing, a novel and complex context has arisen with diverse implications in various aspects such as education, infrastructure, and the regulatory and supervisory framework needed to ensure a healthy development of the financial system. Although it has been shown that digitization brings various benefits, such as sustainable development, improvement of financial and social conditions by its impact on financial inclusion, and providing alternative sources of finance to firms, it also bears significant challenges both for telecommunications infrastructure, as well as for the authorities in the search for a flexible regulation that provides protection to both the financial system and its users without stiffening financial innovation.
Vanessa Veintimilla Brando, Daniel Miranda Lopez
Machine Learning Models, Risk Management Current Regulation and Perspectives
Abstract
Current machine Learning techniques spreading in banking and quantitative finance brings issues to be face by risk management and financial institutions regulation. The former increases models predictive power but at the same time makes models more complex and has to struggle to better explain the role, weight and direction of explanatory variables in the outcomes as well as the sensibility of the result to changes in the feature, different technics have been developed to deal with this problem but there are still important tasks to be completed. On the other side the later has found that the use of internal models as regulated in early Basel regulation stages (Basel II) foster the risk sensitivity for regulatory capital allocation but may lead to undue complexity and so reducing comparability among banks risk. The regulatory response in Basel IV regulation has been to discouraged the use of internal models to reduce the impact of undue complexity in models to improve regulatory capital comparability in the banking system. This is the environment that machine learning models for regulatory purposes have to deal with.
Jose Juan Chavez Gudiño, Jose Antonio Nuñez Mora
Financial Emerging Markets Revisited
Abstract
This chapter analyzes the financial markets of the economic group MIST (Mexico, Indonesia, South Korea, and Turkey) by studying the ETFs related to these countries. The previous economic group is crucial because it has the potential of becoming a leading participant in emerging markets. The document examines their financial time series by identifying outliers, volatility models, time series decomposition, and detecting mildly explosive processes (“financial bubbles”). The results obtained show significant negative outliers, non-constant volatility, and the identification of five exuberant behaviors in Mexico’s ETF.
Carlos Armando Franco Ruiz, Guillermo Benavides Perales
Disruptive Monetary Phenomenon, Challenges and Complexities (Cryptocurrencies)
Abstract
The present document develops on the presence of cryptocurrencies on Latin America. It begins with the explanation of the world scenario that incentive the born of the Bitcoin as an alternative to fiat currencies, as well as the main reasons the financial institutions over the world have attacked it over the years. The main functionality is summarized as the main argument of the supporters as a secure, transparent, and decentralized asset. Later the general conditions of under-development in Latin America are presented: corruption in the governments, increasing socioeconomic gap and migration. Under this stage, the possibility to incorporate cryptocurrencies is explored by pointing the aid to the previously discussed conditions. In this aspect, the advances of the acceptance of cryptocurrencies as money among some countries is briefly explored. Finally, a discussion on the risk and benefits of cryptocurrencies is presented to explain the volatility with a lack of international regulation.
Mario Ivan Contreras Valdez, Daniel Cerecedo Hernandez
Pension Funds in Emerging Markets: A Projection of Mexican Pension Assets
Abstract
The defined contribution pension scheme promoted by the World Bank in the mid-1990s brought an increase in the number of institutional investors within the financial markets of countries that implemented this new system. The World Bank considered that pension funds in developing countries would positively impact them. This is how it becomes increasingly important for pension funds to have more tools and models that allow them to optimize their portfolios according to their needs. Following the introduction of machine learning models, long-term portfolio management has changed, as these large institutional investors have now found a way of managing their portfolios that seems to be more tailored to their needs, compared to the models that were used, emerged from financial theories. In Mexico, the demographic and financial projection allows us to see that if this growth trend in the SAR continues, and the investment regime remains unchanged, by 2050 the resources could require around 7.4 trillion Mexican pesos of government securities outstanding (1.11 times the current total value) and 4.9 trillion of equity securities outstanding (about 60% of the current total value).
Martha Angelica Leon Alvarado, M. Beatriz Mota Aragon
Relationship Between Economic Growth and Oil Production in Emerging Countries for the Period 2020–2050
Abstract
An algorithm of dynamic programming in Montecarlo simulation is developed to analyze the international oil market towards the year 2050. The leading oil exporters are considered, and it is found that the positive relationship between economic growth and oil production will go decreasing. The model suggests that the combination of renewable energies, oil, natural gas, and others will be the variable that will influence economic growth, where oil will no longer be the main actor.
Leovardo Mata Mata, Jaime Humberto Beltran Godoy
Hedging and Optimization of Energy Asset Portfolios
Abstract
Hedging and optimization techniques are useful tools to manage the levels of risk of portfolios. These tools in energy markets are highly recommendable due to their sizes and volatilities. This study uses stock share prices of oil and gas companies of Latin America and other regions and two future contracts for oil. The study proposes the selection of minimum risk portfolios and the calculation of efficient frontiers using different risk measures, one of them coherent. The price return series are transformed into new series to improve granularity and gain extension. Conditional risk measures are calculated through simulation using Gaussian and Extreme Value functions and Copulas-t. We apply non-linear programming techniques to find optimal hedging portfolios and efficient frontiers with the new series and the simulated conditional risk measures. Finally, we comment on using Machine Learning as an alternative way to help solve the proposed problems.
Roberto R. Barrera-Rivera, Humberto Valencia-Herrera
Artificial Intelligence and Its Application in the Study of the Legal Complexity of the Value Added Tax Act in Mexico
Abstract
The text is a raw material, researchers need to extract information and patterns of value. Through the use of AI tools in conjunction with the hard sciences, it is now possible to access significant sources of knowledge that previously remained hidden in the form of patterns of ideas and feelings stored in large volumes of text. The analysis of the raw text of the Law of Value-Added Tax (VAT) considered the three elements: structure, language, and interdependence. With these three elements, a legal complexity index was constructed, and the results of the model’s parameters show the following: the value for the legal complexity variable was negative (−1.39), which means that when the legal complexity index per unit increases, tax collection will decrease 1.39%. It is helpful to remember that interdependence is the component that outweighs the rest within the legal complexity index. The GDP estimator showed a positive sign, and its magnitude was 4.51; this means that when this estimator increases 1%, VAT collection could increase a 4.5%.
Javier Moreno Espinosa, Alonso Carriles Alvarez
Metadaten
Titel
Data Analytics Applications in Emerging Markets
herausgegeben von
José Antonio Núñez Mora
M. Beatriz Mota Aragón
Copyright-Jahr
2022
Verlag
Springer Nature Singapore
Electronic ISBN
978-981-19-4695-0
Print ISBN
978-981-19-4694-3
DOI
https://doi.org/10.1007/978-981-19-4695-0

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