Sistema Regional de Información
en línea para Revistas Científicas de América Latina,
el Caribe, España y Portugal

This study investigates factors influencing e-money adoption among Generation Z in rural Indonesia, a demographic vital for financial inclusion. Employing a modified Unified Theory of Acceptance and Use of Technology (UTAUT) framework, data from 208 rural Gen Z respondents were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Key findings reveal social influence and effort expectancy significantly drive e-money usage, while performance expectancy does not. These results highlight the need for tailored strategies by fintech providers to foster digital payment adoption, particularly by strengthening community engagement and enhancing user-friendliness. The study offers novel insights into consumer behavior in underserved areas, with implications for financial inclusion policies. Future research should expand sample size and geographical scope.

Savings for emergencies, inclusion and financial education in MexicoThe aim of this research is to analyze the relationship between knowledge, education and financial inclusion of Mexicans and the owning of savings accounts for emergencies. The sociodemographic and financial determinants of savings accounts for emergencies are identified. For the analysis, the dichotomous Probit model is used with data from the 2018 National Survey of Financial Inclusion. Results show that financial knowledge, owning a financial accounts, financial training and owning physical assets have a positive effect on holding savings for emergencies. Holding a savings account is the most important predictor, whose effect on the probability of holding savings for emergencies is 12.96%. The people most likely to have an emergency fund are men, elderly, married, with a higher level of education, from an urban location, and those with few dependents. The findings may be useful for the design of financial education strategies that make it possible to enhance access of population to short-term savings products.

The objective of this research is to determine the constructs of regret, pleasure and purchase frequency of an art consumer. A Partial Least Squares and Structural Equations methodology was used for their virtues as second-generation models. The results show that regret bias was statistically explained through financial motivation, passion for art, and alternative offers; therefore, people may have feelings of regret or anxiety due to the fear of missing out on an opportunity by not buying a work of art, as well as that passion for art was an exogenous variable influential in the explanation of loss-regret, the pleasure, and frequency of purchase. The limitation of the research is the subjectivity, historical context, culture of the sample used, the historical context the implications of studying art as an alternative asset are that it improves the culture of investment and the market. The research takes an original approach since it studies a behavioral finance bias such as regret and what determines the passion for art.

Financial Engineering and Optimal Portfolios with Regime Switching The work aims to apply a first order Markov regime switching model with multivariate α-stable distributions to optimize portfolio selection by estimating the model parameters using time series of the logarithmic returns of the daily prices of the ipc and naftrac to detect market regimes. The model captures asymmetry and leptokurtosis in each regime, identifying with the appreciated and depreciated regimes, demonstrating the model's effectiveness in reflecting the dynamics of the Mexican financial market. It is suggested to apply the Markov regime switching model in portfolio management to improve diversification, risk management, and for continuous risk assessment under different market conditions. The model assumes homogeneity in the transition parameters between regimes, which is not entirely realistic, so it is necessary to include adaptations for specific contexts and consider other macroeconomic factors. The originality of the work lies in the integration of multivariate α-stable distributions with Markov regime switching, providing a tool for financial risk management. The study concludes that the proposed model is effective in capturing the statistical characteristics of returns in different market regimes, significantly contributing to the field of financial engineering and portfolio management.

Portfolio Selection: A Behavior Biased ApproachHere the goal is to provide optimal financial portfolios based on a normal likelihood, an a priori distribution on the parameters of the asset valuation model, and the investor's opinion on how to weigh likelihood and a priori in portfolio construction. The biased Bayesian inference methodology is applied to the selection of mean-variance portfolios, with different bias or weighting configurations. The results show an effective proposal to find optimal portfolios that reflect weightings made on likelihood and a priori beliefs. In addition, including biases in portfolio selection can be relevant to portfolio optimization. The proposal contributes to the field of behavioral finance biases and can be easily applied to other financial models that have been treated from a Bayesian approach. In conclusion, the proposal provides optimal weights for the portfolio that reflect both data and beliefs, and the inclusion of biases in portfolio optimization can help build optimal portfolios that incorporate risk preferences and investment objectives.

The objective is a methodology for weighting financial assets in an investment portfolio. It is contrasted by the components of the Dow Jones Industrial Average (DJIA). For this purpose, portfolios with investment horizons between 1 and 2 years are studied using Long-Short Term Memory (LSTM) optimization. The best portfolio was with an investment horizon of 1.5 years. The neural network is trained with 1,000 observations and more than 2,777 portfolios are simulated. The model outperforms the DJIA by 73% to 85%, with a geometric mean annual return differential between 3.7% and 5%. The components of the DJIA in history are used to allocate assets to portfolios between 2008 and 2021. It is recommended that the methodology be contrasted in conjunction with another methodology for selecting financial assets. The conclusions are limited to assets that make up the DJIA. Mostly in the literature, neural networks are used for the short term; this paper contrasts the model to the long term, seeking to weigh assets and not future asset prices. The conclusion is that the LSTM model can be used for this purpose, for investment horizons of 1 to 2 years.

Macroeconomic effect on consumer loan delinquency and its impact on bank profitability in MexicoThe objective of this research is to determine the sensitivity of the delinquency rate (IMOR) of consumer credit to some macroeconomic variables and its impact on bank profitability in Mexico. Elliptical copulas were used to achieve this. The results show that during the period 2011 to 2023 there was a positive relationship between unemployment and interest rate with the IMOR consumption, and a negative one between inflation and the exchange rate with the aforementioned index. It is also shown that the increase in consumer delinquency does not have a significant impact on banks' profitability. The originality of the analysis lies in identifying the variables that have the greatest influence on delinquency, proposing a methodology that does not assume linearity and offering empirical evidence to support the generation of economic policy proposals. It is concluded that the unemployment and the interest rate have an important influence on delinquency. Future research will consider analyzing other segments of the credit sector and their relationship with default.

Proposals to Transfer Risks in Avocado LoadThis study aims to mitigate some risks faced by established avocado industry actors in Michoacan by transferring risks from orchards to packaging facilities and distribution points. Using stochastic dynamic games and Merton-Black-Scholes theory, the study aims to maximize the long-term market share of packing house owners in the state in the presence of organized crime. To the best of our knowledge, this is the first time these methods have been used to this end. The premium to be paid in exchange for property rights over turnpikes is defined. Packaging facility owners are recommended to build a branch office in strategic locations to reduce organized crime control. At the same time, the paper suggests highway concessionaires issue insurance against theft of goods and finance it through the proposed procedure. The study includes cost-benefit sketches from both pecuniary and environmental perspectives but acknowledges that a thorough analysis requires knowledge of the local entrepreneurs’ willingness to implement green actions.

An evaluation of the 4% withdrawal rule for pension savings in MexicoObjective: Evaluating the 4% withdrawal rule for personal pension saving funds in Mexico. Methods: Simulations based on the distributions of monthly real returns of assets and bonds (1989-2023). Results: Monte Carlo simulations indicate that the risk of failure (that is, exhausting the funds before 30 years) is minimized by investing only in bonds. However, investing in assets is required to maximize the probability of achieving a final fund balance goal. Recommendations: If the person wants to keep 50% of the initial fund balance after 30 years of withdrawals, then it is optimal to allocate 10% of the fund to stock and the rest to bonds. This strategy implies a small probability of failure (0.02%), and, in the worst-case scenario, the fund lasts 29 years. Limitations and implications: Simulations do not consider fees and taxes. Hence, investors should be cautious. Originality: The results contradict findings from the only previous study about Mexico. Conclusions: It is relatively safe to follow the 4% rule in Mexico, allocating a small fraction of the fund to assets.

La regeneración de plantas de jojoba (Simmondsia chinensis) puede lograrse mediante micropropagación in vitro y por estacas. En medio Nitsch y Nitsch(1969) modificado con 0,01/0,5/0,4 mg/1 de ANA/BA/AG3 respectivamente,se consiguió brotación de un 60% de segmentos polinodales cultivados, mientras que en secciones nodales, usando 0,3/0,1/0,01 mg/I de ANA/BA/AG3 se formó callo en un 100% y se regeneraron plántulas en un 25%. Secciones de lámina foliar cultivadas con 5 mg/1 de ANA y 0,1 mg/1 de BA, iniciaron tejido no organizado (callo), especialmente en la superficie adaxial de la hoja, alcabo de 30 días. Transcurridos 60-80 días desde la inducción de callo, se inicia la diferenciación de raíces. En tratamientos con solo 0,5 mg/I de BA se obtuvo la formación directa de brotes en la porción basal de la lámina foliar.La propagación por estacas mostró que tanto AIB como otras auxinas pudieron inducir raíces en porcentajes de 8% a 56%, no obteniéndose respuestas en controles sin hormonas.El tratamiento en medio sólido resultó ser significativamente mejor que enmedio líquido (Ps 0,01) para el arraigamiento de estacas.