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

This article studies the econometric modeling and the projection of growth rates of the nominal exchange rate (Peso/Dollar) from 1995 to 2018. Applying Bayesian simulation methods, the best data modeling fit between linear and non-linear econometric approaches is studied by introducing Markovian regime change parameters. The Bayes factor for model selection provides the following evidence: in the analysis of daily growth rates there are periods with low, medium, and high volatility. In the monthly rates, changes were also found in the mean and the volatility of the process. The linear autoregressive econometric model is not supported by the data in any case. Furthermore, instead of structural changes in these rates, evidence of state-dependent parameters is present. The high volatility in both data frequencies coincides with the sub-prime crisis in 2008-2009, but also with other sample periods. Moreover, an optimal weighting approach is applied to Markovian regime change models to study forecast errors in the sample. From this exercise, the forecasting errors of the exchange rate growth rates are lower than those of the linear autoregressive model. Finally, the out-of-sample errors of regime change models and optimal methods, in most cases, exceed those of linear inferences in both data frequencies.

(Yield and volatility of Mexican stock and foreign exchange markets)It analyses the relationship between the yields of the Mexican stock market and the yields (appraisal rate) of the US dollar, as well as the relationship between its volatility. The evidence in this regard, including at the international level, is inconclusive. The analysis is carried out using the coping methodology, which are selected based on the Akaike and Schwarz information criteria. Volatility was estimated by asymmetrical GARCH models with time-variant parameters according to a Markovian change process. Evidence suggests that stock and exchange dynamics are not always associated, but there is an association between stock returns and the appreciation/depreciation of the peso against the dollar and a positive association when volatility is high in both markets. An obvious consequence is that exchange rate risk can be a significant risk to stock trading, as conventional financial theory assumes, so while it is not possible to establish that stock and exchange dynamics are always associated, it is should establish stock investment policies considering such a risk. The originality of the work is that taking into account the presence of non-linearities and absence of normalcy that exist at the extremes of the bivariate distributions of odds of depreciation-stock returns, as well as volatilities (risks) in both markets, using asymmetric copulas, it contributes to the explanation of mixed evidence on the issue of co-integration or long-term relationship (balance in the stable state) between the stock market and exchange.

This paper aims to build a set of algorithmic trading strategies to capture the persistence of financial series. HUELUM Trading System is proposed to make algorithmic trading in a low-frequency environment and is tested with the Exchange Traded Fund (ETF) iShares NAFTRAC daily prices. HUELUM Trading System includes one mean and one trend technical analysis indicators which are compared to a buy & hold strategy as a benchmark. The strategy's implementation is recommended for moderate-high risk profiles and positions with short-term horizons (days or weeks). The principal contribution of this work is that HUELUM Trading System can adapt to NAFTRAC, capturing its behavior, trends, and persistence or momentum. HUELUM is validated through a rolling walk forward and works with any security as long as it has Open, High Low Close (OHLC) prices. When we are in a market with little liquidity and deepness, HUELUM gives accurate buy and sell signals compared to a buy & hold strategy and reduces potential equity losses.

El objetivo del presente trabajo es examinar las oportunidades de diversificación productiva y de emprendimiento que derivan de las capacidades existentes y potenciales con las que cuenta específicamente el estado de Hidalgo. Para ello, se desarrolló un estudio empírico haciendo uso del Método de Reflexiones (MR) y la asignación de ponderadores, con base en las variables de la Teoría de Complejidad Económica propuestas por Hidalgo & Hausmann (2009) y recopiladas del Atlas de Complejidad (2018). A partir de las operaciones algebraicas, se halla en un primer momento que el estado de Hidalgo se encuentra actualmente ubicado en el cuadrante que refleja: “mayor diversificación promedio con mayor ubicuidad promedio”. En un segundo momento, la estrategia balanceada de ponderación, logra generar un ranking de oportunidades que puede ser útil para argumentar modificaciones en materia de política industrial y también para orientar y validar proyectos productivos de emprendedores, empresarios e inversionistas en la región. Una limitación del trabajo es que se basa sólo en datos provenientes de la economía formal-industrial y su originalidad radica en que no existen estudios previos en el contexto analizado.

Comparative Analysis of the Semi-parametric Estimation Methodologies and Copula Estimation in Value at Risk (VaR) in the Colombian Stock MarketThis research article illustrates different types of statistical methodologies with the objective of making an adequate estimate for value at risk (VaR), implementing the use of semi-parametric methods and a flexible class of copulas named VineCopulas. It was found that it is possible to explain volatility and dynamic market movements in estimation techniques by including the management of complex patterns of non-linear dependence in the modeling of financial assets. The flexibility of the models presented with the use of copulas and semi-parametric methodologies, such as quasi-maximum likelihood estimate (QMLE) and extreme value theory (EVT), allowed the adequate estimation of VaR in the Colombian equity market.

El objetivo de este trabajo es examinar los efectos de la comunicación del banco central sobre los errores de pronóstico de inflación para Colombia en el período 2008 – 2016. La metodología empleada consiste en un análisis econométrico compuesto por: i) La estimación de un modelo EGARCH; ii) El uso de Vector Auto regresivos (VAR); y iii) Un análisis de descomposición de varianza. Los resultados del trabajo muestran que los anuncios de política monetaria generan efectos importantes sobre los errores de pronóstico. La principal recomendación de política es que la comunicación es una herramienta que tiene el banco central para reducir los errores de pronóstico. En particular, la comunicación tiene el potencial para lograr una convergencia entre las expectativas de inflación y los objetivos perseguidos por el banco central. La principal limitación está relacionada con la falta de información más desagregada sobre las expectativas de inflación que no permiten analizar su reacción ante diferentes noticias macroeconómicas. La originalidad del trabajo consiste en analizar los errores de pronóstico de inflación con base en la inflación compensada de los títulos de deuda pública.

(Cost of electric generation accounting for environmental externalities: Optimal mix of baseload technologies)Abstract. This paper aims to calculate the Total Levelized Cost of Generation with Externalities (CTNGE, in Spanish) of three baseload technologies: coal thermoelectric, combined cycle and nuclear power plant. Monte Carlo simulation is used to estimate the CTNGE probability densities. The portfolio theory is used to find the mix of technologies that provides the least risky CTNGE and with the lowest average. We find that the nuclear power plant has the lowest CTNGE. The coal-fired thermoelectric plant is the technology with the largest and riskiest CTNGE. The analysis suggests that, when generating electricity, it is convenient to leave out the coal-fired thermoelectric plant and focus on two technologies: combined cycle and nuclear power plant, assigning a higher participation to the latter. One limitation of the work is that the probability densities of the CTNGE estimated through the Monte Carlo simulation depend on the data used. The present analysis suggests that the CTNGE can be significantly modified by including the cost of CO2.

The purpose of this article is to examine the strategic relationship between trade policy in a managed protection regime and commercial exchange at prices below normal value. It presents a three-stage model of imperfect competition that incorporates the possibility for the government authority to influence the production decisions of companies through a credible threat, by means of a specific tariff. This methodology—in a context of segmented markets, Cournot conjectures, and the application of an optimal tariff—generates a mechanism of incentives (which are not sufficient from a social welfare perspective) for domestic and foreign companies to practice reciprocal dumping. A general conclusion is that a free trade policy would be counterproductive, since it would eliminate the incentives that domestic and foreign companies would have to carry out the commercial exchange that would diminish the loss of welfare associated with the existence of monopolies in both markets.

En el presente trabajo se estudia el empleo de modelos markovianos con cambio de régimen (Markov-Switching, MS) de dos regímenes. Estos con varianza constante, ARCH o GARCH, así como con probabilidad gaussiana o t-Student. Los mismos se utilizaron para administrar activamente portafolios en los mercados accionarios andinos (Chile, Colombia y Perú). Al simular 996 semanas de enero del 2000 a enero del 2019, se ejecutó la siguiente estrategia de inversión en dólares de los EEUU: 1) invertir en el activo libre de riesgo si la probabilidad de estar en el régimen de alta volatilidad en t+1 es mayor a 50 % o 2) invertir en el índice accionario en caso contrario. Los resultados sugieren que emplear modelos MS-GARCH gaussianos es lo mejor para la administración activa en el mercado chileno, que el modelo MS-ARCH gaussiano lo es en el colombiano y que es preferible la administración pasiva en Perú.