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Gigante-1A (G-1A) is a well that is located in Upper Magdalena Valley in Colombia, South America. It has been producing for almost 10 years today. There are several wells in this area that have been producing from sandstone and carbonate/dolomite reservoirs at different depths for more than 30 years and are still drawing interest from producers. There is a high interest in new well construction based on experiences from G-1A related to drilling, completion, production stages, reservoir analysis with stimulation techniques, and response-related identification of formation damage. A second well at the same depth is currently in progress. The specific condition of water, oil, and gas flowing commingled to surface from the same zone, covering sandstone and carbonate formations with significant petro-physical differences and reservoir fluids has allowed for the establishment of best practices and identified areas of research to get improved responses. A continuous learning curve focused on improving operational procedures and placement techniques has been built according to the mechanical status of the well before each intervention. Periodical interventions focused on organic deposition, emulsion blockage damages, and scaling related problems have helped to establish operational and treatment design procedures which contribute to effective stimulation results. Continuous improvements related to chemical treatment designs, based on adjustments of formulations, radius of penetration, and placement techniques, have helped to ensure effectiveness. Chemical treatments have focused on organic, nature-related problems since the beginning. In particular, asphaltenes flocculation, have generated pore throat blockage because of asphaltenes deposition and emulsion blockage. Water cut increase over time has brought inorganic scaling problems. Corresponding solutions have been combined with organic stimulation treatments for removal and damage inhibition overtime. There is also a clear learning curve over the last seven years on well lifting in optimizing well production in conjunction with chemical treatments to maximize oil production. Introduction G-1A is geographically located southern department of Huila, about 26 kilometers southeast of the municipality of Gigante. This HPHT well produces from Tetuan formation, where it was completed in May 1998 for the perforated interval 15,372 to 15,430 ft, in 5-in. Liner N-80, 18#/ft, hung at 14,956 ft. 7-in. casing P-110 29#/ft, from surface to casing shoe at 15,349 ft. The target zone in G-1A well in particular combines sandstone and limestone interval lengths along the perforated interval, where the bottomhole reservoir temperature has been identified as 268.5° F. A summary of current downhole conditions according to the most recent production report has been compiled in terms of well characterization related to main reservoir properties, formation fluid data, and current artificial lifting system (Table 1). G-1A has been periodically stimulated for almost eight years after confirming oil reserves through openhole log analysis, reservoir studies, hydraulic fracturing responses previous a blowout in 2000, PBU indications, and nodal analysis after blowout. Formation damage has been considered since the beginning of stimulation treatments after blowout. The blowout was a critical event during well history since a significant impact was made on the mechanical configuration at downhole conditions. Consequently, water reservoir communication has been highly estimated.

Determinación de un portafolio de referencia para las SIEFORE Básicas a través de un modelo de riesgo-rendimiento que optimiza la tasa de reemplazo Determination of a reference portfolio for the Siefore Básicas through a risk-return model that optimizes the replacement rate Resumen: El sistema pensionario en México opera actualmente a través de cuentas individuales en donde el trabajador, el patrón y el gobierno aportan un porcentaje del salario a la cuenta de cada afiliado. Estos recursos son invertidos en diversos instrumentos financieros a través de Sociedades de Inversión (SIEFORES). El objetivo del estudio es elaborar un portafolio de referencia para cada una de las cuatro SIEFORE Básicas, incorporando activos y pasivos de largo plazo, para optimizar las inversiones del portafolio, con el fin de lograr la máxima tasa de reemplazo posible. Los resultados convergen a portafolios más conservadores que los que actualmente administran las SIEFORE. El portafolio de referencia obtenido asigna un bajo porcentaje a instrumentos de renta variable y un mayor peso a instrumentos de renta fija, la optimización elige también portafolios con instrumentos de menor plazo, 3 y 5 años, sobre instrumentos de más largo plazo. n Palabras clave: AFORE, pensiones, portafolio de referencia, renta fija, renta variable.n Clasificación jel: H75, J26.n Abstract: The Mexican system of pensions nowadays works through individual accounts, where the employee, employer and the government give a percentage of the wage to the individual account of the worker. The resources are invested in different financial instruments trough Investment Societies (SIEFORES). The objective of the paper is to construct a benchmark portfolio for each of four Basic SIEFORE, which permits incorporate the existence of long-term assets and liabilities to optimize the investments of this benchmark portfolio and to obtain the biggest replacement rate. The selected benchmark portfolio in the model assigns a

Transfer Entropy was applied to analyze the correlations and flow of information between 200,500 tweets and 23 of the largest capitalized companies during 6 years along the period 2013-2018. The set of tweets were obtained applying a text mining algorithm and classified according to daily date and company mentioned. We proposed the construction of a Sentiment Index applying a Natural Processing Language algorithm and structuring the sentiment polarity for each data set. Bootstrapped Simulations of Transfer Entropy were performed between stock prices and Sentiment Indexes. The results of the Transfer Entropy simulations show a clear information flux between general public opinion and companies’ stock prices. There is a considerable amount of information flowing from general opinion to stock prices, even between different Sentiment Indexes. Our results suggest a deep relationship between general public opinion and stock prices. This is important for trading strategies and the information release policies for each company.

PurposeThis paper tests the accuracies of the models that predict the Value-at-Risk (VaR) for the Market Integrated Latin America (MILA) and Association of Southeast Asian Nations (ASEAN) emerging stock markets during crisis periods.Design/methodology/approachMany VaR estimation models have been presented in the literature. In this paper, the VaR is estimated using the Generalized Autoregressive Conditional Heteroskedasticity, EGARCH and GJR-GARCH models under normal, skewed-normal, Student-t and skewed-Student-t distributional assumptions and compared with the predictive performance of the Conditional Autoregressive Value-at-Risk (CaViaR) considering the four alternative specifications proposed by Engle and Manganelli (2004).FindingsThe results support the robustness of the CaViaR model in out-sample VaR forecasting for the MILA and ASEAN-5 emerging stock markets in crisis periods. This evidence is based on the results of the backtesting approach that analyzed the predictive performance of the models according to their accuracy.Originality/valueAn important issue in market risk is the inaccurate estimation of risk since different VaR models lead to different risk measures, which means that there is not yet an accepted method for all situations and markets. In particular, quantifying and forecasting the risk for the MILA and ASEAN-5 stock markets is crucial for evaluating global market risk since the MILA is the biggest stock exchange in Latin America and the ASEAN region accounted for 11% of the total global foreign direct investment inflows in 2014. Furthermore, according to the Asian Development Bank, this region is projected to average 7% annual growth by 2025.