Asymmetries and heavy tails are well-known characteristics on compound daily returns stock market in dices. The THSV-SMN–Threshold Stochastic Volatility Modelwith Scale Mixture of Normal Distributions– model has become an important tool for analysis regarding forecasting asset returns and Value at Risk and Expected Shortfall portfolio estimations in order to assess marketrisk.Therefore, under a Bayesian approach,we develop an extensionon the model proposed by Abanto & Garrafa(2019).This extension allows for an endogenous threshold and will be studied under two theoretical frameworks: the use of order statistics and a random walk Metropolis–Hasting algorithm(RWMH). We test themodel extension upon stock market indices across the globe along four regions (NorthAmerica, LATAM,EuropeandAsia) withour proposed RWMH algorithm and compare the results with the original (fixedthreshold) model...

La presente investigación tiene como objetivo realizar un análisis sobre las posibles maneras de afrontar el problema de la baja cobertura del sistema de pensiones peruano. Para ello se realizará dos estimaciones que buscan encontrar los principales determinantes de la cobertura del sistema de pensiones. Utilizaremos la Encuesta Nacional de Hogares para el año 2018 y modelamos la probabilidad de participación en un programa de pensiones cuyas principales fuentes de alimentación son vectores de características individuales, de hogar y de empleo.

La presente investigación tiene como objetivo realizar un análisis sobre las posibles maneras de afrontar el problema de la baja cobertura del sistema de pensiones peruano. Para ello se realizará dos estimaciones que buscan encontrar los principales determinantes de la cobertura del sistema de pensiones. Utilizaremos la Encuesta Nacional de Hogares para el año 2018 y modelamos la probabilidad de participación en un programa de pensiones cuyas principales fuentes de alimentación son vectores de características individuales, de hogar y de empleo.

Asymmetries and heavy tails are well-known characteristics on compound daily returns stock market in dices. The THSV-SMN–Threshold Stochastic Volatility Modelwith Scale Mixture of Normal Distributions– model has become an important tool for analysis regarding forecasting asset returns and Value at Risk and Expected Shortfall portfolio estimations in order to assess marketrisk.Therefore, under a Bayesian approach,we develop an extensionon the model proposed by Abanto & Garrafa(2019).This extension allows for an endogenous threshold and will be studied under two theoretical frameworks: the use of order statistics and a random walk Metropolis–Hasting algorithm(RWMH). We test themodel extension upon stock market indices across the globe along four regions (NorthAmerica, LATAM,EuropeandAsia) withour proposed RWMH algorithm and compare the results with the original (fixedthreshold) model...