Valor en riesgo del portafolio de TES de los bancos colombianos

En este trabajo se realiza la medición del riesgo de mercado para el portafolio de TES de un banco colombiano determinado, abordando el pronóstico de valor en riesgo (VaR) mediante diferentes modelos multivariados de volatilidad: EWMA, GARCH ortogonal, GARCH robusto, así como distintos modelos de VaR con distribución normal y distribución t-student, evaluando su eficiencia con las metodologías de backtesting propuestas por Candelon et al. (2011) con base en el método generalizado de momentos, junto con los test de independencia y de cobertura condicional planteados por Christoffersen y Pelletier (2004) y por Berkowitz, Christoffersen y Pelletier (2010). Los resultados obtenidos demuestran que la mejor especificación del VaR para la medición del riesgo de mercado del portafolio de TES de los bancos colombianos, es el construido a partir de volatilidades EWMA y basado en la distribución normal, ya que satisface las hipótesis de cobertura no condicional, independencia y cobertura condicional, al igual que los requerimientos estipulados en Basilea II y en la normativa vigente en Colombia.

Stock return comovements and integration within the Latin American integrated market

Financial integration has been pursued aggressively across the globe in the last fifty years; however, there is no conclusive evidence on the diversification gains (or losses) of such efforts. These gains (or losses) are related to the degree of comovements and synchronization among increasingly integrated global markets. We quantify the degree of comovements within the integrated Latin American market (MILA). We use dynamic correlation models to quantify comovements across securities as well as a direct integration measure. Our results show an increase in comovements when we look at the country indexes, however, the increase in the trend of correlation is previous to the institutional efforts to establish an integrated market in the region. On the other hand, when we look at sector indexes and an integration measure, we find a decreased in comovements among a representative sample of securities form the integrated market.

A likelihood ratio appropach to family-based association studies with covariates

We introduce a procedure for association based analysis of nuclear families that allows for dichotomous and more general measurements of phenotype and inclusion of covariate information. Standard generalized linear models are used to relate phenotype and its predictors. Our test procedure, based on the likelihood ratio, unifies the estimation of all parameters through the likelihood itself and yields maximum likelihood estimates of the genetic relative risk and interaction parameters. Our method has advantages in modelling the covariate and gene-covariate interaction terms over recently proposed conditional score tests that include covariate information via a two-stage modelling approach. We apply our method in a study of human systemic lupus erythematosus and the C-reactive protein that includes sex as a covariate.

International portfolio diversification: evidence from emerging markets

Taking into account previous research we could assume to be beneficial to diversify investments in emerging economies. We investigate in the paper International Portfolio Diversification: evidence from Emerging Markets if it still holds true, given the assumption of larger world markets integration. Our results suggest a wide spread positive time-varying correlations of emerging and developed markets. However, pair-wise cross-country correlations gave evidence that emerging markets have low integration with developed markets. Consequently, we evaluate out-of-sample performance of a portfolio with emerging equity countries, confirming the initial statement that it has a better a risk-adjusted performance over a purely developed markets portfolio.

Desempenho reprodutivo de novilhas Nelore pré-púberes expostas à progesterona

Pós-graduação em Zootecnia - FMVZ

Does Exchange Rate Risk Affect Exports Asymmetrically? Asian Evidence

The effects of exchange rate risk have interested researchers, since the collapse of fixed exchange rates. Little consensus exists, however, regarding its effect on exports. Previous studies implicitly assume symmetry. This paper tests the hypothesis of asymmetric effects of exchange rate risk with a dynamic conditional correlation bivariate GARCH(1,1)-M model. The asymmetry means that exchange rate risk (volatility) affects exports differently during appreciations and depreciations of the exchange rate. The data include bilateral exports from eight Asian countries to the US. The empirical results show that real exchange rate risk significantly affects exports for all countries, negative or positive, in periods of depreciation or appreciation. For five of the eight countries, the effects of exchange risk are asymmetric. Thus, policy makers can consider the stability of the exchange rate in addition to its depreciation as a method of stimulating export growth.

Export Promotion through Exchange Rate Policy: Exchange Rate Depreciation or Stabilization?

Exchange rate movements affect exports in two ways -- its depreciation and its variability (risk). A depreciation raises exports, but the associated exchange rate risk could offset that positive effect. The present paper investigates the net effect for eight Asian countries using a dynamic conditional correlation bivariate GARCH-M model that simultaneously estimates time varying correlation and exchange rate risk. Depreciation encourages exports, as expected, for most countries, but its contribution to export growth is weak. Exchange rate risk contributes to export growth in Malaysia and the Philippines, leading to positive net effects. Exchange rate risk generates a negative effect for six of the countries, resulting in a negative net effect in Indonesia, Japan, Singapore, Taiwan and a zero net effect in Korea and Thailand. Since the negative effect of exchange rate risk may offset, or even dominate, positive contributions from depreciation, policy makers need to reduce exchange rate fluctuation along with and possibly before efforts to depreciate the currency.

Inflation targeting in Korea, Indonesia, Thailand, and the Philippines : the impact on business cycle synchronization between each country and the world

This paper empirically analyzes whether and to what extent the adoption of inflation targeting (IT) in Korea, Indonesia, Thailand and the Philippines has affected their business cycle synchronization with the rest of the world. By employing the dynamic conditional correlation (DCC) model developed by Engle (2002), we find that IT in Asia has little effect on international business cycle synchronization and the effect is positive in some of the countries, if any. These findings basically seem to be consistent with the evidence from relevant literature.

Integração espacial e eficiência do hedge no mercado sul-americano de soja: comparações entre Brasil e Argentina

Este trabalho tem por objetivo analisar o potencial de desenvolvimento do contrato futuro de soja no Brasil, por meio da atração de hedgers brasileiros e argentinos. Para tanto, faz-se necessário conhecer os padrões das conexões dos preços entre as regiões analisadas. Nesse sentido, o Capítulo 2 investigou a integração espacial do mercado físico de soja no Brasil (região de Sorriso, no Mato Grosso) e na Argentina (região de Rosário, na província de Santa Fé) e comparou ao grau de integração com os Estados Unidos. Foram empregados modelos autorregressivos com threshold (TAR e M-TAR) e modelos vetoriais de correção de erros, lineares e com threshold (VECM e TVECM), visando captar os efeitos dos custos de transação sobre a integração espacial entre essas regiões. Os resultados apontaram que o mercado de soja brasileiro, argentino e norte-americano são integrados, mesmo considerando-se os efeitos dos custos de transação sobre as decisões de arbitragem espacial. Consequentemente, os preços da soja no mercado internacional tendem a refletir o comportamento dos principais países produtores. Apesar disso, o tempo de transmissão de choques de preços mostrou-se, em geral, menor entre Brasil e Argentina, refletindo a proximidade geográfica. Apontou-se também o comportamento assimétrico da transmissão desses choques, uma vez que choques positivos sobre a relação de longo prazo tendem a ser mais persistentes que os negativos. Se o contrato futuro reflete o comportamento de preços de um único mercado físico integrado, deve-se então esperar que o risco de base seja menor para este mercado e, portanto, que a eficiência do hedge seja maior. No Capítulo 3, o objetivo se constituiu em verificar se há maior eficiência no hedge realizado com os contratos com vencimento em março na CME em relação à BM&FBOVESPA, considerando-se as relações de longo prazo entre os preços à vista e futuros, bem como a dinâmica na estrutura de covariâncias condicionais, por meio de modelos de correção de erros (VECM) e modelos de heterocedasticidade condicional generalizados com correlação condicional dinâmica (DCC-GARCH). Os resultados mostraram que, em geral, a introdução da dinâmica nos segundos momentos das distribuições dos erros tende a aumentar a eficiência da estratégia de hedge. Além disso, foi observado que os produtores de Sorriso tendem a obter melhores condições de hedge na CME, embora haja redução da variância ao se operar na BM&FBOVESPA. Por outro lado, a eficiência do hedge para os produtores de Rosário foi significativamente maior na BM&FBOVESPA do que na CME, o que indica o mercado potencial de hedgers argentinos para negociar o contrato futuro de soja local no Brasil.

The Impact of the ECB’s Asset Purchase Programmes on Sovereign Bond Spreads in the Euro Area. Bruges European Economic Research Papers 35/2015

This paper estimates the immediate impact of the European Central Bank’s asset purchase programmes on sovereign bond spreads in the euro area between 2008 and 2015 using a country-by-country GARCH model. The baseline estimates are rigorously diagnosed for misspecification and subjected to a wide range of sensitivity tests. Among others, changes in the dependent variable, the independent variables and the number of (G)ARCH terms are tested. Moreover, the model is applied to subsamples and dynamic conditional correlations are analyzed to estimate the effects of the asset purchases on the contagion of spread movements. Generally, it is found that the asset purchase programmes triggered an reduction of sovereign bond spreads. More specifically, the Securities Markets Programme (SMP) had the most significant immediate effects on sovereign bond spreads across the euro area. The announcements related to the Outright Monetary Transactions (OMT) programme also yielded substantial spread compression in the periphery. In contrast to that, the most recent Public Sector Purchase Programme (PSPP) announced in January 2015 and implemented since March 2015 had no significant immediate effects on sovereign bond spreads, except for Irish spreads. Hence, immediate effects seem to be dependent upon the size of the programme, the extent to which it targets distressed sovereigns and the way in which it is communicated.

A comprehensive portfolio construction under stochastic environment

Prior research has established that idiosyncratic volatility of the securities prices exhibits a positive trend. This trend and other factors have made the merits of investment diversification and portfolio construction more compelling. ^ A new optimization technique, a greedy algorithm, is proposed to optimize the weights of assets in a portfolio. The main benefits of using this algorithm are to: (a) increase the efficiency of the portfolio optimization process, (b) implement large-scale optimizations, and (c) improve the resulting optimal weights. In addition, the technique utilizes a novel approach in the construction of a time-varying covariance matrix. This involves the application of a modified integrated dynamic conditional correlation GARCH (IDCC - GARCH) model to account for the dynamics of the conditional covariance matrices that are employed. ^ The stochastic aspects of the expected return of the securities are integrated into the technique through Monte Carlo simulations. Instead of representing the expected returns as deterministic values, they are assigned simulated values based on their historical measures. The time-series of the securities are fitted into a probability distribution that matches the time-series characteristics using the Anderson-Darling goodness-of-fit criterion. Simulated and actual data sets are used to further generalize the results. Employing the S&P500 securities as the base, 2000 simulated data sets are created using Monte Carlo simulation. In addition, the Russell 1000 securities are used to generate 50 sample data sets. ^ The results indicate an increase in risk-return performance. Choosing the Value-at-Risk (VaR) as the criterion and the Crystal Ball portfolio optimizer, a commercial product currently available on the market, as the comparison for benchmarking, the new greedy technique clearly outperforms others using a sample of the S&P500 and the Russell 1000 securities. The resulting improvements in performance are consistent among five securities selection methods (maximum, minimum, random, absolute minimum, and absolute maximum) and three covariance structures (unconditional, orthogonal GARCH, and integrated dynamic conditional GARCH). ^

A Comprehensive Portfolio Construction Under Stochastic Environment

Prior research has established that idiosyncratic volatility of the securities prices exhibits a positive trend. This trend and other factors have made the merits of investment diversification and portfolio construction more compelling. A new optimization technique, a greedy algorithm, is proposed to optimize the weights of assets in a portfolio. The main benefits of using this algorithm are to: a) increase the efficiency of the portfolio optimization process, b) implement large-scale optimizations, and c) improve the resulting optimal weights. In addition, the technique utilizes a novel approach in the construction of a time-varying covariance matrix. This involves the application of a modified integrated dynamic conditional correlation GARCH (IDCC - GARCH) model to account for the dynamics of the conditional covariance matrices that are employed. The stochastic aspects of the expected return of the securities are integrated into the technique through Monte Carlo simulations. Instead of representing the expected returns as deterministic values, they are assigned simulated values based on their historical measures. The time-series of the securities are fitted into a probability distribution that matches the time-series characteristics using the Anderson-Darling goodness-of-fit criterion. Simulated and actual data sets are used to further generalize the results. Employing the S&P500 securities as the base, 2000 simulated data sets are created using Monte Carlo simulation. In addition, the Russell 1000 securities are used to generate 50 sample data sets. The results indicate an increase in risk-return performance. Choosing the Value-at-Risk (VaR) as the criterion and the Crystal Ball portfolio optimizer, a commercial product currently available on the market, as the comparison for benchmarking, the new greedy technique clearly outperforms others using a sample of the S&P500 and the Russell 1000 securities. The resulting improvements in performance are consistent among five securities selection methods (maximum, minimum, random, absolute minimum, and absolute maximum) and three covariance structures (unconditional, orthogonal GARCH, and integrated dynamic conditional GARCH).

A Dynamic Model of Hand-and-Foot Syndrome in Patients Receiving Capecitabine

For the purpose of developing a longitudinal model to predict hand-and-foot syndrome (HFS) dynamics in patients receiving capecitabine, data from two large phase III studies were used. Of 595 patients in the capecitabine arms, 400 patients were randomly selected to build the model, and the other 195 were assigned for model validation. A score for risk of developing HFS was modeled using the proportional odds model, a sigmoidal maximum effect model driven by capecitabine accumulation as estimated through a kinetic-pharmacodynamic model and a Markov process. The lower the calculated creatinine clearance value at inclusion, the higher was the risk of HFS. Model validation was performed by visual and statistical predictive checks. The predictive dynamic model of HFS in patients receiving capecitabine allows the prediction of toxicity risk based on cumulative capecitabine dose and previous HFS grade. This dose-toxicity model will be useful in developing Bayesian individual treatment adaptations and may be of use in the clinic.