Suomen taloussuhdanteiden kansainvälinen yhteisvaihtelu

Taloussuhdanteiden yhteisvaihtelun tutkimus on eräs taloustieteiden vanhimmista tutkimusaloista. Finanssikriisi ja euroalueen kohtaamat talousvaikeudet ovat kuitenkin nostaneet aiheen jälleen hyvin ajankohtaiseksi. Kuluneiden kahdenkymmenen vuoden aikana tutkimusalueesta on muodostunut erittäin laaja lukuisine näkökulmineen ja debatteineen. Tutkielman aiheena on Suomen taloussuhdanteiden kansainvälinen yhteisvaihtelu valittujen vertailumaiden kanssa. Vertailumaat ovat Ruotsi, Norja, Tanska, Saksa, Ranska, Iso-Britannia ja Yhdysvallat. Tutkielmaan valitut taloussuhdannetta kuvaavat muuttujat ovat reaalinen bruttokansantuote, yksityinen kokonaiskulutus ja teollisuustuotantoindeksi. Aineisto on kerätty Lappeenrannan tiedekirjaston Nelli-portaalin OECD iLibrary-tietokannasta ja se kattaa aikajakson 1960 Q1- 2014 Q4. Maakohtainen taloussuhdanne operationalisoidaan laskemalla ensimmäinen logaritminen differenssi, joka edustaa perinteistä reaalisuhdanneteoreettisen koulukunnan näkemystä taloussuhdanteesta. Tutkielman näkökulmaksi valitaan yhden maan näkökulma, joka on hieman harvinaisempi näkökulma verrattuna laajempiin alueellisiin näkökulmiin. Tutkimusmenetelminä käytetään Pearsonin korrelaatiokerrointa, Engle-Granger- sekä Johansenin yhteisintegroituvuustestejä ja VAR-GARCH-BEKK –mallilla laskettua dynaamista korrelaatiota, jotka lasketaan Suomen ja vertailumaiden välille maapareittain. Tuloksia tulkitaan suomalaisen vientiä vertailumaihin suunnittelevan yrityksen näkökulmasta. Tutkielman tulosten perusteella Engle-Grangerin menetelmällä laskettu samanaikainen yhteisintegroituvuus Suomen ja vertailumaiden välillä on epätodennäköistä. Kun yhteisintegroituvuuden annetaan riippua myös viiveistä, saadaan Johansenin menetelmällä yhteisintegroituvuus Suomen ja Yhdysvaltojen välille reaalisessa bruttokansantuotteessa, Suomen ja Saksan, Suomen ja Ranskan sekä Suomen ja Yhdysvaltojen välille yksityisessä kokonaiskulutuksessa sekä Suomen ja Norjan välille teollisuustuotantoindeksissä. Tulosten tulkintaa vaikeuttavat niiden malliriippuvuus ja informaatiokriteerien toisistaan poikkeavat mallisuositukset, joten yhteisintegroituvuus on mahdollinen myös muiden maaparien kohdalla. Dynaamisten korrelaatiokuvaajien perusteella maaparien välisen yhteisvaihtelun voimakkuus muuttuu ajan mukana. Finanssikriisin aikana kokonaistuotannossa on havaittavissa korkeampi korrelaatio, mutta korrelaatio palaa sen jälkeen perustasolleen. Kokonaiskulutuksen korrelaatio on kokonaistuotantoa alhaisempi ja pitemmissä aikajaksoissa vaihtelevaa.

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.

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.

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.

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).

Dynamic correlations between REIT sub-sectors and the implications for diversification

The issue of whether Real Estate Investment Trusts (REITs) should pursue a focused or diversified investment strategy remains an ongoing debate within both the academic and industry communities. This article considers the relationship between REITs focused on different property sectors in a Generalized Autoregressive Conditional Heteroscedasticity-Dynamic Control Correlation (GARCH-DCC) framework. The daily conditional correlations reveal that since 1990 there has been a marked upward trend in the coefficients between US REIT sub-sectors. The findings imply that REITs are behaving in a far more homogeneous manner than in the past. Furthermore, the argument that REITs should be focused in order that investors can make the diversification decision is reduced.

Co-movements between US and UK stock prices: the roles of macroeconomic information and time-series varying conditional correlations

This paper provides evidence on the sources of co-movement in monthly US and UK stock price movements by investigating the role of macroeconomic and financial variables in a bivariate system with time-varying conditional correlations. Crosscountry communality in response is uncovered, with changes in the US Federal Funds rate, UK bond yields and oil prices having similar negative effects in both markets. Other variables also play a role, especially for the UK market. These effects do not, however, explain the marked increase in cross-market correlations observed from around 2000, which we attribute to time variation in the correlations of shocks to these markets. A regime-switching smooth transition model captures this time variation well and shows the correlations increase dramatically around 1999-2000. JEL classifications: C32, C51, G15 Keywords: international stock returns, DCC-GARCH model, smooth transition conditional correlation GARCH model, model evaluation.

Análise de contágio a partir do modelo de correlação condicional constante com mudança de regime Markoviana

Nas últimas décadas, a análise dos padrões de propagação internacional de eventos financeiros se tornou o tema de grande parte dos estudos acadêmicos focados em modelos de volatilidade multivariados. Diante deste contexto, objetivo central do presente estudo é avaliar o fenômeno de contágio financeiro entre retornos de índices de Bolsas de Valores de diferentes países a partir de uma abordagem econométrica, apresentada originalmente em Pelletier (2006), sobre a denominação de Regime Switching Dynamic Correlation (RSDC). Tal metodologia envolve a combinação do Modelo de Correlação Condicional Constante (CCC) proposto por Bollerslev (1990) com o Modelo de Mudança de Regime de Markov sugerido por Hamilton e Susmel (1994). Foi feita uma modificação no modelo original RSDC, a introdução do modelo GJR-GARCH formulado em Glosten, Jagannathan e Runkle (1993), na equação das variâncias condicionais individuais das séries para permitir capturar os efeitos assimétricos na volatilidade. A base de dados foi construída com as séries diárias de fechamento dos índices das Bolsas de Valores dos Estados Unidos (SP500), Reino Unido (FTSE100), Brasil (IBOVESPA) e Coréia do Sul (KOSPI) para o período de 02/01/2003 até 20/09/2012. Ao longo do trabalho a metodologia utilizada foi confrontada com outras mais difundidos na literatura, e o modelo RSDC com dois regimes foi definido como o mais apropriado para a amostra selecionada. O conjunto de resultados encontrados fornecem evidências a favor da existência de contágio financeiro entre os mercados dos quatro países considerando a definição de contágio financeiro do Banco Mundial denominada de “muito restritiva”. Tal conclusão deve ser avaliada com cautela considerando a extensa diversidade de definições de contágio existentes na literatura.

Sequential updating via dynamic hierarchical models: A Bayesian approach to longitudinal data analysis

Most statistical analysis, theory and practice, is concerned with static models; models with a proposed set of parameters whose values are fixed across observational units. Static models implicitly assume that the quantified relationships remain the same across the design space of the data. While this is reasonable under many circumstances this can be a dangerous assumption when dealing with sequentially ordered data. The mere passage of time always brings fresh considerations and the interrelationships among parameters, or subsets of parameters, may need to be continually revised. ^ When data are gathered sequentially dynamic interim monitoring may be useful as new subject-specific parameters are introduced with each new observational unit. Sequential imputation via dynamic hierarchical models is an efficient strategy for handling missing data and analyzing longitudinal studies. Dynamic conditional independence models offers a flexible framework that exploits the Bayesian updating scheme for capturing the evolution of both the population and individual effects over time. While static models often describe aggregate information well they often do not reflect conflicts in the information at the individual level. Dynamic models prove advantageous over static models in capturing both individual and aggregate trends. Computations for such models can be carried out via the Gibbs sampler. An application using a small sample repeated measures normally distributed growth curve data is presented. ^

Stock market integration between new EU member states and the Euro-zone

This paper measures the degree in stock market integration between five Eastern European countries and the Euro-zone. A potentially gradual transition in correlations is accommodated by smooth transition conditional correlation models. We find that the correlation between stock markets has increased from 2001 to 2007. In particular, the Czech and Polish markets show a higher correlation to the Euro-zone. However, this is not a broad-based phenomenon across Eastern Europe. We also find that the increase in correlations is not a reflection of a world-wide phenomenon of financial integration but appears to be specific to the European market. JEL classifications: C32; C51; F36; G15 Keywords: Multivariate GARCH; Smooth Transition Conditional Correlation; Stock Return Comovement; New EU Members.