Benefits of diversifying investments into emerging markets with time-varying correlations: An Australian perspective

Australian investors can reduce their overall portfolio risk by diversifying into equities from other markets. Emerging markets have attracted significant interest because of their low correlations with Australian equity market returns; however, a number of studies have indicated that correlations between equity returns are increasing over time, so using unconditional estimates of correlations in a portfolio optimization model can result in the selection of a portfolio that may not be optimal.We use an Asymmetric Dynamic Conditional Correlation GARCH model to estimate time-varying correlations and include these correlation estimates in the portfolio optimization model. The assets used for portfolio construction comprise seven emerging market indices that are available to foreign investors. This study finds that, despite increasing correlations, there are still potential benefits for Australian investors who diversify into international emerging markets.     

International Asset Allocation With Regime Shifts

Correlations between international equity market returns tendto increase in highly volatile bear markets, which has led someto doubt the benefits of international diversification. Thisarticle solves the dynamic portfolio choice problem of a U.S.investor faced with a time-varying investment opportunity setmodeled using a regime-switching process which may be characterizedby correlations and volatilities that increase in bad times.International diversification is still valuable with regimechanges and currency hedging imparts further benefit. The costsof ignoring the regimes are small for all-equity portfoliosbut increase when a conditionally risk-free asset can be held.     

Dynamic Correlations Among Asset Classes: REIT and Stock Returns

We use the Dynamic Conditional Correlation model with Generalized Autoregressive Conditional Heteroskedasticity (DCC-GARCH) developed by Engle (Journal of Business & Economic Statistics 20(3):339–350, 2002) to examine dynamics in the correlation of returns between publicly traded REITs and non-REIT stocks. The results suggest that REIT-stock correlations form three distinct periods. During the first period, ending in August 1991 with the start of the modern REIT era, correlations were high and without trend, never dipping below 59%. During the second period, ending in September 2001 with the inclusion of REITs in broad stock market indexes, correlations declined precipitously to 30%, enabling substantially higher portfolio allocations to both high-return asset classes and therefore higher portfolio returns without increasing portfolio volatility. During the third period, since September 2001, correlations increased steadily but only reached 59% in late 2008. A simple portfolio optimization suggests that asset managers would be willing to pay 20 basis points per year, plus the difference in transaction costs, for the ability to use DCC-GARCH modeling of dynamic correlations in place of rolling 24-month asset correlations.     

Evaluating the impact of market reforms on Value-at-Risk forecasts of Chinese A and B shares

This paper analyses the time-varying conditional correlations between Chinese A and B share returns using the Dynamic Conditional Correlation (DCC) model of Engle [Engle, R.F. (2002), “Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models”, Journal of Business and Economic Statistics, 20, 339–350.]. The results show that the conditional correlations increased substantially following the B share market reform, whereby Chinese investors were permitted to purchase B shares. However, this increase in correlations was found to have begun well before the B share market reform. This result has significant implication relating to the structure of the information flow between the markets for the two classes of shares. Value-at-Risk (VaR) threshold forecasts are used to analyse the importance of accommodating dynamic conditional correlations between Chinese A and B shares, and thus reflects the impact of the changes in information flow on the risk evaluation of a diversified portfolio. The competing VaR forecasts are analysed using the Unconditional Coverage, Serial Independence and Conditional Coverage tests of Christoffersen [Christoffersen (1998), “Evaluating Interval Forecasts”, International Economic Review, 39, 841–862], and the Time Until First Failure Test of Kupiec [Kupiec, P.H., (1995), “Techniques for Verifying the Accuracy of Risk Measurements Models”, Journal of Derivatives, 73–84]. The results offer mild support for the DCC model over its constant conditional correlation counterpart.     

Time Variation in Diversification Benefits of Commodity, REITs, and TIPS

Diversification benefits of three “hot” asset classes—Commodity, Real Estate Investment Trusts (REITs), and Treasury Inflation-Protected Securities (TIPS)—are well-studied on an individual basis and in a static setting. Using data from 1970 to 2010, this paper documents both that the three asset classes are in general not substitutes for each other, and that diversification benefits of each asset class change substantially over time. Therefore, all three asset classes ought to be included in investors’ portfolios. Furthermore, we show that the observed time variation in diversification benefits can be explained by time-varying return correlations. To see the implications of these findings for asset allocation in practice, we examine the out-of-sample performance of portfolio strategies, based on a variety of correlation structures. We find that the Dynamic Conditional Correlation (DCC) model (Engle, J Bus Econ Stat 20(3):339–350, 2002) outperforms other correlation structures, such as rolling-window, historical, and constant correlations. Our findings suggest that diversification benefits of the three asset classes should be examined in a dynamic setting, and that investors need to use appropriate correlation estimates to adjust for such time variation.     

Equity market integration in emerging Balkan markets

This paper examines long-run relationships among five Balkan emerging stock markets (Turkey, Romania, Bulgaria, Croatia, Serbia), the United States and three developed European markets (UK, Germany, Greece), during the period 2000-2009. Conventional, regime-switching cointegration tests and Monte Carlo simulation provide evidence in favour of a long-run cointegrating relationship between the Balkan emerging markets within the region and globally. Moreover, we apply the Asymmetric Generalized Dynamic Conditional Correlation (AG-DCC) multivariate GARCH model of Cappiello et al. (2006), in order to capture the impact of the 2007-2009 financial crisis on the time-varying correlation dynamics among the developed and the Balkan stock markets. Results show that stock market dependence is heightened, supporting the herding behaviour during the 2008 stock market crash period. Our findings have important implications for international portfolio diversification and the effectiveness of domestic policies, as these emerging markets are exposed to external shocks.     

Dynamic correlations and volatility linkages between stocks and sukuk: Evidence from international markets

An understanding of volatility and co-movements in financial markets is important for portfolio allocation and risk management practices. The current financial crisis caused a shrinkage in values of most assets, an increased volatility and a threat to the survival of several institutional investors. Managing risks and returns within the classic portfolio theory, when correlations across securities soar, is increasingly challenging. In this paper, we investigate the volatility behavior and the co-movements between sukuk and international stock indexes. Symmetric multivariate GARCH models with dynamic conditional correlations (DCC) were estimated under Student-t distribution. We provide evidence of high correlations between sukuk and US and EU stock markets, without finding the well-known flight to quality behavior affecting Islamic bonds. We also show that volatility linkages between sukuk and regional market indexes are higher during financial crisis. We argue that investors could obtain diversification benefits including sukuk in a well-diversified equity portfolio, given their lower volatility compared to equity. But higher volatility linkages and dynamic correlations during financial crises show that they are hybrid instruments between bonds and equity. Our findings are relevant for institutional investors and asset managers that include Islamic bonds in a diversified portfolio.     

Dynamic correlations and hedging effectiveness between gold and stock markets: Evidence for BRICS countries

This paper examines the dynamic relationships between gold and stock markets using data for the BRICS counties. For this purpose, we estimate the Asymmetric DCC model for weekly stock and gold data. Our main objective is to examine the time-varying correlations between the two assets and to check the effectiveness of gold as a hedge for equity markets. The empirical results reveal that the dynamic conditional correlations switch between positive and negative values over the period under study. These correlations are low to negative during the major financial crises suggesting that gold can act as a safe haven against extreme market movements. We also evaluate the implications for portfolio diversification and hedging effectiveness for the gold/stock pairs. Our findings suggest that adding gold to a stock portfolio enhances its risk-adjusted return.     

Stock market volatility spillovers and portfolio hedging: BRICS and the financial crisis

The paper investigates the dynamic risk–return properties of the BRICS (Brazil, Russia, India, China, South Africa) capital markets and models potential time-varying correlations and volatility spillover effects with the US stock market. A VAR(1)–GARCH(1,1) framework contributes useful insight into US–BRICS market interactions and expands on a thin past empirical literature. A disaggregated approach pays attention to critical US–BRICS business sectors, namely the industrial and financial sectors. Significant return and volatility transmission dynamics are identified between the US and BRICS stock markets and business sectors. This is a critical input that can affect efficient global portfolio diversification and risk management strategies. Based on this empirical evidence, the study proceeds to assess effective portfolio hedge ratios and to construct optimal portfolio weights for diversified asset allocation to US–BRICS markets and business sectors.     

Asset allocation using flexible dynamic correlation models with regime switching

The asset allocation decision is often considered as a trade-off between maximizing the expected return of a portfolio and minimizing the portfolio risk. The riskiness is evaluated in terms of variance of the portfolio return, so that it is fundamental to consider correctly the variance of its components and their correlations. The evidence for the heteroskedastic behaviour of the returns and the time-varying relationships among the portfolio components have recently shifted attention to the multivariate GARCH models with time varying correlation. In this work we insert a particular Markov Switching dynamics in some Dynamic Correlation models to consider the abrupt changes in correlations affecting the assets in different ways. This class of models is very general and provides several specifications, constraining some coefficients. The models are applied to solve a sectorial asset allocation problem and are compared with alternative models.     

Cross‐region and cross‐sector asset allocation with regimes

Cross‐region and cross‐sector asset allocation decisions are one of the most fundamental issues in international equity portfolio management. Equity returns exhibit higher volatilities and correlations, and lower expected returns, in bear markets compared to bull markets. However, static mean–variance analysis fails to capture this salient feature of equity returns. We accommodate the nonlinearity of returns using a regime switching model across both regions and sectors. The regime‐dependent asset allocation potentially adds value to the traditional static mean–variance allocation. In addition, optimal allocation across sectors provide greater benefits compared to international diversification, which is characterized by higher returns, lower risks, lower correlations with the world market and a higher Sharpe ratio.     

Predictable risk and returns in emerging markets

The emergence of new equity markets in Europe, Latin America,Asia, the Mideast and Africa provides a new menu of opportunitiesfor investors. These markets exhibit high expected returns aswell as high volatility. Importantly, the low correlations withdeveloped countries' equity markets significantly reduces theunconditional portfolio risk of a world investor. However, standardglobal asset pricing models, which assume complete integrationof capital markets, fail to explain the cross section of averagereturns in emerging countries. An analysis of the predictabilityof the returns reveals that emerging market returns are morelikely than developed countries to be influenced by local information.     

Explaining international stock correlations with CPI fluctuations and market volatility

This paper investigates the dynamic correlations among six international stock market indices and their relationship to inflation fluctuation and market volatility. The current research uses a newly developed time series model, the Double Smooth Transition Conditional Correlation with Conditional Auto Regressive Range (DSTCC-CARR) model. Findings reveal that international stock correlations are significantly time-varying and the evolution among them is related to cyclical fluctuations of inflation rates and stock volatility. The higher/lower correlations emerge between countries when both countries experience a contractionary/expansionary phase or higher/lower volatilities.     

Cross-asset relations,correlations and economic implications

This paper examines the interrelations and time-varying correlations for eight assets. One-year rolling correlations reveal that each of the 28 correlations exhibit both positive and negative values. Linear regressions reveal that given macroeconomic and financial variables contain predictive power for different asset return correlations. The term structure of interest rates and consumer sentiment feature as prominent predictor variables. Structural break tests and non-linear regressions indicate a cycling of correlations between high and low risk periods. In seeking to consider the economic content of the interrelations, we construct a safe and risky portfolio and show that the correlation between these portfolios can allow for improved market timing. Further, the safe and risky portfolio returns and correlation exhibit predictive power for macroeconomic conditions and may be used in a leading indicator role. The results presented here should be of interest to investors and policy-makers as well as academics wishing to examine the relations between both asset returns and financial and real markets.     

Portfolio selection with commodities under conditional copulas and skew preferences

This article investigates the portfolio selection problem of an investor with three-moment preferences taking positions in commodity futures. To model the asset returns, we propose a conditional asymmetric t copula with skewed and fat-tailed marginal distributions, such that we can capture the impact on optimal portfolios of time-varying moments, state-dependent correlations, and tail and asymmetric dependence. In the empirical application with oil, gold and equity data from 1990 to 2010, the conditional t copulas portfolios achieve better performance than those based on more conventional strategies. The specification of higher moments in the marginal distributions and the type of tail dependence in the copula has significant implications for the out-of-sample portfolio performance.     

Asset Trading Volume with Dynamically Complete Markets and Heterogeneous Agents

Trading volume of infinitely lived securities, such as equity, is generically zero in Lucas asset pricing models with heterogeneous agents. More generally, the end‐of‐period portfolio of all securities is constant over time and states in the generic economy. General equilibrium restrictions rule out trading of equity after an initial period. This result contrasts the prediction of portfolio allocation analyses that portfolio rebalancing motives produce nontrivial trade volume. Therefore, other causes of trade must be present in asset markets with large trading volume.     

Diversification evidence from international equity markets using extreme values and stochastic copulas

Tail dependence plays an important role in financial risk management and determination of whether two markets crash or boom together. However, the linear correlation is unable to capture the dependence structure among financial data. Moreover, given the reality of fat-tail or skewed distribution of financial data, normality assumption for risk measure may be misleading in portfolio development. This paper proposes the use of conditional extreme value theory and time-varying copula to capture the tail dependence between the Australian financial market and other selected international stock markets. Conditional extreme value theory enables the model adequacy and the tail behavior of individual financial variable, while the time-varying copula can fully disclose the changes of dependence structure over time. The combination of both proved to be useful in determining the tail dependence. The empirical results show an outperformance of the model in the analysis of tail dependence, which has an important implication in cross-market diversification and asset pricing allocation.     

Risk and return implications from investing in emerging European stock markets

The dynamic linkages and the effects of time-varying volatilities are investigated for major emerging Central European (CE) and developed stock markets. Risk and return implications for portfolio diversification to these markets are assessed, causal lead–lag relationships are identified and asymmetric volatility effects are evaluated. The presence of one cointegration vector indicates market comovements towards a stationary long-run equilibrium path. Central European markets tend to display stronger linkages with their mature counterparts rather than their neighbors. An asymmetric EGARCH model indicates varying but persistent volatility effects for the CE markets. International portfolio diversification can be less effective across cointegrated markets because risk cannot be reduced substantially and return can exhibit a volatile reaction to domestic and international shocks. The possibility of arbitrage short-run profits, however is not ruled out.     

On the characteristics of dynamic correlations between asset pairs

Recent research provides considerable evidence that correlations between assets change significantly over time and diversification benefits of correlations may vary substantially based on the time-varying measure of correlation used for different asset types. Our study evaluates and compares alternative time-series correlation modeling techniques according to both statistical and economic metrics, focusing specifically on individual asset pairs. We identify the moving correlation structure that best tracks the dynamic conditional correlation estimates using a large set of different financial time series encompassing 467 asset pairs in nine different asset classes. Results from our direct, statistical loss function based, and indirect, portfolio mean-variance based, forecast evaluations provide optimal window-length ranges for 36 asset-class pairs which should help in portfolio construction as well as risk management. Furthermore for robustness tests, we implement the model confidence set approach which, without a benchmark specification, produces a set of models constructed to contain the best models with a given level of confidence among competing forecast evaluations.     

Art as an investment: risk, return and portfolio diversification in major painting markets

The present paper examines risk, return and the prospects for portfolio diversification among major painting and financial markets over the period 1976–2001. The art markets examined are Contemporary Masters, French Impressionists, Modern European, 19th Century European, Old Masters, Surrealists, 20th Century English and Modern US paintings. The financial markets comprise US Treasury bills, corporate and government bonds and small and large company stocks. In common with the published literature in this area, the present study finds that the returns on paintings are much lower and the risks much higher than conventional investment markets. Moreover, while low correlations of returns suggest that opportunities for portfolio diversification in art works alone and in conjunction with equity markets exist, the construction of Markowitz mean‐variance efficient portfolios indicates that no diversification gains are provided by art in financial asset portfolios. However, diversification benefits in portfolios comprised solely of art works are possible, with Contemporary Masters, 19th Century European, Old Masters and 20th Century English paintings dominating the efficient frontier during the period in question.