A Portfolio Approach to Estimating the Average Correlation Coefficient for the Constant Correlation Model

This paper presents a portfolio approach to estimating the average correlation coefficient of a group of stocks which are considered for portfolio analysis. The average correlation coefficient has been shown to produce a better estimate of the future correlation matrix than individual pairwise correlations. The advantage of the approach described here is that it does not require the estimation of pairwise correlations for estimating their average.     

Characteristic-based mean-variance portfolio choice

We study empirical mean-variance optimization when the portfolio weights are restricted to be direct functions of underlying stock characteristics such as value and momentum. The closed-form solution to the portfolio weights estimator shows that the portfolio problem in this case reduces to a mean-variance analysis of assets with returns given by single-characteristic strategies (e.g., momentum or value). In an empirical application to international stock return indexes, we show that the direct approach to estimating portfolio weights clearly beats a naive regression-based approach that models the conditional mean. However, a portfolio based on equal weights of the single-characteristic strategies performs about as well, and sometimes better, than the direct estimation approach, highlighting again the difficulties in beating the equal-weighted case in mean-variance analysis. The empirical results also highlight the potential for ‘stock-picking’ in international indexes using characteristics such as value and momentum with the characteristic-based portfolios obtaining Sharpe ratios approximately three times larger than the world market.     

A multi-factor model for the risk management of portfolios

We propose a methodology for modelling the value at risk of a complex portfolio, based on an extension of the Ho, Stapleton and Subrahmanyam technique. We model the variance-covariance structure of up to seven variables. These could represent four country indices and three exchange rates, for example. In addition, the effect of an arbitrary number of orthogonal factors can be analysed. The system is illustrated by estimating the value at risk for a portfolio of international stocks where the factors are stock market indices and exchange rates, a portfolio of international bonds where the factors are interest rates as well as exchange rates, and a portfolio of interest rate derivatives in different currencies. In this last case, we model a two-factor term structure of interest rates in each of the currencies, valuing the derivatives at a future date using these term structures and the Black model. The model is applied for different fineness of the binomial density and computational accuracy and efficiency are estimated.
G13, G15, G21     

The value of asset allocation advice: Evidence from The Economist's quarterly portfolio poll

This study analyzes the economic importance of portfolio advice for an investor with an international and multiple-asset investment strategy. We construct portfolios based upon the asset allocation and security market advice of major international investment bankers and analyze the performance using weight-based techniques. Our results indicate that portfolio advisers are not able to outperform passive benchmarks. They do not realize superior performance either through appropriate timing or selection skills. Apparent market timing skills as measured by the Portfolio Change Measure are to a large extent an artifact caused by serial correlation in the return indices used. Likewise, the apparent short-run performance persistence is more due to the serial correlation in returns than to active portfolio selection strategies.     

Mean-variance optimization using forward-looking return estimates

Despite its theoretical appeal, Markowitz mean-variance portfolio optimization is plagued by practical issues. It is especially difficult to obtain reliable estimates of a stock’s expected return. Recent research has therefore focused on minimum volatility portfolio optimization, which implicitly assumes that expected returns for all assets are equal. We argue that investors are better off using the implied cost of capital based on analysts’ earnings forecasts as a forward-looking return estimate. Correcting for predictable analyst forecast errors, we demonstrate that mean-variance optimized portfolios based on these estimates outperform on both an absolute and a risk-adjusted basis the minimum volatility portfolio as well as naive benchmarks, such as the value-weighted and equally-weighted market portfolio. The results continue to hold when extending the sample to international markets, using different methods for estimating the forward-looking return, including transaction costs, and using different optimization constraints.

     

Covariance complexity and rates of return on assets

This paper considers the estimation of the expected rate of return on a set of risky assets. The approach to estimation focuses on the covariance matrix for the returns. The structure in the covariance matrix determines shared information which is useful in estimating the mean return for each asset. An empirical Bayes estimator is developed using the covariance structure of the returns distribution. The estimator is an improvement on the maximum likelihood and Bayes–Stein estimators in terms of mean squared error. The effect of reduced estimation error on accumulated wealth is analyzed for the portfolio choice model with constant relative risk aversion utility.     

Portfolio selection and skewness: Evidence from international stock markets

This paper finds that the returns of the world's 14 major stock markets are not normally distributed, and that the correlation matrix of these stock markets was stable during the January 1988–December 1993 time period. Polynomial goal programming, in which investor preferences for skewness can be incorporated, is utilized to determine the optimal portfolio consisting of the choices of 14 international stock indexes. The empirical findings suggest that the incorporation of skewness into an investor's portfolio decision causes a major change in the construction of the optimal portfolio. The evidence also indicate that investors trade expected return of the portfolio for skewness.     

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.     

Possibility versus feasibility: International portfolio diversification under financial liberalization

Financial liberalization may have double-edged impacts on international portfolio diversification since it increases financial market integration and market correlation simultaneously. Financial market integration enhances the possibility of diversifying portfolios internationally, while financial market correlation reduces the feasibility of such a diversification benefit. Using a dataset of stock market across 35 countries over the period 2001–2021, this paper examines the “possibility versus feasibility” puzzle arising from international portfolio diversification under financial liberalization. The empirical results show that financial liberalization has a positive (negative or no) impact on diversification benefits in its early (medium or developed) stage respectively due to its dual effects. Moreover, market integration positively affects diversification benefits only in the early stage of financial liberalization, while market correlation consistently has a negative impact on diversification benefits. Furthermore, this paper proposes an integration-correlation-oriented (ICO) diversification strategy to address the “possibility versus feasibility” puzzle, enabling international investors to make appropriate decisions on international portfolio diversification under financial liberalization.     

International portfolio diversification: a synthesis and an update

This paper provides a synthesis of the existing literature on international portfolio diversification and presents some new results on the subject. We address the question of whether international portfolio diversification is always a reasonable method of reducing the risk of an investment portfolio without negatively affecting its return expectations. Unfortunately, there is still not a simple answer to this question. When ex-post data is examined, potential benefits of international diversification can certainly be detected. However, we also argue that it might be difficult for investors to select an optimal investment strategy ex-ante, when the correlation structure among the international equity is unstable over time. While such findings do not completely rule out the potential benefits of international diversification, they certainly make them more difficult to realize in practice.     

International Diversification Strategies for Direct Real Estate

This paper will disentangle the performance of international real estate into property type performance and region selection. This helps to create an international diversification strategy for direct real estate. We use constrained cross-section regression with dummy variables for regions and property types to measure the best risk reducer. We analyze the impact of currency changes on total returns by looking at a hedged and un-hedged portfolio, both stock and equally weighted. The findings show that geographic factors have the largest influence on the volatility of international real estate returns. The average variance of the regional effects is higher than the property type effects and therefore the regional effects have a higher influence on the variation of the total portfolio. However, the regional effects are less stable through time, compared with the variance and correlation of the property type effects. Also the property type effect seems to become a more important factor for the return over time, especially when the return is expressed in local currency.     

International equity portfolio allocations and transaction costs

In spite of the critical role of transaction cost, there are not many papers that explicitly examine its influence on international equity portfolio allocation decisions. Using bilateral cross-country equity portfolio investment data and three direct measures of transaction costs for 36 countries, we provide evidence that markets where transaction costs are lower attract greater equity portfolio investments. The results imply that future research on international equity portfolio diversification cannot afford to ignore the role of transaction costs, and policy makers, especially in emerging markets, will have to reduce transaction costs to attract higher levels of foreign equity portfolio investments.     

Do return prediction models add economic value?

We compare statistical and economic measures of forecasting performance across a large set of stock return prediction models with time-varying mean and volatility. We find that it is very common for models to produce higher out-of-sample mean squared forecast errors than a model assuming a constant equity premium, yet simultaneously add economic value when their forecasts are used to guide portfolio decisions. While there is generally a positive correlation between a return prediction model’s out-of-sample statistical performance and its ability to add economic value, the relation tends to be weak and only explains a small part of the cross-sectional variation in different models’ economic value.     

MEASURING THE COST OF CAPITAL IN AN INTERNATIONAL CAPM FRAMEWORK

This paper can be viewed as extending the traditional CAPM framework in two important ways. The first expands the concept of the market portfolio to include international securities. The second extends the definition of systematic risk to include currency risk.
What becomes clear in estimating the cost of capital for an international asset is that both extensions have become necessary if the traditional CAPM is to remain relevant. International markets have become increasingly integrated over the past two decades and so all assets might now be considered "international" and priced accordingly. The inclusion of the currency risk factor is not an ad hoc addition to the CAPM but rather results quite naturally from the fact that foreign returns need to be converted into a domestic currency.
Based on an examination of 18 companies, the article shows that the use of a broader market portfolio will tend to lower the estimated cost of capital for most firms, but in some cases could actually raise it. (In the case of Singapore Airlines, for example, the currency risk factor adds substantially to the cost of capital, while materially reducing it in the case of Nestlé.) Using a simple regression, the authors also attempt to show how the specifics of a particular company—for example, the currencies that are part of their cost/ revenue structure—determine the impact of currency risk on the cost of capital.     

Which market integration measure?

This paper compares the dynamics of the financial integration process as described by different empirical approaches. To this end, a wide range of measures accounting for several dimensions of integration is employed. In addition, we evaluate the performance of each measure by relying on an established international finance result, i.e., increasing financial integration leads to declining international portfolio diversification benefits. Using monthly equity market data for three different country groups (i.e., developed markets, emerging markets, developed plus emerging markets) and a dynamic indicator of international portfolio diversification benefits, we find that (i) all measures give rise to a very similar long-run integration pattern; (ii) the standard correlation explains variations in diversification benefits as well or better than more sophisticated measures. These findings are robust to a battery of robustness checks.     

Realistic Portfolio Allocation Decision-Making For The Small U.S. Retail Investor

This study introduces new domestic mixed-asset and international equity securities that allow for exact portfolio replication even by small U.S. retail investors. Using these new series, various return characteristics are examined. Finally, three sets of mean-variance analyses are conducted: a domestic equity sector-only portfolio, a domestic mixed-asset portfolio, and an international mixed-asset portfolio. Real estate warrants inclusion to varying degrees in all three portfolios. International equity inclusion was also demonstrated.     

Strategic International Diversification and Monthly Seasonality

To the author's knowledge no other studies have dealt with the effect of international diversification on stock market monthly seasonality. The aim of this study is to investigate this effect in various ways: stock market monthly seasonality is analyzed by incorporating exchange rates and trading costs in international portfolio returns. The variance of the world portfolio is decomposed into six components. Stochastic dominance approach is used to show the robustness of the results. Five trading strategies are compared to help international investors be more informed. All the results show that monthly seasonality is clearly present in an economic sense and robust. Particularly, when exchange rates are incorporated into portfolio returns. January has the highest return and the lowest risk in the world portfolio.     

Are the gains from international portfolio diversification exaggerated? The influence of downside risk in bear markets

The fundamental rationale for international portfolio diversification is that it expands the opportunities for gains from portfolio diversification beyond those that are available through domestic securities. However, if international stock market correlations are higher than normal in bear markets, then international diversification will fail to yield the promised gains just when they are needed most. We evaluate the extent to which observed correlations to monthly returns in bear, calm and bull markets are captured by three popular bivariate distributions: (1) the normal, (2) the restricted GARCH(1,1) of J. P. Morgan’s RiskMetrics, and (3) the Student-t with four degrees of freedom. Observed correlations during calm and bull markets are unexceptional compared to these models. In contrast, observed correlations during bear markets are significantly higher than predicted. Higher-than-normal correlations during extreme market downturns result in monthly returns to equal-weighted portfolios of domestic and international stocks that are, on average, more than two percent lower than those predicted by the normal distribution. If the extent of non-normality during bear markets persists over time, then a US investor allocating assets into foreign markets might want to allocate more assets into foreign markets with near-normal correlation profiles and avoid markets with higher-than-normal bear market co-movements.     

Market proxies and the conditional prediction of returns

Ex post efficient proxies for the market portfolio are tested against the equal weight proxy. The equal weight proxy outperforms the others when the criterion is squared error of conditional prediction of returns. The ex post efficient proxies use maximum likelihood estimates of return. Stein estimates of return will generally be different from the maximum likelihood estimates and they necessarily correspond to market proxies which are not efficient ex post. In other words, there generally exists a better, inefficient, proxy than an ex post efficient proxy when the criterion is squared error of conditional prediction of return.