Optimization,cointegration and diversification gains from international portfolios: an out-of-sample analysis

This study investigates comparative performance of iShares and their underlying market indices in a portfolio context from the perspective of U.S. investors. Two aspects are important. First, portfolios based on standard optimization procedures and a portfolio based on cointegration procedures are created and out-of-sample performance is compared. The portfolio utilizing cointegration inputs shows superior out-of-sample performance. Second, portfolio performance measurement is extended to different holding periods. The findings do not differ.     

Portfolio selection, diversification and fund-of-funds: a note

The present paper examines the performance and diversification properties of active Australian equity fund‐of‐funds (FoF). Simulation analysis is employed to examine portfolio performance as a function of the number of funds in the portfolio. The present paper finds that as the number of funds in an FoF portfolio increases, performance improves in a mean–variance setting; however, measures of skewness and kurtosis behave less favourably given an investor's preferences for the higher moments of the return distribution. The majority of diversification benefits are realized when a portfolio of approximately 6 active equity funds are included in the FoF portfolio.     

Do ADRs enhance portfolio performance for a domestic portfolio? Evidence from the 1990s

American depository receipts (ADRs) represent an increasingly popular and convenient mechanism for international investing. We analyze ADRs traded throughout the 1990s and find that these securities offer a diversification and portfolio performance benefit when combined with a domestic portfolio (proxied by the S&P 500). While we find that emerging market ADRs are effective instruments for reducing portfolio risk, they do not improve portfolio performance as measured by the Sharpe ratio. Developed market ADRs do improve portfolio performance as measured by the Sharpe ratio. The asset allocation which maximizes the Sharpe ratio is 84 percent domestic stocks, 16 percent developed ADRs, and 0 percent emerging ADRs. Further, due to problems in defining an appropriate market index for ADRs, the Sharpe ratio is viewed to be the preferred performance measure. Other measures such as Jensen’s alpha and the Treynor measure are susceptible to being “gamed” to distort portfolio performance.     

Maximizing an equity portfolio excess growth rate: a new form of smart beta strategy?

It has been claimed that, for dynamic investment strategies, the simple act of rebalancing a portfolio can be a source of additional performance, sometimes referred to as the volatility pumping effect or the diversification bonus because volatility and diversification turn out to be key drivers of the portfolio performance. Stochastic portfolio theory suggests that the portfolio excess growth rate, defined as the difference between the portfolio expected growth rate and the weighted-average expected growth rate of the assets in the portfolio, is an important component of this additional performance (see Fernholz [Stochastic Portfolio Theory, 2002 (Springer)]). In this context, one might wonder whether maximizing a portfolio excess growth rate would lead to an improvement in the portfolio performance or risk-adjusted performance. This paper provides a thorough empirical analysis of the maximization of an equity portfolio excess growth rate in a portfolio construction context for individual stocks. In out-of-sample empirical tests conducted on individual stocks from 4 different regions (US, UK, Eurozone and Japan), we find that portfolios that maximize the excess growth rate are characterized by a strong negative exposure to the low volatility factor and a higher than 1 exposure to the market factor, implying that such portfolios are attractive alternatives to competing smart portfolios in markets where the low volatility anomaly does not hold (e.g. in the UK, or in rising interest rate scenarios) or in bull market environments.     

Potential performance and tests of portfolio efficiency

The potential performance of an asset set may be obtained by choosing the portfolio proportions to maximize the Sharpe (1966) performance measure. If a portfolio has a Sharpe measure equivalent to the potential performance of the underlying set of assets, then it is efficient. Multivariate statistical procedures for comparing potential performance and testing portfolio efficiency are developed and then evaluated using simulations. Two likelihood ratio statistics are then used to compare stock and bond indices against sets of 20 and 40 portfolios. The procedures are also compared to the Gibbons (1982) methodology for testing financial models.     

A conditional asset-pricing model with the optimal orthogonal portfolio

This paper employs a conditional asset-pricing model based on the optimal orthogonal portfolio approach to construct a factor portfolio that embodies all the latent factors important for pricing a given set of test assets. The advantage of this portfolio to the anomaly related mimicking portfolios is its ability to separate out the components of average return that are not related to the return covariation. The performance of this portfolio is evaluated against several conventional factors, using both cross-sectional and time-series regression approaches, as well as the Hansen and Jagannathan (1997) distance measure. Its strong out-of-sample results indicate that our suggested methodology may have important applications in risk management, portfolio selection and performance evaluation.     

Using industry momentum to improve portfolio performance

Minimum-variance portfolios, which ignore the mean and focus on the (co)variances of asset returns, outperform mean–variance approaches in out-of-sample tests. Despite these promising results, minimum-variance policies fail to deliver a superior performance compared with the simple 1/N rule. In this paper, we propose a parametric portfolio policy that uses industry return momentum to improve portfolio performance. Our portfolio policies outperform a broad selection of established portfolio strategies in terms of Sharpe ratio and certainty equivalent returns. The proposed policies are particularly suitable for investors because portfolio turnover is only moderately increased compared to standard minimum-variance portfolios.     

Portfolio Optimization under Solvency Constraints: A Dynamical Approach

We develop portfolio optimization problems for a nonlife insurance company seeking to find the minimum capital required that simultaneously satisfies solvency and portfolio performance constraints. Motivated by standard insurance regulations, we consider solvency capital requirements based on three criteria: ruin probability, conditional Value-at-Risk, and expected policyholder deficit ratio. We propose a novel semiparametric formulation for each problem and explore the advantages of implementing this methodology over other potential approaches. When liabilities follow a Lognormal distribution, we provide sufficient conditions for convexity for each problem. Using different expected return on capital target levels, we construct efficient frontiers when portfolio assets are modeled with a special class of multivariate GARCH models. We find that the correlation between asset returns plays an important role in the behavior of the optimal capital required and the portfolio structure. The stability and out-of-sample performance of our optimal solutions are empirically tested with respect to both the solvency requirement and portfolio performance, through a double rolling window estimation exercise.     

How much should portfolios shrink?

This paper develops a portfolio model that penalizes the deviation from a reference portfolio. The proposed model renders a robust portfolio that performs superior under parameter uncertainty. Penalizing the deviation also improves the performance of existing shrinkage portfolio models that are suboptimal due to model parameter uncertainty. The equal-weight portfolio turns out to be a better reference portfolio than the currently holding portfolio even in the presence of transaction costs. A data-driven method for determining the degree of penalization is offered. Comprehensive simulation and empirical studies suggest that the proposed model significantly outperforms various existing models.     

A comparison of static and dynamic portfolio policies

Garleanu and Pedersen (2013) show that the optimal static portfolio policy in light of quadratic transaction costs is a weighted average of the existing portfolio and the target portfolio. In this paper, we demonstrate the importance of the robust target portfolio in the static portfolio policy that considers quadratic transaction costs. By using both empirical and simulated data, we find no evidence that the optimal dynamic portfolio policy proposed by Garleanu and Pedersen (2013) is superior to the static portfolio policy that trades towards the robust target portfolio. The robust target portfolio is achieved by either introducing time-varying covariances or restricting portfolio weights. Furthermore, the static portfolio with time-varying covariances and the short sale-constrained static portfolio are both very efficient in reducing portfolio turnover. The good performance of the static portfolio policy is robust to parameter uncertainty and trading parameters.     

Optimizing international portfolios with options and forwards

We develop a stochastic programming model to address in a unified manner a number of interrelated decisions in international portfolio management: optimal portfolio diversification and mitigation of market and currency risks. The goal is to control the portfolio’s total risk exposure and attain an effective balance between risk and expected return. By incorporating options and forward contracts in the portfolio optimization model we are able to numerically assess the performance of alternative tactics for mitigating exposure to the primary risks. We find that control of market risk with options has more significant impact on portfolio performance than currency hedging. We demonstrate through extensive empirical tests that incremental benefits, in terms of reducing risk and generating profits, are gained when both the market and currency risks are jointly controlled through appropriate means.     

Benchmark Invariancy,Seasonality and APM-Free Portfolio Performance Measures

The Jobson-Korkie (1981) Z score and the positive period weighting (PPW) score of Grinblatt and Titman (1989) are applied to various benchmarks of market and mimicking portfolios to study the benchmark invariancy problem. Significantly different portfolio performance inferences are found for a sample of 146 equity mutual funds depending on the mean-variance efficiency of the portfolio benchmarks (mimicking portfolios versus market indices). Portfolio performance inferences are affected significantly by the number of factors, nonsynchronous trading adjustment, and the sizes of the firms used for factor extraction. The returns of the portfolio benchmarks exhibit significant monthly seasonalities, which, in turn, significantly influence mutual fund performance inferences.     

THE PERFORMANCE MEASUREMENT AND EVALUATION OF A CORPORATE RETIREMENT PLAN: A CASE STUDY

This paper is based on an actual study of a pooled profit-sharing plan sponsored by a Fortune 50 company from September 1978 to June 1983. The purpose of performance measurement is to identify skill at portfolio management and provide evidence indicating whether performance coincides with the investment skills claimed by the portfolio manager. The approach here is to apply the security market line analysis suggested by Fama. Characteristic lines were determined for the plan portfolio allowing the calculation for alpha, the Jensen differential performance index, beta, and R². Tests are made to determine if the investment manager was able to achieve superior performance by shifting portfolio market sensitivity in anticipation of major market moves (market-timing effect) and/or selecting undervalued securities (security-selection effect).     

A Value-At-Risk Calculation of Required Reserves for Credit Risk in Corporate Lending Portfolios

This paper demonstrates that the building blocks of the insurance process, under similar assumptions, produce identical results to the option-pricing approach in the case of pricing individual loans. We examine the performance of a collective of such building blocks, using portfolio historical performance to endogenously parameterize the default cost function unique to a particular portfolio. Having estimated the appropriate default cost function, we can then specify the reserve requirement for a bank operating such a portfolio. In this respect, the additivity of the Poisson parameter is a powerful feature, allowing one to decompose portfolio performance over time and homogeneous portfolio subsections. Portfolios with greater and lesser risk and profitability respectively are hypothesized, and a capital adequacy framework which equates risk across such portfolios is examined. Finally, we simulate the operation of the proposed capital adequacy model. Observed insolvencies are fewer than those observable under present regulation, and specific problems may be identified earlier than at present.     

Further evidence on performance evaluation: Portfolio holdings,recommendations, and turnover costs

This paper analyzes the performance of mutual funds in Spain between January 1980 and June 1990. The robustness of results to alternative measurements and benchmarks are analyzed. The results indicate that, with monthly returns alone, it is not possible to distinguish between selectivity and timing. We are only able to measure the magnitude of total performance. To be more precise about the reasons behind performance, portfolio holdings are necessary. This work employs a new data set based on monthly portfolio holdings of a representative sample of funds. A comparison of results using monthly returns and monthly portfolio holdings is made. In particular, thanks to the availability of portfolio holdings, we are able to separate selectivity and timing. Finally, the impact of turnover costs is considered.     

Do commodities add value in multi-asset portfolios? An out-of-sample analysis for different investment strategies

An essential motive for investing in commodities is to enhance the performance of portfolios traditionally including only stocks and bonds. We analyze the in-sample and out-of-sample portfolio effects resulting from adding commodities to a stock-bond portfolio for commonly implemented asset allocation strategies such as equally- and strategically-weighted portfolios, risk-parity, minimum-variance as well as reward-to-risk timing, mean-variance and Black–Litterman. We analyze different commodity groups such as agricultural and livestock commodities that currently are critically discussed. The out-of-sample portfolio analysis indicates that the attainable benefits of commodities are much smaller than suggested by previous in-sample studies. Hence, in-sample analyses, such as spanning tests, might exaggerate the advantages of commodities. Moreover, the portfolio gains greatly vary between different types of commodities and sub-periods. While aggregate commodity indices, industrial and precious metals as well as energy improve the performance of a stock-bond portfolio for most asset allocation strategies, we hardly find positive portfolio effects for agriculture and livestock. Consequently, investments in food commodities are not essential for efficient asset allocation.     

A jackknife-type estimator for portfolio revision

This article proposes a novel approach to portfolio revision. The current literature on portfolio optimization uses a somewhat naïve approach, where portfolio weights are always completely revised after a predefined fixed period. However, one shortcoming of this procedure is that it ignores parameter uncertainty in the estimated portfolio weights, as well as the biasedness of the in-sample portfolio mean and variance as estimates of the expected portfolio return and out-of-sample variance. To rectify this problem, we propose a jackknife procedure to determine the optimal revision intensity, i.e. the percent of wealth that should be shifted to the new, in-sample optimal portfolio. We find that our approach leads to highly stable portfolio allocations over time, and can significantly reduce the turnover of several well established portfolio strategies. Moreover, the observed turnover reductions lead to statistically and economically significant performance gains in the presence of transaction costs.     

Measuring bond mutual fund performance with portfolio characteristics

This paper studies the performance of U.S. bond mutual funds using measures constructed from a novel data set of portfolio weights. Active fund managers exhibit outperformance before costs and fees generating, on average, gross returns of 1% per annum over the benchmark portfolio constructed using past holdings (approximately the same magnitude as expenses and transaction costs combined). This suggests that fund managers are able to earn back their fees and costs. There is evidence of neutral ability to time different portfolio allocations (sector, credit quality, and portfolio maturity allocations) and only a subgroup of bond funds exhibit successful timing ability. One performance measure based on portfolio holdings predicts future fund performance and provides information not contained in the standard measures. These results provide the first evidence of the value of active management in bond mutual funds.     

Análisis de portafolio por sectores mediante el uso de algoritmos genéticos: caso aplicado a la Bolsa Mexicana de Valores

The type of industry, size of company, number of employees, etc. are variables that are considered as control variables in a large number of articles. In this research we consider the sector variable as a determinant of financial performance (Baird et al. 2012) and the risk (Artikis and Nifora, 2011) rather than as a control variable. This paper analyzes six sectors of the Mexican economy divided according to the Mexican Stock Exchange: industrial, basic consumer products, materials, non basic consumer products, telecommunications and financial services. The sample consists of Mexican companies, that is, 30 companies in the 2007-2012 period. To measure portfolio performance two classic indicators are used: (1) Jensen alpha and (2) Sharpe ratio, and also conditional metrics are used that measures the number of times the portfolio return exceeds the market average. The goal is to find a portfolio that maximizes these parameters and compare the results between the different sectors under study. Due to a nonlinear programming problem, genetic algorithms are used to obtain the optimal portfolio that maximizes these metrics. The results show a better risk-adjusted financial performance in the field of materials and financial services and a lower performance in such sectors as the industrial and telecommunications ones.     

Markowitz efficiency and size effect: evidence from the UK stock market

Academics and practitioners have frequently debated the relationship between market capitalization and expected return. We apply the Markowitz efficient frontier approach to develop a portfolio performance measure that compares the return of a portfolio to its optimal return, using data from the UK stock market over the period 1985–2012. Our results show that there is a negative relationship between portfolio size and portfolio return during the period under study. When comparing actual portfolio return with achievable return for the same level of risk, we find that as the portfolio size expands, underperformance of the portfolio increases, i.e. the larger the portfolio size, the greater the underperformance. This indicates that Markowitz efficiency is difficult to achieve, particularly in large portfolios. Changing model parameters leads to alternative efficient frontiers that impact upon the measurement of performance. However, the use of alternative efficient frontiers does not affect our result of the size effect on the relative performance of portfolios. Our study shows that the size effect is present over the full period. Our findings also suggest that the excess returns found in small portfolios are likely to be associated with higher levels of diversifiable risk in comparison with larger portfolios. Furthermore, in contrast to other studies, we find no evidence to support the size reversal effect in the data.