International portfolio allocation: The role of conditional higher moments

Le, Trung H.

doi:10.1016/j.iref.2020.09.005

Cited by 7 publications

(4 citation statements)

References 62 publications

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“…Finally, we find that the asymmetric models provide better performance than the symmetric alternatives. This result is in line with Bams et al (2017), Slim et al (2017), and Le (2021) and highlights the importance of allowing for the leverage effect in the conditional volatility.…”

Section: Resultssupporting

confidence: 89%

“…In his seminal work, Hansen (1994) shows that return skewness and kurtosis are also time‐varying (see, e.g., Harvey & Siddique, 1999; Jondeau & Rockinger, 2003, for further empirical evidence). Consequently, several empirical studies highlight the importance of accounting for higher moments in asset pricing (e.g., Dittmar, 2002; Harvey & Siddique, 2000), portfolio allocation (e.g., Ghysels et al, 2016; Harvey et al, 2010; Le, 2021), and risk management (e.g., Bali et al, 2008; Kostika & Markellos, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…Zhu (2013) documents the importance of additional information provided by return distribution predictability up the fourth moment for portfolio selection using a combined approach of quantile regression and copulas. Similarly, Ghysels et al (2016), Hadhri and Ftiti (2019), and Le (2021) explore that incorporating conditional skewness and kurtosis significantly changes the optimal weights to emerging countries and resulting in sizable economic gains in an international portfolio allocation analysis. He and Hamori (2021) argue that the skewness spillover from developed markets is important for investor decisions in emerging markets.…”

Section: Introductionmentioning

confidence: 99%

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Forecasting VaR and ES in emerging markets: The role of time‐varying higher moments

2023

Journal of Forecasting

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This paper aims at the role of accounting for time‐varying higher moments in conditional volatility models in emerging markets. In particular, we perform a comprehensive analysis of out‐of‐sample value at risk (VaR) and expected shortfall (ES) forecasts of eight generalized autoregressive conditional heteroskedasticity (GARCH) models with alternative distributions for 10 leading emerging markets. To evaluate the forecast accuracy, we employ a battery of absolute performance backtests and two alternative loss functions in the relative performance exercises. We find that the asymmetric GARCH models with time‐varying skewness and kurtosis significantly outperform traditional GARCH‐based forecasts across quantiles across quantile levels. In particular, we explore that the superior performance of the GARCH models with improved distributions is mainly driven by their performance during crisis periods, where the traditional GARCH specifications often underestimate the tail risk in the markets.

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Section: Resultssupporting

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Forecasting VaR and ES in emerging markets: The role of time‐varying higher moments

2023

Journal of Forecasting

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“…In the parametric portfolio policy, the parameter space does not increase with the number of assets, but with the number of asset characteristics. Additionally, the parametric strategy is good at exploring the impact of time‐varying characteristics on portfolio weights and has become popular in portfolio selection (see Barroso & Santa‐Clara, 2015; Laborda & Olmo, 2017; Laborda & Olmo, 2020; Le, 2021). Thus, we adopt a parametric portfolio policy to capture the impact of the topological characteristics of LS networks on asset allocation.…”

Section: Literature Reviewmentioning

confidence: 99%

The role of long‐ and short‐run correlation networks in international portfolio selection

Jiang

et al. 2023

Int. J Fin Econ

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By considering the effect of long‐ and short‐run correlation (LS) networks, we propose an LS network‐augmented parametric portfolio selection model (LSNA‐PP). First, we combine the dynamic conditional correlation‐mixed data sampling (DCC‐MIDAS) model with the planar maximally filtered graph (PMFG) method to construct LS networks and extract network topological characteristics. Second, we design portfolio weights as a function of these topological characteristics to construct the LSNA‐PP model. Third, we apply the model to construct an international portfolio from 2010 to 2021. The empirical results illustrate the efficacy of the LSNA‐PP model in two ways. First, the LSNA‐PP model clarifies the economic interpretation of topological characteristics in portfolio selection, such as the positive effect of the long‐run correlation network and the negative effect of the short‐run correlation network on the weights. Second, the LSNA‐PP model performs well in terms of return expectations, risk diversification, and attractive risk‐adjusted returns, which are especially useful for stakeholders such as regulators, managers, and investors.

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Median-adaptive portfolios: a minimum criteria approach to asset allocation

Kyriazi,

Tarani,

Thomakos

2023

Ann Oper Res

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We propose a new class of adaptive portfolios for asset allocation, based on a one-parameter variation of the equally weighted portfolio and the use of the median-ranked asset. Our methodological contribution offers a simple way of performing, static or optimized, allocation of assets in portfolios of any dimension, thus easily circumventing the “curse of dimensionality”. Our results show that, even for a static selection of the parameter that defines our allocation, we obtain improved performance compared to the equally weighted benchmark in all the standard metrics. For the case of an optimized selection of the parameter we offer results from minimum variance optimization, that do require the estimation of the covariance matrix, but our approach can easily be adapted to other kinds of portfolio objective functions. This new class of portfolios can easily be added to, as a complement or substitute, to any existing portfolio allocation method.

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International portfolio allocation: The role of conditional higher moments

Cited by 7 publications

References 62 publications

Forecasting VaR and ES in emerging markets: The role of time‐varying higher moments

Forecasting VaR and ES in emerging markets: The role of time‐varying higher moments

The role of long‐ and short‐run correlation networks in international portfolio selection

Median-adaptive portfolios: a minimum criteria approach to asset allocation

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