Forthcoming articles

International Journal of Portfolio Analysis and Management

International Journal of Portfolio Analysis and Management (IJPAM)

These articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

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International Journal of Portfolio Analysis and Management (4 papers in press)

Regular Issues

  • Why are 'true' active managers essential for markets?   Order a copy of this article
    by John Galakis 
    Abstract: There has been tremendous growth in the assets managed through passive strategies both by institutional and private investors, especially over the last 20 years. This trend is not expected to abate anytime soon; on the contrary, it is projected to intensify, as investors have been increasingly rotating out of underperforming and higher cost active strategies into lower cost index-related ones. Besides cost, index-linked investing exhibits numerous benefits. There is, however, ample empirical evidence that shows that it is creating widespread price distortions that have considerable impact on individual security and market risk/return distributions. This dark side of passive investing has sizeable repercussions for corporate investing and investor portfolio allocation decisions. In this environment, the presence of true active managers is essential, as they could offset part of the distortions.
    Keywords: Passive Investing; Active Investing; Active Managers; Index Premium; Index Turnover Cost; Co-movement; Price Detachment; Exchange Traded Funds; Volatility Spillover; Systemic Risk; Fund Flows; Market Efficiency.

  • An Efficient Equity Investing Model Using Smart Beta Based on Market Phase Information   Order a copy of this article
    by Rei Yamamoto 
    Abstract: Recently, smart beta has become popular and its exchange-traded funds (ETFs) are now sold by asset management companies. Therefore, by using low-cost smart beta ETFs, we can easily conduct factor investing. We propose a market phase classification method based on market directions and cross-sectional volatility to explain the rates of return of smart beta indices and a conditional portfolio optimization model to use the characteristics of these rates of return. Empirical analyses show that our proposed model achieves better performance than both the market index and a normal portfolio optimization model used in Japanese and global markets.
    Keywords: asset management; smart beta; factor investing; portfolio optimization; conditional mean-absolute deviation model; market phase information.

  • New Smart Beta Index Using the Rachev Ratio Under a Non-Normal Return Distribution   Order a copy of this article
    by Rei Yamamoto, Naoya Kawadai 
    Abstract: In this paper, we focus on the Rachev ratio proposed by Biglova et al. (2004) and propose a new smart beta index using it. This ratio has demonstrated its effectiveness as a performance measure; however, it is difficult to consider it to be a portfolio tool, particularly due to its nonconvexity. Therefore, we propose a simple weighting method to construct a portfolio, transforming it into a new smart beta index. Moreover, we compare its performance with other smart beta indices in the global stock markets. The result of our empirical analysis, corroborate our contention that the proposed smart beta index using the Rachev ratio provides higher performance than other standard smart beta indices. Hence, we conclude that this smart beta is a new effective index that can be used in global stock markets.
    Keywords: portfolio; Rachev ratio; smart beta; non-normal distributions; global markets.

  • Stochastic volatility modeling in portfolio selection via sequential Monte Carlo simulation   Order a copy of this article
    by Igor Do Nascimento, Pedro Albuquerque, Yaohao Peng 
    Abstract: This paper uses Particle Filter to estimate daily volatility in the Brazilian financial stocks market and obtain an optimal allocation of assets via Monte Carlo approach. Our volatility model outperforms the Kalman Filter besides overcome non-additivity and non-Gaussian disturbance pattern. The historical statistics use an optimist Black-Litterman priori view to systematize our analysis in a rolling window. Our propose have better out-of-sample metrics than Markowitz, Naive (equal assets weight) and Bovespa Index benchmark.
    Keywords: Stochastic Volatility; Particle Filter; Monte Carlo Methods; Dynamic Models; Portfolio Allocation; Bayesian analysis.