JournalTOCs

International Journal of Portfolio Analysis and Management
Number of Followers: 3

Hybrid journal (It can contain Open Access articles)
ISSN (Print) 2048-2361 - ISSN (Online) 2048-237X
Published by Inderscience Publishers

[451 journals]

Why are 'true' active managers essential for markets?
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  Authors: Jinfeng Wang, Gongfa Li, Ying Liu, Juntong Yun, Yuting Liu, Licheng Huang, Du Jiang
  Pages: 199 - 223
  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; ETFs; volatility spillover; systemic risk; fund flows; market efficiency
  Citation: International Journal of Portfolio Analysis and Management, Vol. 2, No. 3 (2021) pp. 199 - 223
  PubDate: 2021-06-15T23:20:50-05:00
  DOI: 10.1504/IJPAM.2021.115629
  Issue No: Vol. 2, No. 3 (2021)
An efficient equity investing model using smart beta based on market phase
information
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  Authors: Jinfeng Wang, Gongfa Li, Ying Liu, Juntong Yun, Yuting Liu, Licheng Huang, Du Jiang
  Pages: 224 - 237
  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 optimisation model to use the characteristics of these rates of return. Empirical analyses show that the proposed model achieves better performance than both the market index and a normal portfolio optimisation model used in Japanese and global markets.
  Keywords: asset management; smart beta; factor investing; portfolio optimisation; conditional mean-absolute deviation model; market phase information
  Citation: International Journal of Portfolio Analysis and Management, Vol. 2, No. 3 (2021) pp. 224 - 237
  PubDate: 2021-06-15T23:20:50-05:00
  DOI: 10.1504/IJPAM.2021.115631
  Issue No: Vol. 2, No. 3 (2021)
New smart beta index using the Rachev ratio under a non-normal return
distribution
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  Authors: Rei Yamamoto, Naoya Kawadai
  Pages: 238 - 248
  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 non-convexity. 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: Rachev ratio; smart beta; non-normal distributions; global markets
  Citation: International Journal of Portfolio Analysis and Management, Vol. 2, No. 3 (2021) pp. 238 - 248
  PubDate: 2021-06-15T23:20:50-05:00
  DOI: 10.1504/IJPAM.2021.115632
  Issue No: Vol. 2, No. 3 (2021)
Stochastic volatility modelling in portfolio selection via sequential
Monte Carlo simulation
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  Authors: Igor Ferreira Do Nascimento, Pedro Henrique Melo Albuquerque, Yaohao Peng
  Pages: 249 - 267
  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 overcoming non-additivity and non-Gaussian disturbance pattern. The historical statistics use an optimist Black-Litterman priori view to systematise our analysis in a rolling window. Our proposed method has 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
  Citation: International Journal of Portfolio Analysis and Management, Vol. 2, No. 3 (2021) pp. 249 - 267
  PubDate: 2021-06-15T23:20:50-05:00
  DOI: 10.1504/IJPAM.2021.115633
  Issue No: Vol. 2, No. 3 (2021)
Asset allocation and downside risk
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  Authors: Igor Ferreira Do Nascimento, Pedro Henrique Melo Albuquerque, Yaohao Peng
  Pages: 268 - 284
  Abstract: Economists have long recognised that investors care more about downside risk than total variation, which includes upside gains. This paper develops a new technique, along the lines of Sharpe's (1990, 1992) asset-class model, to measure the performance of an actively managed portfolio with respect to downside risk. The new technique involves choosing a multiple asset-class benchmark with the highest possible correlation with the active strategy return subject to the constraint that the risks are the same. The risk-matched portfolio can be used to measure the performance of an active portfolio with respect to downside risk. Because, by construction the risk of the benchmark is the same as the active portfolio, it is a simple matter to compare the performance of the active to the benchmark using the Sortino ratio. To illustrate the new technique, we compare the performance of exchange traded funds that track S&P equal-weighted and value weighed sector indexes.
  Keywords: asset-class models; downside risk; performance measurement; Sharpe ratio; Sortino ratio
  Citation: International Journal of Portfolio Analysis and Management, Vol. 2, No. 3 (2021) pp. 268 - 284
  PubDate: 2021-06-15T23:20:50-05:00
  DOI: 10.1504/IJPAM.2021.115662
  Issue No: Vol. 2, No. 3 (2021)