An Examination of Institutional Dividend Clienteles: Evidence from Australian Institutional Portfolio Holdings

2006 ◽  
Author(s):  
Aelee Jun ◽  
David R. Gallagher ◽  
Graham Partington
Keyword(s):  
Portfolio Holdings

On the ability of New Zealand actively managed funds to generate outperformance in their domestic equity allocations

2018 ◽  
Vol 30 (4) ◽  
pp. 463-481 ◽  
Author(s):  
Bart Frijns ◽  
Ivan Indriawan
Keyword(s):  
New Zealand ◽  
Stock Returns ◽  
Tracking Error ◽  
Tracking Errors ◽  
Content Type ◽  
Portfolio Holdings ◽  
Market Index ◽  
Stock Picking ◽  
Fund Size ◽  
Managed Funds

Purpose This paper aims to assess the ability of New Zealand (NZ) actively managed funds to generate risk-adjusted outperformance using portfolio holdings data. Focusing on domestic equity allocations addresses the benchmark selection issue, particularly for funds with national and international exposures. Design/methodology/approach The authors assess performance using several asset pricing models including the CAPM, three-factor and four-factor models. The authors also assess performance across funds with different characteristics such as fund size, size of local holdings, type of fund provider, past returns and fees. The authors further examine whether funds engage in any stock-picking or market timing by considering the active share and tracking error. Findings The returns on NZ equity holdings of NZ actively managed funds from 2010 to 2017 provide little evidence of risk-adjusted outperformance and stock-picking skill. These exposures yield pre-cost returns that have a nearly perfect correlation with the market index and an insignificant alpha. Funds show little tendency to bet on any of the main characteristics known to predict stock returns, such as size, book-to-market and momentum. In addition, the authors show that the average active shares and tracking errors are low, suggesting that the majority of funds hold NZ equity portfolios that closely mimic the market index. Originality/value Existing studies rely on returns data which aggregate performance across all asset classes with varying exposures. This may lead to benchmark selection issues (particularly for funds with international exposures) which may obscure the fund manager’s true stock-picking skills. Assessment using holdings data would enable suitable performance measurement by researchers and industry analysts.

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