Examining the Performance of Indian Exchange Traded Funds (ETFs)

Sethi, Naman

doi:10.17015/ejbe.2016.018.04

Cited by 4 publications

(7 citation statements)

References 6 publications

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“…Following the existing literature (Rompotis, 2012 ; Reddy, 2012; Alam, 2013 ; Narend & Thenmozhi, 2016 ; Sethi, 2016 ; Malhotra et al, 2016 ; Singh & Kaur, 2016 ) we estimate the performance and tracking efficiency of the sample equity ETF’s.…”

Section: Methodsmentioning

confidence: 99%

“…An Ordinary Least Square (OLS) regression is performed to resolve a set a of gripping issues (Prather et al, 2009 ; Rompotis, 2010 , 2012 ; Charupat & Miu, 2013 ; Sethi, 2016 ). As the results of Augumented Dickey Fuller test indicated that the returns of ETF’s and Indexes are stationary, OLS regression model can be carried out using the following equation: where R pt denote the sample ETF’s average raw return on day t , R bt represents average raw return of the underling benchmark on day t and residual error is denoted by ε pt .…”

Section: Methodsmentioning

confidence: 99%

“…Singh and Kaur ( 2016 ) revealed that volume traded and Assets under Management of ETF’s positively affect the tracking efficiency of the ETF whereas volatility negatively influence the tracking ability of ETF. Sethi ( 2016 ) found that management expenses and risks positively impact the tracking error of the ETF. Other factors that can impact the level of tracking error of an ETF include the differences in investment styles, market capitalization, number of securities and index volatility in the ETF portfolio (Aber et al, 2009 ; Rompotis, 2010 , 2011 , 2012 ; Bello, 2012 ; Buetow & Henderson, 2012 ; Charupat & Miu, 2013 ; Reddy, 2013 ; Bas & Sarioglu, 2015 ; Narend & Thenmozhi, 2016 ; Sethi, 2016 ; Singh & Kaur, 2016 ).…”

Section: Methodsmentioning

confidence: 99%

“…Defusco et al ( 2011 ) used pricing deviation as the performance metric to evaluate the ETF’s for which, the sample of Spiders, Cubes and Diamonds were chosen and the author explains the price deviation of the sample is non-zero, predictable that can be attributed to stationarity, accumulation and distribution of dividends and specific price discovery process. Sethi ( 2016 ) studied ETF’s listed on NSE, India to examine their performance with respect to risk, return, expenses and trading characteristics. The study concluded that ETF’s have underperformed the benchmark indices and have loaded investors with an extra amount of risk.…”

Section: Literature Reviewmentioning

confidence: 99%

See 3 more Smart Citations

Investment Performance and Tracking Efficiency of Indian Equity Exchange Traded Funds

Alamelu¹,

Goyal

2022

Asia-Pac Financ Markets

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Exchange Traded Funds (ETF’s) are one of the beloved passively managed funds that offer both retail and institutional investors an access to highly profitable and wide- range of diversifiable financial assets. The study aims to assess the ability of Indian equity ETF’s in replicating the performance of their benchmark indices using a sample of 27 equity ETF’s traded on the National Stock Exchange of India during the pre-pandemic period from 01/01/2015 to 31/12/2019. Evaluation of the performance of sample ETF’s through risk-return analysis, risk-adjusted performance measures, tracking error analysis and multi-factor regression have revealed that the majority of the sample ETF’s outperformed their tracking indices but with notable tracking errors during the study period. Further, the study also indicates that the returns of the sample ETF’s have a significant and positive relationship with the returns of the index but are inversely related to risk and management fees. The results of this study will have major implications for investors in evaluating the performance of ETF’s and fund managers as well in taking suitable measures to reduce tracking errors that will help in successful replication of the benchmark along with undertaking initiatives that will enable the ETF’s to become price efficient.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

See 2 more Smart Citations

Investment Performance and Tracking Efficiency of Indian Equity Exchange Traded Funds

Alamelu¹,

Goyal

2022

Asia-Pac Financ Markets

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“…A base de dados coletados utilizada para a realização deste trabalho foi obtida na plataforma Bloomberg, sendo composta pelos preços de fechamento diários das cotas dos fundos, valores diários de fechamento dos seus índices de referência e pelos valores diários de fechamento das cotas do valor patrimonial líquido dos referidos fundos, de 2 de dezembro de 2008 até 10 de setembro de 2018, perfazendo um total de 2.416 observações. Os cálculos foram feitos utilizando as ferramentas de análise e estatísticas do programa Microsoft Excel Modelo de identificação da estratégia de replicação Conforme aplicado porRompotis (2012) eSethi (2016), uma regressão simples é utilizada para desvendar uma série de elementos relevantes: Tracking Error Rompotis (2012) define o termo "tracking error" como os desvios nos retornos de produtos de investimentos geridos de forma passiva e os seus benchmarks, cujo…”

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Uma Análise Da Eficiência De Exchange-Traded Funds Brasileiros: 2008-2018

CONDE¹

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The objective of this study is to analyze the pricing efficiency of three of the most liquid brazilian Exchange-Traded Funds (BOVA11, SMAL11 and PIBB11) and determine if they follow closely the indexes they try to replicate, comparing with the international literature regarding the foreign ETFs performance. Firstly, this study verifies which strategy is adopted by each fund, as well as the quality of this replication by evaluating the tracking error observed in these funds. Then it is analyzed if there is any deviation between the trading price and the net asset value (NAV) of the respective ETF, that is, if the security is being traded, on average, with a premium or discount. Finally, it is evaluated the persistence of those premiums and discounts found, that is, how much time it takes until the trading price and the NAV go back to equilibrium. The results showed that both BOVA11 and PIBB11 adopt a full replication strategy, while SMAL11 presents an optimization strategy. The tracking error found is in line with those observed in European ETFs and the three funds are traded, on average, with a discount. Finally, both BOVA11 and PIBB11 take seven days to go back to equilibrium, while SMAL11 only takes two days, an unexpected result as this is the least liquid fund of the three that are part of this study. Therefore, the arbitrage tools are not being used efficiently.

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