2018
DOI: 10.1108/ijmf-09-2017-0187
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Effects of asymmetric information on market timing in the mutual fund industry

Abstract: Purpose The purpose of this paper is to investigate the effects of information asymmetry (between the realized return and the expected return) on market timing in the mutual fund industry. Design/methodology/approach For the purpose, the authors use a panel of 1,488 active open-end mutual funds for the period 2004-2013. The authors use fund-specific time-dynamic betas. The information asymmetry is measured as the standard deviation of idiosyncratic risk. The data set is decomposed into five market fundamenta… Show more

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Cited by 62 publications
(37 citation statements)
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References 38 publications
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“…Consistent with the attendant literature (Bond et al, 2001;Tchamyou & Asongu, 2018), the system GMM estimator (Arellano & Bover, 1995;Blundell & Bond, 1998) has better properties of estimation relative to the difference estimator (Arellano & Bond, 1991).…”
Section: Specificationsupporting
confidence: 73%
“…Consistent with the attendant literature (Bond et al, 2001;Tchamyou & Asongu, 2018), the system GMM estimator (Arellano & Bover, 1995;Blundell & Bond, 1998) has better properties of estimation relative to the difference estimator (Arellano & Bond, 1991).…”
Section: Specificationsupporting
confidence: 73%
“…This procedure of estimation is typically in line with the income catch-up scholarship that has been assessed building on models of neoclassical growth, notably: Baumol (1986); Sala-i-Martin (1992, 1995) and Mankiw et al (1992). The attendant theoretical insights have been extended to other areas of development studies, inter alia: financial markets and financial intermediary developments (Narayan et al, 2011;Tchamyou & Asongu, 2017;Tchamyou et al, 2018;Efobi et al, 2019).…”
Section: Methodsmentioning
confidence: 85%
“…A plethora of reasons motivate the choice of an alternative system GMM estimation strategy, notably, that it (i) does not eliminate cross‐country variations, (ii) controls for potential endogeniety in all regressors through instrumentation and accounts for the unobserved heterogeneity, and (iii) mitigates potential small sample biases from the difference estimator (Asongu, ; Tchamyou, Asongu, & Nwachukwu, ). Moreover, basic conditions for the use of the GMM strategy are also fulfilled, notably: (i) the condition for persistence is apparent because the correlation coefficient between the outcome variable and its first lag is higher than 0.800, which is the rule of thumb for establishing persistence in an outcome variable; and (ii) the number of cross sections (or 44 countries) is higher than the number of periods in each cross section (or 13 years).…”
Section: Methodsmentioning
confidence: 99%