What drives the “Smart-Money” effect? Evidence from investors’ money flow to mutual fund classes

Jiang, George J.; Yüksel, H. Zafer

doi:10.1016/j.jempfin.2016.11.005

Cited by 40 publications

(15 citation statements)

References 39 publications

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“…Table reports the performance of average, positive, and negative flow portfolios based on the four‐factor model, as well as the difference in factor alpha (α 4F ) between positive and negative flow portfolios. We note that all flow‐sorted portfolios have negative abnormal returns, consistent with the literature that mutual funds, after expenses and accounting for momentum, on average underperform their benchmarks (Carhart, ; Jiang & Yuksel, ; Sapp & Tiwari, ). More importantly, Table shows a positive relation between retail fund flow and future fund performance for retails funds during the whole sample period.…”

Section: Flow‐performance Relation and Investor Timing Ability: High supporting

confidence: 86%

“…In this section, we perform additional analysis to test whether the positive flow‐performance relation is due to smart money or flow‐induced performance. Coval and Stafford (), Lou (), and Jiang and Yuksel () show that fund flow is highly persistent, thus predictable. Following these studies, we decompose fund flows into expected and unexpected components.…”

Section: Flow‐performance Relation and Investor Timing Ability: High mentioning

confidence: 99%

“…The main explanatory variable is normalized fund flow (

Flo {normalw}_{i, t - 1}

). Other control variables include fund four‐factor alpha, expense ratio, fund size, age, return volatility, portfolio turnover, and family size at month t − 1 (Carhart, ; Chen et al., ; Gil‐Bazo & Ruiz‐Verdu, ; Gruber, ; Jiang & Yuksel, ). To distinguish between smart‐money and flow‐induced performance hypotheses, we further decompose fund flow into expected (or predictable) and unexpected components.…”

Section: Flow‐performance Relation and Investor Timing Ability: High mentioning

confidence: 99%

See 2 more Smart Citations

Sentimental mutual fund flows

Jiang

Yüksel

2019

The Financial Review

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We show that many stylized empirical patterns for mutual fund flows are driven by investor sentiment. Specifically, when sentiment is high, investors exhibit a stronger tendency of chasing past fund performance; fund flows are less sensitive to fund expenses; and investors are attracted more to funds with sheer visibility. Moreover, the well‐documented positive relation between fund flows and future fund performance is significant only during high sentiment periods and is mainly driven by expected component of fund flows. Finally, we show that mutual fund investors exhibit a significantly negative timing ability at the individual fund level when sentiment is high.

show abstract

Section: Flow‐performance Relation and Investor Timing Ability: High supporting

confidence: 86%

Section: Flow‐performance Relation and Investor Timing Ability: High mentioning

confidence: 99%

“…The main explanatory variable is normalized fund flow (

Flo {normalw}_{i, t - 1}

Section: Flow‐performance Relation and Investor Timing Ability: High mentioning

confidence: 99%

See 1 more Smart Citation

Sentimental mutual fund flows

Jiang

Yüksel

2019

The Financial Review

Self Cite

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“…The literature found a significant positive association between mutual fund flows and future mutual fund performance (e.g., Gruber, ; Jiang & Yuksel, ). Fund performance is related to its attractiveness.…”

Section: Methodsmentioning

confidence: 99%

Mutual fund performance: The decision quality and capital magnet efficiencies

Hsieh

Tebourbi

et al. 2020

Manage Decis Econ

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This study employs a two-stage network data envelopment analysis model to analyze the decision quality and capital magnet efficiencies of 155 mutual funds in Taiwan during the period 2007-2016. The empirical results show that fund managers improved their decision quality; however, their capital magnet efficiency declined.This study also found 10 mutual funds performing in decision quality and capital magnet efficiencies, from which practical suggestions are provided to investors.Finally, this study constructs a market competition matrix to help fund managers (and investors) improve their operating and portfolio performance, plus resource allocation.

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“…To take just one example, on 9 th June 2015 when the day's market return on the Shanghai Composite Index reached 5.76%, as many as 87.7% of the tradeable A shares hit the upper price limit. The consequence of hitting the upper limit is that no further trades that would involve further upward price movements are permissible until 1 See among others, Jotikasthira et al, 2012;Kirchler et al, 2015;Razena et al, 2017;Jiang and Yuksel, 2017;Yang and Yang, 2019. 2 According to retail investors' holding value data from China Securities Depository & Clearing Corporation Limited, the percentage of retail accounts whose stock holding market value exceeding 1 million in 2011 and 2016 are only 0.82% and 2.75%.…”

Section: Introductionmentioning

confidence: 99%