Identifying the interaction between stock market returns and trading flows of investor types: Looking into the day using daily data

Ülkü, Numan; Weber, Enzo

doi:10.1016/j.jbankfin.2013.03.021

Cited by 17 publications

(63 citation statements)

References 65 publications

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“…Schmeling () found that sentiment indexes are non‐stationary, and whilst we are measuring sentiment differently to Schmeling, who used an index of consumer confidence, if order flow metrics reflect sentiment they are also likely to be non‐stationary. Moreover, Ülkü and Weber () conduct Dickey–Fuller non‐stationarity tests on aggregate order flow of different types of institutional investors and find that the level of each series is non‐stationary, but that changes are stationary. Since our order flow imbalance measures are constructed from order flow information, we would also expect them to be non‐stationary.…”

Section: Summary Statisticsmentioning

confidence: 99%

Sentiment, order imbalance, and co‐movement: An examination of shocks to retail and institutional trading activity

Chelley‐Steeley

Lambertides

Savva

2017

Euro Fin Management

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Using order flow imbalance as a measure of sentiment we show that positive and negative shocks to sentiment lead to lower co‐movement between portfolio and market returns in the post‐shock period. Furthermore, an asymmetry is present as positive shocks to sentiment have less impact on co‐movement changes than negative shocks. Moreover, shocks to retail sentiment and the sentiment of two types of institutional investors lead to a reduction in co‐movement. Positive shocks to institutional order flow imbalance lead to smaller reductions in co‐movement than associated with retail shocks. These effects exist even after controlling for firm‐specific and market‐wide news.

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Section: Summary Statisticsmentioning

confidence: 99%

Sentiment, order imbalance, and co‐movement: An examination of shocks to retail and institutional trading activity

Chelley‐Steeley

Lambertides

Savva

2017

Euro Fin Management

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“…However, odd-lot transactions have lost their relevance over time, and recent evidence suggests that trader-type classifications based on trade size got blurred as a result of electronic trading and order divisibility (Hvidkjaer 2008, Campbell et al 2009). §See Kim et al (2009) and Ülkü and Weber (2013) for recent comprehensive studies of KSE trading flows data.…”

Section: Mondays and Reversals In Koreamentioning

confidence: 99%

“…The analysis in Ülkü and Weber (2013) indicates that foreign and institutional investors' price impact in KSE is permanent over a horizon up to 10 days; net foreign flow shocks do even positively forecast future returns after controlling for intraday positive feedback trading. Thus, for the purposes of the current analysis with a five-day horizon, foreigners can be treated as informed traders.…”

mentioning

confidence: 96%

“…Kim et al (2009) and Ülkü and Weber (2013)]. The conclusions of the literature on trading by investor types can be summarized as follows: individuals appear to be uninformed contrarian liquidity suppliers.…”

mentioning

confidence: 99%

“…However, as they do not charge a bid-ask spread, their role is different from that of a market maker. The analysis of Ülkü and Weber (2013) indicates that individuals' net trading negatively forecasts future returns up to a horizon of 10 days, § which contrasts the market makers who earn zero profits in Kyle (1985) and FW models. On the other hand, these individual traders do not arrive randomly as assumed of liquidity traders in Kyle and FW models, hence they cannot be assigned the role of liquidity traders, either.…”

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confidence: 99%

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Reversal of Monday returns

Ülkü

Andonov

2015

Quantitative Finance

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This paper elaborates an interesting aspect of the Monday anomaly: Monday returns are relatively more likely to reverse over the subsequent days. We document that, although the Monday low-return anomaly disappeared, the subsequent reversal of Monday returns remains robust to date. The reversals, measured over a five-day horizon, are pervasive across international stock markets, reasonably stable over time, significant following both positive and negative Monday returns, and not confined to extreme Monday returns. Trading strategies designed to exploit these reversals earn economic profits. We examine potential explanations for the reversal of Monday returns using trading flows data of investor types from Korea. All predictions of the Foster and Viswanathan [J. Finance, 1993, 48, 187-211] model are confirmed: volatility is higher, trading volume is lower, market depth is lower and price impact costs are higher on Mondays. The model implies lower price quality on Mondays, but does not specifically predict reversal of Monday returns. We show that the trading intensity of international/institutional investors is lower on Mondays. This appears to make the market relatively more susceptible to individual investors' trading, which is negatively correlated with international/institutional investors. Thus, Monday returns are relatively more likely to reverse during the subsequent days of the week when institutional investors trade more aggressively.

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Investor types' trading around the short‐term reversal pattern

Оніщенко

Ülkü

2020

Int. J Fin Econ

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Using exact and complete Korean data of investor trading, we provide an anatomy of investor types' trading throughout the short-horizon overshootingand-reversal pattern in stock returns. We document two forms of non-optimal trading behaviour associated with the pattern: First, institutional investors' chasing of return shocks at the overshooting point, particularly in the large-cap segment. Second, individual investors' buying of winner stocks in the small-cap segment, consistent with an attention-driven speculative buying bias.attention-driven buying, investor response to stock return shocks, overshooting and short-term reversals, trading flows of investor types

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Identifying the interaction between stock market returns and trading flows of investor types: Looking into the day using daily data

Cited by 17 publications

References 65 publications

Sentiment, order imbalance, and co‐movement: An examination of shocks to retail and institutional trading activity

Sentiment, order imbalance, and co‐movement: An examination of shocks to retail and institutional trading activity

Reversal of Monday returns

Investor types' trading around the short‐term reversal pattern

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