New evidence of quarterly return patterns in the Spanish stock market

Ortiz, Cristina; Zárate, José M. Ortiz de; Vicente, Luis

doi:10.1080/13504851.2014.995358

Cited by 3 publications

(5 citation statements)

References 11 publications

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“…First, Ortiz et al (2015) find no return anomalies in the first three quarters of their sample years; however, in the fourth quarter they find a significant turn-of-the-year effect for small-cap stocks with poor performance, which could influence our results as well. Second, Lou and Schinckus (2015) document an asymmetric effect of small and large stocks indicating that herding behavior is particularly present for small stocks in bullish periods, while in bearish times crowd moves for large shares, which in our analysis might lead to biased estimations of the microstructure without controlling for the size effect.…”

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confidence: 68%

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Market microstructure during financial crisis: Dynamics of informed and heuristic-driven trading

Ormos

Timotity

2016

Finance Research Letters

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We implement a market microstructure model including informed, uninformed and heuristicdriven investors, which latter behave in line with loss-aversion and mental accounting. We show that the probability of informed trading (PIN) varies significantly during 2008. In contrast, the probability of heuristic-driven trading (PH) remains constant both before and after the collapse of Lehman Brothers. Cross-sectional analysis yields that, unlike PIN, PH is not sensitive to size and volume effects. We show that heuristic-driven traders are universally present in all market segments and their presence is constant over time. Furthermore, we find that heuristic-driven investors and informed traders are disjoint sets.

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confidence: 68%

“…First, Ortiz et al (2015) find no return anomalies in the first three quarters of their sample years;…”

Section: Please Insert Table 3 About Herementioning

confidence: 93%

Market microstructure during financial crisis: Dynamics of informed and heuristic-driven trading

Ormos

Timotity

2016

Finance Research Letters

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“…However, due caution should be exercised when interpreting statistical results. As there is substantial evidence that many developed markets are not informationally efficient (Ratner, 1996;Narayan, 2008;Borges, 2010;Pati and Rajib, 2011;Ortiz et al, 2015), the finding of no causality in either direction, especially in the case of nascent financial markets, like that of Qatar, is unlikely to serve as an empirical demonstration of informational efficiency.…”

Section: Dynamic Relationmentioning

confidence: 96%

The asymmetric price-volume relation revisited: evidence from Qatar

Ahmed

2018

JABS

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Purpose This study aims to revisit the stock price–volume relations, providing new evidence from the emerging market of Qatar. In particular, three main issues are examined using both aggregate market- and sector-level data. First, the return–volume relation and whether or not this relation is asymmetric. Second, the common characteristics of return volatility; and third, the nature of the relation between trading volume and return volatility. Design/methodology/approach The study uses the OLS and VAR modeling approaches to examine the contemporaneous and dynamic (causal) relations between index returns and trading volume, respectively, while an EGARCH-X(1,1) model is used to analyze the volatility–volume relation. The data set comprises daily index observations and the corresponding trading volumes for the entire market and the individual seven sectors of the Qatar Exchange (i.e. banks and financial services, consumer goods and services, industrials, insurance, real estate, telecommunications and transportation). Findings The empirical analysis reports evidence of a positive contemporaneous return–volume relation in all sectors barring transportation and insurance. This relation appears to be asymmetric for all sectors. For the market and almost all sectors, there is no significant causality between returns and volume. By and large, these findings lend support for the implications of the mixture of distributions hypothesis (MDH). Lastly, the information content of lagged volume seems to have an important role in predicting the future dynamics of return volatility in all sectors, with the industrials being the exception. Practical implications The findings provide important implications for portfolio managers and investors, given that the volume of transactions is generally found to be informative about the price movement of sector indices. Specifically, tracking the behavior of trading volume over time can give a broad portrayal of the future direction of market prices and volatility of equity, thereby enriching the information set available to investors for decision-making. Originality/value Based on both market- and sector-level data from the emerging stock market of Qatar, this study attempts to fill an important void in the literature by examining the return–volume and volatility–volume linkages.

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“…In the case of the Spanish market, some of these patterns have also been detected, different effects and patterns on profitability and volatility being studied (García‐Machado & Rybczyński, 2017; Ortiz et al, 2015).…”

Section: Literature Reviewmentioning

confidence: 99%

“…In the case of the Spanish market, some of these patterns have also been detected, different effects and patterns on profitability and volatility being studied (García-Machado & Rybczy nski, 2017;Ortiz et al, 2015). Camino (1996) investigated the intraday effect by dividing the IBEX-35 index into 15-min periods and found that yields were statistically different in the first 4 h after the opening of transactions.…”

Section: Literature Reviewmentioning

confidence: 99%

Early prediction of Ibex 35 movements

Miranda‐García

Vargas

Mori

et al. 2022

Journal of Forecasting

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In this paper, we examine the early predictability of the market's directional movement using intraday high‐frequency data (695,764 observations) from an stock index (Ibex 35 Index) to provide, either private or institutional investors, an early warning system based on an “early indicator” of the financial market fluctuations with an optimal combination of the two more relevant variables for this strategy, accuracy, and earliness. A novel supervised machine learning early classification technique (Artificial Intelligence) has been applied, for the first time, to the high‐frequency time series of both price and certain technical indicators. The results obtained allow us to assert that the intraday movement of the Ibex 35 can be predicted with acceptable levels of accuracy 24 min after the start of the session and to establish certain informative intraday hourly patterns. Consequently, different indicators of precision and earliness in the session are generated, obtaining that, after a certain point in the session, no gains in precision are generated.

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New evidence of quarterly return patterns in the Spanish stock market

Cited by 3 publications

References 11 publications

Market microstructure during financial crisis: Dynamics of informed and heuristic-driven trading

Market microstructure during financial crisis: Dynamics of informed and heuristic-driven trading

The asymmetric price-volume relation revisited: evidence from Qatar

Early prediction of Ibex 35 movements

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