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Relevant bibliographies by topics / Seasonality in Lithuanian stock market returns

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Academic literature on the topic 'Seasonality in Lithuanian stock market returns'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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Journal articles on the topic "Seasonality in Lithuanian stock market returns"

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Macijauskas, Lukas. "Seasonality Analysis of Lithuanian Stock Market." Business: Theory and Practice 11, no. (3) (2010): 279–85. https://doi.org/10.3846/btp.2010.30.

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The main purpose of this article is to test if there are any seasonal tendencies in Lithuanian stock market and if so, do they match seasonal anomalies found in other countries. To achieve this ambition, tests were done by dividing returns of OMXV index into three groups: month of the year, week of the month and day of the week. Analysis was made using 10 years of historical data which covers main stages of Lithuanian stock market cycle. Results show that seasonal anomalies do exist in Lithuanian stock market and that their characteristics are similar to those found by researches in other stoc

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Sarma, S. N. "Stock Market Seasonality in an Emerging Market." Vikalpa: The Journal for Decision Makers 29, no. 3 (2004): 35–42. http://dx.doi.org/10.1177/0256090920040303.

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The objective of this paper is to explore the day-of-the-week effect on the Indian stock market returns in the post-reform era. Till the late seventies, empirical studies provided ample evidence as to the informational efficiency of the capital markets advocating futility of information in consistently generating abnormal returns. However, later studies identified certain anomalies in the efficient market postulate. One major anomaly brought forth was the calendar-related abnormal rates of return. Various studies in this domain empirically demonstrated, through parametric and non-parametric te

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Vu, Ha, and Sean Turnell. "Seasonality in the Australian Stock Market." Applied Economics and Finance 6, no. 5 (2019): 158. http://dx.doi.org/10.11114/aef.v6i5.4445.

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This paper examines the presence of day-of-the-week and month-of-the-year effects in the Australian stock market over the past several decades, and investigates whether long-standing anomalies persist following the 1987 stock market crash, and the 2008 global financial crisis. We find that before the 1987 crash the Australian stock market recorded lowest returns on Tuesday and highest returns on Thursdays. However, these daily phenomena seemed to vanish in the decades since, suggesting that Australian daily share prices are more likely to move randomly. In contrast, monthly seasonality is stil

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Bansal, Ved Prakash. "The Effect of Seasonality over Stock Exchanges in India." Journal of Business Management and Information Systems 4, no. 1 (2017): 65–72. http://dx.doi.org/10.48001/jbmis.2017.0401008.

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This study investigated to examine stock market seasonality effect in Indian stock market for Bombay Stock Exchange (BSE) 100. The monthly return data of BSE 100 for the period from April, 2001 to March, 2016 was used for analysis. After examining the stationarity of the return series and correlogram, regression equation & ARIMA model is used to find the monthly effect in stock returns in India. The results confirmed the existence of seasonality in stock returns in India.

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Umoru, David, Timothy Igbafe Aliu, and Beauty Igbinovia. "Seasonality Effects, Stock Exchange and Foreign Exchange Markets: Comparative Analysis of Volatility Behavior During Covid-19." Asian Journal of Economics, Business and Accounting 24, no. 9 (2024): 367–91. http://dx.doi.org/10.9734/ajeba/2024/v24i91498.

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This study investigated the effects of seasonality on stock exchange and foreign exchange markets of two WAMZ and two BRICS countries which include Nigeria, Ghana, and Brazil and China. The Auto Regressive Integrated Moving Average (ARIMA) regression approach and the Markov-regime switching methodologies were executed. The parsimonious ARIMA estimates reported Nigeria’s stock returns demonstrated lower volatility (SIGMASQ = 0.000141) than Ghana’s stock returns (SIGMASQ = 0.004003). Similarly, Nigeria had a lower returns volatility than Ghana (SIGMASQ = 0.001829 < 0.07727) in the foreign exc

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Husain, Fazal. "A Seasonality in the Pakistani Equity Market: The Ramadhan Effect." Pakistan Development Review 37, no. 1 (1998): 77–81. http://dx.doi.org/10.30541/v37i1pp.77-81.

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This paper attempts to explore a seasonal pattern, the Ramadhan effect, in the Pakistani equity market. Ramadhan, the holy month of fasting, is expected to affect the behaviour of stock market in Pakistan where the environment in Ramadhan is different from other months as people devote more time to perform religious rituals and the general economic activity slows down. The effects of Ramadhan on mean return and stock returns volatility are examined by including a dummy variable in regressions and GARCH models respectively. The analysis indicates a significant decline in stock returns volatilit

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Al-Saad *, Khalid, and Imad A. Moosa. "Seasonality in stock returns: evidence from an emerging market." Applied Financial Economics 15, no. 1 (2005): 63–71. http://dx.doi.org/10.1080/0960310042000281185.

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8

Ahmed, Ahmed, and Sohair Ahmed. "Monthly Patterns in Egyptian Stock Market." GIS Business 12, no. 3 (2017): 17–24. http://dx.doi.org/10.26643/gis.v12i3.3355.

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In this paper, monthly effect in Egyptian stock market is investigated for the period January 2007 to July 2015. After examining the random walk hypothesis of the return series, a Seasonal Autoregressive Moving Average (SARMA) model is specified to test the monthly effect in Egyptian Stock market. The results of the study imply that the banking sector of stock market is informationally efficient and does not confirm to the existence of seasonality in stock returns.

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9

Teresienė, Deimantė. "LITHUANIAN STOCK MARKET ANALYSIS USING A SET OF GARCH MODELS." Journal of Business Economics and Management 10, no. 4 (2009): 349–60. http://dx.doi.org/10.3846/1611-1699.2009.10.349-360.

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This article analyses the main factors that influence stock price volatility. The author offers a three‐stage system for explaning a set of stock price volatility factors. The main point is to pay attention to investor's psychology as the main factor of price volatility. For practical analysis the returns of the OMXV index and stock prices of the Lithuanian stock market are taken and applied to a set of GARCH models. The main idea is to choose the best of the general autoregressive conditional heteroskedasticity models (GARCH) for OMXV index and all sectors. All models are ranged according to

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Harshita, Harshita, Shveta Singh, and Surendra S. Yadav. "Calendar anomaly: unique evidence from the Indian stock market." Journal of Advances in Management Research 15, no. 1 (2018): 87–108. http://dx.doi.org/10.1108/jamr-11-2016-0096.

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Purpose The purpose of this paper is to ascertain the monthly seasonality in the Indian stock market after taking into consideration the market features of leptokurtosis, volatility clustering and the leverage effect. Design/methodology/approach Augmented Dickey-Fuller, Phillips-Perron and Kwaitkowski-Phillips-Schmidt-Shin tests are deployed to check stationarity of the series. Autocorrelation function, partial autocorrelation function and Ljung-Box statistics are employed to check the applicability of volatility models. An exponential generalized auto regressive conditionally heteroskedastic

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Dissertations / Theses on the topic "Seasonality in Lithuanian stock market returns"

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Tang, Gordon Yu Nam. "Diversification, intervalling effect and seasonality : an empirical study of the Hong Kong stock market." Thesis, University of Strathclyde, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.320111.

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Book chapters on the topic "Seasonality in Lithuanian stock market returns"

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Ilt√ºzer Samur, Zeynep, Cumhur Ekinci, and Oktay Tas. "Seasonality and the Relation between Volatility and Returns." In Stock Market Volatility. Chapman and Hall/CRC, 2009. http://dx.doi.org/10.1201/9781420099553.ch26.

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"■ Seasonality and the Relation between Volatility and Returns: Evidence from Turkish Financial Markets." In Stock Market Volatility. Chapman and Hall/CRC, 2009. http://dx.doi.org/10.1201/9781420099553-34.

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