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

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

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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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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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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Árendáš, Peter, Božena Chovancová, Jana Kotlebova, and Martin Koren. "January anomalies on CEE stock markets." Investment Management and Financial Innovations 18, no. 4 (2021): 120–30. http://dx.doi.org/10.21511/imfi.18(4).2021.11.

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Numerous studies show that stock markets are often impacted by various calendar anomalies that disrupt the “random walk” behavior of stock prices. These anomalies contradict the Efficient markets theory and can be exploited to generate abnormal returns. This paper investigates the presence of two of them, namely the January effect and the January barometer, on the stock markets of 12 Central and Eastern European (CEE) countries. The paper examines the statistical significance of differences in returns recorded over the month of January and returns recorded over the other months (the January ef

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Iqbal, Dr. "Seasonal Analysis of Abnormal Returns after Quarterly Earnings Announcements." International Journal of Accounting and Financial Reporting 1, no. 1 (2014): 501. http://dx.doi.org/10.5296/ijafr.v4i2.6622.

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This study examines whether the Indian stock market is efficient in semi-strong form and seasonality exists. For this purpose, we take the first and fourth quarters’ results of companies for the years 2008 to 2011. We divide companies into good news and bad news portfolios on the basis of percentage changes in net profits and net sales. We use event study methodology. The results reveal that average abnormal returns occur randomly and cumulative average abnormal returns are significant for both portfolios. Fourth quarter results give better positive signals to the market than first quarter res

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Ackert, Lucy F., and George Athanassakos. "Gamesmanship and Seasonality in U.S. Stock Returns." Journal of Risk and Financial Management 14, no. 5 (2021): 206. http://dx.doi.org/10.3390/jrfm14050206.

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We re-examined the seasonal pattern in the excess returns of highly visible American firms. In contrast to the seasonality for risky, less visible firms, we found that highly visible stocks display return seasonality that shows the opposite trend. Fund managers are prone to gamesmanship, putting downward pressure on prices for highly visible firms at the beginning of the year, which is reversed later with buying pressure. Due to the bonus culture, fund managers start the year by buying small, risky stocks in order to beat benchmarks. Once targets are met, they adjust toward visible, less risky

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Al-Awadhi, Abdullah, Ahmad Bash, and Fouad Jamaani. "Ramadan Effect: A Structural Time-Series Test." International Journal of Financial Research 12, no. 1 (2021): 260. http://dx.doi.org/10.5430/ijfr.v12n1p260.

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This study investigates whether religious belief creates stock market return seasonality, focusing on the Muslim holy month “Ramadan". We use long-term data from 12 stock markets in countries with a high Muslim majority. Using a structural time-series model that takes into account a “trend component" and a stochastic “seasonal component”, we find no significant evidence of Ramadan return seasonality for the 12 stock markets over the long-term. This result suggests that there is no trend component for Ramadan effect and that Ramadan returns seasonality vanish in the long-term.

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Lieksnis, Raimonds. "MULTIFACTOR ASSET PRICING ANALYSIS OF THE BALTIC STOCK MARKET." Ekonomika 89, no. 4 (2010): 85–95. http://dx.doi.org/10.15388/ekon.2010.0.964.

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This study investigates whether the Fama–French three-factor asset pricing model is applicable for explaining cross-sectional returns of stocks listed in the Baltic stock exchanges. Findings confirm the validity and economic significance of the three-factor model for the Baltic stock market: only investors who chose to invest in value stocks during the reference period achieved positive returns by matching or beating the returns of the stock market index. The monthly returns of 8 Latvian, 13 Estonian and 27 Lithuanian company stocks are analyzed for the time period from June 2002 till February

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Naz, Farah, Tooba Lutfullah, and Kanwal Zahra. "COVID-19 and Seasonality in Monthly Returns: a Firm Level Analysis of PSX." Zagreb International Review of Economics and Business 27, no. 1 (2024): 201–30. http://dx.doi.org/10.2478/zireb-2024-0010.

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Abstract The current study scrutinizes the calendar anomalies in the context of the local market by analyzing the Pakistan Stock Exchange (PSX). For this purpose, closing prices of KSE-100, KSE-30 and KSE-All share Index from January, 2009 to June, 2021 have been used as well as a thorough individual firm level analysis is done, taking average log-returns of selected sample firms returns using OLS regression, general GARCH (1,1), asymmetric TGARCH and PGARCH models. The results indicate monthly seasonality, with significant April, July, and September effect in PSX indices returns. The findings

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Tabash, Mosab I., Ayishana M. V., Abdussalam P.K., and Mujeeb Saif Mohsen Al-Absy. "Calendar Anomalies in Financial Markets: A Bibliometric Analysis." International Journal of Economics and Financial Issues 15, no. 3 (2025): 371–82. https://doi.org/10.32479/ijefi.17669.

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Calendar anomalies are predictable pattern in stock returns, questioning the Efficient Market Hypothesis and enabling investors to enhance their trading strategies. There has been a proliferation of studies investigating these calendar-based effects across diverse financial markets in recent years. This paper aims to provide a comprehensive bibliometric analysis of the existing literature on calendar anomalies in financial markets to uncover insights on the relevant themes, influential authors, and emerging research fronts. The bibliometric analysis is grounded in 432 articles from the Scopus

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Heston, Steven L., and Ronnie Sadka. "Seasonality in the Cross Section of Stock Returns: The International Evidence." Journal of Financial and Quantitative Analysis 45, no. 5 (2010): 1133–60. http://dx.doi.org/10.1017/s0022109010000451.

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AbstractThis paper studies seasonal predictability in the cross section of international stock returns. Stocks that outperform the domestic market in a particular month continue to outperform the domestic market in that same calendar month for up to 5 years. The pattern appears in Canada, Japan, and 12 European countries. Global trading strategies based on seasonal predictability outperform similar nonseasonal strategies by over 1% per month. Abnormal seasonal returns remain after controlling for size, beta, and value, using global or local risk factors. In addition, the strategies are not hig

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Norvaišienė, Rasa, and Jurgita Stankevičienė. "The Month Effect in the Baltic and Nordic Stock Markets at Market-Level and Sector-Level." Engineering Economics 33, no. 5 (2022): 473–85. http://dx.doi.org/10.5755/j01.ee.33.5.28183.

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The purpose of this study is to analyze and compare the trends in the expression of the month effect in the Nasdaq Baltic and Nasdaq Nordic stock markets, as well as to examine whether the seasonal stock price fluctuations occur in all industrial sectors of these markets or are specific to certain sectors only. The OMX Baltic Benchmark, OMX Baltic, and OMX Nordic 40 indexes, which reflect the situation in the Baltic and Nordic stock markets, were used in the study to assess seasonality at the market level. To assess the seasonality in separate sectors of the Baltic and Nordic markets, we used

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Lobão, Júlio. "Seasonal anomalies in the market for American depository receipts." Journal of Economics, Finance and Administrative Science 24, no. 48 (2019): 241–65. http://dx.doi.org/10.1108/jefas-09-2018-0088.

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Purpose The literature provides extensive evidence for seasonality in stock market returns, but is almost non-existent concerning the potential seasonality in American depository receipts (ADRs). To fill this gap, this paper aims to examine a number of seasonal effects in the market for ADRs. Design/methodology/approach The paper examines four ADRs for the period from April 1999 to March 2017 to look for signs of eight important seasonal anomalies. The authors follow the standard methodology of using dummy variables for the time period of interest to capture excess returns. For comparison, the

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Harshita, Shveta Singh, and Surendra S. Yadav. "Unique Calendar Effects in the Indian Stock Market: Evidence and Explanations." Journal of Emerging Market Finance 18, no. 1_suppl (2019): S35—S58. http://dx.doi.org/10.1177/0972652719831549.

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Covering 20 years (1995–2015), the article ascertains the presence of the month-of-the-year effect in the Indian stock market, for the raw returns series as well as after adjusting for non-linearities of the market. Whether the effect is the same for portfolios of different sizes and values is also ascertained. The threshold generalised autoregressive conditionally heteroskedastic (TGARCH) model is employed to address non-linearity. The results suggest the presence of higher returns in November/December at the index level. Further, only firms with a size smaller than the average exhibit season

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Fraz, Tayyab Raza. "Forecasting the Stock Market Returns Using nonlinear hybrid GARCH-SETAR model." JISR management and social sciences & economics 22, no. 1 (2024): 31–50. http://dx.doi.org/10.31384/jisrmsse/2024.22.1.2.

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Forecasting stock market returns is a valuable tool for investors seeking to enhance their gains in stock trading. Predicting stock prices proves to be a formidable endeavor due to its substantial volatility, non-linear characteristics trends, and responsiveness to multifaceted variables, including economic conditions, market trends, seasonality, and sentiment. Despite these complexities, non-linear methodologies like threshold time series and conditional heteroscedasticity models are underutilized. This study aims to assess the predictive capabilities of a hybrid GARCH-SETAR model in the cont

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Jurkšas, Linas, and Arvydas Paškevičius. "The Relationship Between Macroeconomy and Asset Prices: Long Run Causality Evidence From Lithuania." Organizations and Markets in Emerging Economies 8, no. 1 (2017): 63–85. http://dx.doi.org/10.15388/omee.2017.8.1.14198.

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The purpose of this paper is to determine the long-run causal impact of various economic factors on Lithuanian stock, government securities and real estate prices, and to assess how accurately future asset returns can be forecasted based solely on economic information. Five macroeconomic indicators, namely, gross domestic product (GDP), foreign direct investment (FDI), consumer price index (CPI), money supply (MS) and Vilnius interbank offered rate (VILIBOR), were included in the model. The results of the created autoregressive distributed lag model (ARDL) revealed that a long-run causal relat

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Plastun, Alex, Inna Makarenko, Lyudmila Khomutenko, Yanina Belinska, and Maryna Domashenko. "Exploring frequency of price overreactions in the Ukrainian stock market." Investment Management and Financial Innovations 15, no. 3 (2018): 157–68. http://dx.doi.org/10.21511/imfi.15(3).2018.13.

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This paper explores the frequency of price overreactions in the Ukrainian stock market by focusing on the PFTS Index over the period 2006–2017 and UX index over the period 2008–2017, as well as some “blue chips” (BAVL, UNAF, MSICH, CEEN) for the period of 2013–2015. Using static approach to detect overreactions, a number of hypotheses are tested: the frequency of price overreactions is informative about crisis events in the economy (H1), can be used for price prediction purposes (H2), and exhibits seasonality (H3). To do this, various statistical tests (both parametric and non-parametric), inc

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Dr., G. LalithaKumari, and V. Uthra. "An Analysis of turn of the month effect on SandP BSE Healthcare Index in the Indian Stock Market." International Journal of Trend in Scientific Research and Development 2, no. 2 (2018): 138–45. https://doi.org/10.31142/ijtsrd8340.

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The presence of the seasonal or monthly effect in stock returns has been reported in several developed and emerging stock markets. The Efficient Market Hypothesis EMH suggests that asset prices reflect on all obtainable information Fama,1970 . However, many studies have accepted not only that stock prices are predictable based on the preceding information, but also that indicators such as dividend yields, and gross domestic product contain information that is useful in predicting stock prices. This evidence is commonly called calendar anomalies. Calendar anomalies refer to the tendency of stoc

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Pham, Hai Yen, Richard Chung, Eduardo Roca, and Ben-Hsien Bao. "Do investors value firm efficiency improvement? Evidence from the Australian context." Corporate Ownership and Control 13, no. 3 (2016): 293–308. http://dx.doi.org/10.22495/cocv13i3c2p4.

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Do investors value improvement in efficiency? This paper investigates the relation between the firm’s technical efficiency change and subsequent stock returns. We employ a stochastic frontier analysis to evaluate a firm’s efficiency for a large panel of non-financial companies in Australia from January 1990 to October 2012. The results show that over the sample period, the estimated mean improvement in firm’s efficiency is 3% per year. We find that an equally-weighted (value-weighted) portfolio of stocks with the top tertile level change in efficiency outperforms an equally-weighted (value-wei

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Sehgal, Sanjay, and Vanita Tripathi. "Size Effect in Indian Stock Market: Some Empirical Evidence." Vision: The Journal of Business Perspective 9, no. 4 (2005): 27–42. http://dx.doi.org/10.1177/097226290500900403.

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In this study we attempt to test if there is a size effect in Indian stock market. The data relates to the top 482 Indian companies for the period 1990–2003. We find a strong size premium using six alternative measures of company size, viz., Market Capitalization, Enterprise Value, Net Fixed Assets, Net Annual Sales, Total Assets and Net Working Capital. Further the size based investment strategy seems to be economically feasible as it provides extra normal returns on risk adjusted basis. Frequent rebalancing of size based portfoilo is however found to be undesirable. The size effect does not

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Kaur, Harvinder. "Time Varying Volatility in the Indian Stock Market." Vikalpa: The Journal for Decision Makers 29, no. 4 (2004): 25–42. http://dx.doi.org/10.1177/0256090920040403.

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This paper investigates the nature and characteristics of stock market volatility in India. The volatility in the Indian stock market exhibits characteristics similar to those found earlier in many of the major developed and emerging stock markets. Various volatility estimators and diagnostic tests indicate volatility clustering, i.e., shocks to the volatility process persist and the response to news arrival is asymmetrical, meaning that the impact of good and bad news is not the same. Suitable volatility forecast models are used for Sensex and Nifty returns to show that: The ‘day-of-the-week

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Shaikh, Imlak, and Puja Padhi. "On the relationship between implied volatility index and equity index returns." Journal of Economic Studies 43, no. 1 (2016): 27–47. http://dx.doi.org/10.1108/jes-12-2013-0198.

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Purpose – The purpose of this paper is to analyze the asymmetric contemporaneous relationship between implied volatility index (India VIX) and Equity Index (S & P CNX Nifty Index). In addition, the study also analyzes the seasonality of implied volatility index in the form of day-of-the-week effects and option expiration cycle. Design/methodology/approach – This study employs simple OLS estimation to analyze the contemporaneous relationship among the volatility index and stock index. In order to obtain robust results, the analysis has been presented for the calendar years and sub-periods.

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Ahmad Al-smadi, Ayman Abdalmajeed, Mahmoud Khalid Almsafir, and Nur Hanis Hazwani Binti Husni. "Trends and Calendar effects in Malaysia’s Stock Market." Accounting and Finance Research 6, no. 1 (2017): 18. http://dx.doi.org/10.5430/afr.v6n1p18.

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Investing can help a person's wealth to generate more, and investing in stock is proven as one of the most profitable forms of available investment. The benefits gained in stock broking are immediate Buy/Sell which investor can sell part of their investment any time and at low transaction cost. However, investing in stock will require investor to observe the market, as market can be a volatile place and investor need to acquire knowledge of what they actually are doing. This study will discuss the price trends over the year, and how it will get affected by the seasonality in Malaysia, which al

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Enow, Samuel Tabot. "Revisiting the January effect anomaly: evidence from international stock markets." International Journal of Research in Business and Social Science (2147- 4478) 13, no. 4 (2024): 245–51. http://dx.doi.org/10.20525/ijrbs.v13i4.3273.

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A recurring theme in the literature and discussion of stock market analysis is the concept of the January effect which essentially implies buy in December and sell in January. The January effect is based on the perceived seasonality trend where short term investors hope to take advantage of the arbitrage opportunity between December and January. However, this perceived anomaly continues is seen as a myth and has been strongly rejected by many market participants in the current dispensation. The purpose of this paper was to investigate the January effect in the Nikkei 225, JSE, CAC 40, DAX, and

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Nayak, Pratham, and Shravya Suresh. "Forecast and Analysis of Stock Market Volatility Using Deep Learning Algorithms." ECS Transactions 107, no. 1 (2022): 6027–35. http://dx.doi.org/10.1149/10701.6027ecst.

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Stock markets serve as a platform where individuals and institutional investors can come together to buy and sell shares in a public venue and ultimately impact the economy. With the advent of digital technology these markets or exchanges exist as electronic marketplaces. These markets are very volatile thus making the stock market prediction a highly challenging problem. These predictions of stock value offer great profits which serve as a huge motivation for extensive research in this area. Identifying and predicting a stock value beforehand by even a fraction of a second can result in very

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Debasish, Sathya Swaroop. "STOCK PRICE SEASONALITY EFFECT AND TRADING STRATEGY – AN EMPIRICAL STUDY OF SELECTED IT COMPANIES IN INDIA." Business, Management and Education 10, no. 2 (2012): 264–88. http://dx.doi.org/10.3846/bme.2012.19.

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The primary objective of the study is to investigate the existence of seasonality in stock price behavior in Indian stock market and more specifically in the IT sector. The period of the study is from 3rd November 1994 to 31st December 2010. The study has employed daily price series of selected seven IT companies obtained from the official website of National Stock Exchange (NSE). The study used multiple regression technique to examine the significance of the regression coefficient for investigating day of week effects and week of the month effect, and Kruskal Wallis for analysis of trading st

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Karmakar, Madhusudan, and Madhumita Chakraborty. "A Trading Strategy for the Indian Stock Market: Analysis and Implications." Vikalpa: The Journal for Decision Makers 25, no. 4 (2000): 27–38. http://dx.doi.org/10.1177/0256090920000404.

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A curious seasonality reported in finance is the monthly effect which implies that the mean daily return for stock is positive and higher during the first half of the month than the second half. Another related anomaly is the turn-of-the-month effect which is said to exist when the average daily return at the turn of the month is significantly higher than the daily return on the remain ing days of the month. This paper examines both the monthly effect and the turn-of-themonth effect in the Indian stock market by applying two different approaches: calendar day approach and trading day approach.

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Shreyas, R. Katwey. "Modelling Stock Market Volatility and Its Impact on Investment Strategies: A GARCH and ARIMA Approach." Journal of Research and Review in Sales and Marketing 2, no. 1 (2024): 9–18. https://doi.org/10.5281/zenodo.13986934.

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<em>The present work aims to examine the accuracy of stock price and volatility in the context of the Nifty 50 index in India by using ARIMA and GARCH models. The linear model ARIMA designed for analysing linear trends and seasonality in the time series data was suitable for determining the price changes but excluded the phenomenon of volatility clustering typical for financial markets. We thus employed the GARCH model which was capable of capturing time varying volatility and provided good forecasts of high and low volatility periods. Its implementation of the two models affords a comprehensi

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Georgiou, Catherine. "The British Stock Market under the Structure of Market Capitalization Value: New Evidence on its Predictive Content." International Journal of Business and Economic Sciences Applied Research 13, no. 3 (2020): 57–70. http://dx.doi.org/10.25103/ijbesar.133.05.

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Purpose: The aim of our paper is twofold. First, we examine the predictive ability of log book-market, dividend-price, earnings-price and dividend-earnings ratios on the most recent data set of the strongest securities in the UK economy; unlike the majority of the studies in this data set, our analysis is not limited on returns but further investigates dividend and earnings growth predictability under the presence of the most recent global financial recession. Second, we exploit the long-run equilibrium relationship in two systems, [p_t,d_t,e_t] and [p_t,b_t,e_t] and examine the predictive abi

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Chen, Chieh-Shuo, Jia-Chi Cheng, Fang-Chi Lin, and Chihwei Peng. "The role of house money effect and availability heuristic in investor behavior." Management Decision 55, no. 8 (2017): 1598–612. http://dx.doi.org/10.1108/md-10-2016-0725.

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Purpose The house money effect is proposed to describe that people appear to consider large or unexpected wealth gains to be distinct from the rest of their wealth, and are thus more willing to gamble with such gains than they ordinarily would be. On the other hand, the availability heuristic describes that people tend to have a cognitive and systematic bias due to their reliance on easily available or associational information. The purpose of this paper is to employ these behavioral perspectives in an empirical model regarding the January anomaly to explore investor behavior in Taiwanese stoc

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Kapalczynski, Anna. "Seasonal effects on stock markets." Business and Management Review 13, no. 03 (2022). http://dx.doi.org/10.24052/bmr/v13nu03/art-10.

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We revisit factors associated with seasonality of stock markets. We find that interest rates and their seasonal components exhibit a strong relationship with returns and that association is more pronounced in countries, where interest rate seasonality is generally small. Additionally, using difference-in-difference estimation, we add to the growing evidence of increased synchronicity among countries belonging to the European Monetary Union. While we find strong evidence for stock market relationship with economic factors, our sample exhibits little indication that changing risk preferences thr

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Lavin, Angeline M. "An Empirical Investigation Of The Persistence Of Stock And Bond Return Seasonality." Journal of Applied Business Research (JABR) 16, no. 2 (2011). http://dx.doi.org/10.19030/jabr.v16i2.2037.

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<p class="MsoNormal" style="text-align: justify; margin: 0in 0.5in 0pt;"><span style="font-family: &quot;CG Times&quot;,&quot;serif&quot;;"><span style="font-size: x-small;">The purpose of this paper is to investigate the persistence of seasonality in stock and bond returns using data from 1926 to 1992. This study finds evidence of seasonality in stock returns during the 1926-92 period.<span style="mso-spacerun: yes;">&nbsp; </span>Dividing the data into sub-periods yields the following results: there was no evidence of stock market seasonality

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Farah Naz, Kanwal Zahra, and Tooba Lutfullah. "Testing Daily Seasonality Using Value Premium Portfolios Returns: The Case of Pakistan." Audit and Accounting Review 2, no. 1 (2023). http://dx.doi.org/10.32350/aar.21.05.

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Calendar anomalies are a well-documented phenomena in financial markets. The current study scrutinized calendar anomalies in the context of the local market by analyzing the Pakistan stock exchange. The data from the listed companies of PSX have been considered to test for seasonality in value premium portfolios using OLS regression, general GARCH (1,1), TGARCH, GJR-GARCH, PGARCH, and EGARCH models. The findings suggest that return seasonality among different value premium portfolios explains the economically and statistically significant magnitude of small firm effect. The current research al

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Kumar, Harish, and Mridul Dawar. "Seasonality in the Indian Stock Markets: A Study of Calendar Effects." MUDRA : Journal of Finance and Accounting 4, no. 01 (2017). http://dx.doi.org/10.17492/mudra.v4i01.9780.

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Theoretical and technological advances in Behavioural Finance over the last decades seem to have shifted the paradigm away from the Efficient Market Hypothesis proposed by Fama in 1970s. The hypothesis implied that securities are always priced efficiently since all the relevant information is fully reflected in their prices. However, this normative statement comes under heavy scrutiny with the existence of seasonality in stock returns. This paper investigates seasonality in the Indian stock markets through the existence of calendar effects. Employing time series analysis on data from January 1

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Maheshwari, Supriya, and Raj S. Dhankar. "Seasonality in Momentum Profits: Evidence from the Indian Stock Market." Journal of Commerce and Accounting Research 4, no. 3and4 (2015). http://dx.doi.org/10.21863/jcar/2015.4.3and4.012.

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The paper investigates Indian momentum profitability along with its performance stability round the year using the stock price data from National Stock Exchange (NSE). Results show evidence in favour of momentum profitability over the sample period from 1997 to 2013. Moreover, the momentum performance is not specific to any particular month suggesting no influence of calendar on momentum anomaly in the Indian stock market, though momentum strategies performed differently in different calendar months, with particularly strong negative returns in the month of May. However, no statistically signi

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Wuthisatian, Rattaphon. "An examination of calendar anomalies: evidence from the Thai stock market." Journal of Economic Studies ahead-of-print, ahead-of-print (2021). http://dx.doi.org/10.1108/jes-06-2020-0298.

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PurposeThe study examines the existence of calendar anomalies, including the day-of-the-week (DOW) effect and the January effect, in the Stock Exchange of Thailand.Design/methodology/approachUsing daily stock returns from March 2014 to March 2019, the study performs regression analysis to examine predictable patterns in stock returns, the DOW effect and the January effect, respectively.FindingsThere is strong evidence of a persistent monthly pattern and weekday seasonality in the Thai stock market. Specifically, Monday returns are negative and significantly lower than the returns on other trad

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Amihud, Yakov, and Joonki Noh. "Illiquidity and Stock Returns II: Cross-section and Time-series Effects." Review of Financial Studies, July 9, 2020. http://dx.doi.org/10.1093/rfs/hhaa080.

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Abstract Lou and Shu decompose Amihud’s illiquidity measure (ILLIQ) proposing that its component, the average of inverse dollar trading volume (IDVOL), is sufficient to explain the pricing of illiquidity. Their decomposition misses a component of ILLIQ that is related to illiquidity. We find that this component affects stock returns significantly, both in the cross-section and in time-series. We show that the ILLIQ premium is significantly positive after controlling for mispricing, sentiment, and seasonality. In addition, the aggregate market ILLIQ outperforms market IDVOL in estimating the ef

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Naz, Farah, Kanwal Zahra, Muhammad Ahmad, and Salman Riaz. "Day-of-the-week effect: A sectoral analysis of Pakistan stock exchange." International Journal of Financial Engineering, May 27, 2021, 2141006. http://dx.doi.org/10.1142/s2424786321410061.

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This study scrutinizes the day-of-the-week effect anomaly in the context of market and industry analysis of the Pakistan stock exchange. For this purpose, daily closing prices of KSE-100, KSE-30, and KSE-All Share Index from January 01, 2009 to December 31, 2018, have been used. Similarly, sector returns are also calculated, taking average log-returns of selected sample firms. To analyze the data ordinary least squares (OLS) regression, general generalized autoregressive conditional heteroscedasticity (GARCH) (1,1) as well as asymmetric threshold GARCH (TGARCH) and exponential GARCH (EGARCH) m

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Boubaker, Heni, Bassem Saidane, and Mouna Ben Saad Zorgati. "Modelling the dynamics of stock market in the gulf cooperation council countries: evidence on persistence to shocks." Financial Innovation 8, no. 1 (2022). http://dx.doi.org/10.1186/s40854-022-00348-3.

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AbstractThis study examines the statistical properties required to model the dynamics of both the returns and volatility series of the daily stock market returns in six Gulf Cooperation Council countries, namely Bahrain, Oman, Kuwait, Qatar, Saudi Arabia, and the United Arab Emirates, under different financial and economic circumstances. The empirical investigation is conducted using daily data from June 1, 2005 to July 1, 2019. The analysis is conducted using a set of double long-memory specifications with some significant features such as long-range dependencies, asymmetries in conditional v

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Hasan, Fakhrul, and Basil Al-Najjar. "Calendar anomalies and dividend announcements effects on the stock markets returns." Review of Quantitative Finance and Accounting, July 18, 2024. http://dx.doi.org/10.1007/s11156-024-01321-0.

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AbstractIn this study, we extend the existing literature around dividend signaling theory and calendar anomalies by addressing the question of whether calendar anomalies, including Halloween, Turn-of-the-Month (TOM), January, Monday, and Friday effects, have any influence on the relationship between stock returns and dividend announcements. Previous studies have primarily focused on demonstrating the impact of calendar anomalies on overall stock market returns. Our main aim is to investigate whether the Cumulative Abnormal Returns (CARs) associated with dividend announcements made by firms lis

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-, Dhiraj Naphade. "A Predictive Modeling Approach to Multi-Objective Marketing Mix Optimization: Balancing Performance, Acquisition, and Efficiency." International Journal on Science and Technology 16, no. 1 (2025). https://doi.org/10.71097/ijsat.v16.i1.2606.

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A predictive modeling article for multi-objective marketing mix optimization is presented to address the complex challenge of budget allocation across marketing channels. This article integrates machine learning, time-series analysis, and constrained optimization techniques to develop a comprehensive framework that simultaneously optimizes customer acquisition and cost efficiency. It accounts for critical factors, including seasonality, ad stock effects, cross-channel interactions, and diminishing returns, while accommodating practical budget constraints. The proposed framework utilizes non-li

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Khan, Mushtaq Hussain, Navid Feroze, Junaid Ahmed, and Mahzar Mughal. "Forecasting the extreme impact of Covid-19 on airline and petroleum stocks: a comparison of alternative time-series models." Journal of Modelling in Management, January 2, 2025. https://doi.org/10.1108/jm2-04-2023-0071.

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Purpose Earlier studies used conventional time-series models to forecast the impact of the Covid-19 pandemic on stock market performance. This study aims to provide a more flexible model that offers more robust estimation features, such as incorporating additional information (prior) about the model parameters, capturing the evolving behavior of the parameters over time and being able to include several covariates using a spike and slab prior, within the context of the Covid-19 shock and its effect on stock market performance. Design/methodology/approach Empirically, this paper compares autore

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