Calendar Effect

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Abdellatif El Afia - One of the best experts on this subject based on the ideXlab platform.

  • Forecasting Demand With Support Vector Regression Technique Incorporating Feature Selection in the Presence of Calendar Effect
    Contemporary Approaches and Strategies for Applied Logistics, 2020
    Co-Authors: Malek Sarhani, Abdellatif El Afia
    Abstract:

    Reliable prediction of future demand is needed to better manage and optimize supply chains. However, a difficulty of forecasting demand arises due to the fact that heterogeneous factors may affect it. Analyzing such data by using classical time series forecasting methods will fail to capture such dependency of factors. This chapter addresses these problems by examining the use of feature selection in forecasting using support vector regression while eliminating the Calendar Effect using X13-ARIMA-SEATS. The approach is investigated in three different case studies.

  • An extension of X13-ARIMA-SEATS to forecast islamic holidays Effect on logistic activities
    2014 International Conference on Logistics Operations Management, 2014
    Co-Authors: Malek Sarhani, Abdellatif El Afia
    Abstract:

    To better manage and optimize logistic activities, factors that affect it must be determined: The Calendar Effect is one of these factors which must be analyzed. Analyzing such kind of data by using classical time series forecasting methods, such as exponential smoothing method and ARIMA model, will fail to capture such variation. This paper is released to present a review of the models which are used to forecast the Calendar Effect, especially moving holidays Effect. We adopt the recent approach of X13-ARIMA-SEATS and extend it for being able to forecast the Effect of Islamic holidays. Our extension is applied to Moroccan case studies, and aims to give recommendations concerning this Effect on logistic activities.

  • GOL - An extension of X13-ARIMA-SEATS to forecast islamic holidays Effect on logistic activities
    2014 International Conference on Logistics Operations Management, 2014
    Co-Authors: Malek Sarhani, Abdellatif El Afia
    Abstract:

    To better manage and optimize logistic activities, factors that affect it must be determined: The Calendar Effect is one of these factors which must be analyzed. Analyzing such kind of data by using classical time series forecasting methods, such as exponential smoothing method and ARIMA model, will fail to capture such variation. This paper is released to present a review of the models which are used to forecast the Calendar Effect, especially moving holidays Effect. We adopt the recent approach of X13-ARIMA-SEATS and extend it for being able to forecast the Effect of Islamic holidays. Our extension is applied to Moroccan case studies, and aims to give recommendations concerning this Effect on logistic activities.

  • forecasting demand with support vector regression technique combined with x13 arima seats method in the presence of Calendar Effect
    International Journal of Applied Logistics, 2014
    Co-Authors: Malek Sarhani, Abdellatif El Afia
    Abstract:

    In order to better manage and optimize supply chain, a reliable prediction of future demand is needed. The difficulty of forecasting demand is due mainly to the fact that heterogeneous factors may affect it. Analyzing such kind of data by using classical time series forecasting methods, will fail to capture such dependency of factors. This paper is released to present a forecasting approach of two stages which combines the recent methods X13-ARIMA-SEATS and Support Vector Regression (SVR). The aim of the first one is to remove the Calendar Effect, while the purpose of the second one is to forecast the demand after the removal of this Effect. This approach is applied to three different case studies and compared to the forecasting method based on SVR alone.

Sarah L Shafer - One of the best experts on this subject based on the ideXlab platform.

  • paleo Calendar Effect adjustments in time slice and transient climate model simulations paleocaladjust v1 0 impact and strategies for data analysis
    Geoscientific Model Development, 2019
    Co-Authors: Patrick J Bartlein, Sarah L Shafer
    Abstract:

    Abstract. The “paleo Calendar Effect” is a common expression for the impact that changes in the length of months or seasons over time, related to changes in the eccentricity of Earth's orbit and precession, have on the analysis or summarization of climate-model output. This Effect can have significant implications for paleoclimate analyses. In particular, using a “fixed-length” definition of months (i.e., defined by a fixed number of days), as opposed to a “fixed-angular” definition (i.e., defined by a fixed number of degrees of the Earth's orbit), leads to comparisons of data from different positions along the Earth's orbit when comparing paleo with modern simulations. This Effect can impart characteristic spatial patterns or signals in comparisons of time-slice simulations that otherwise might be interpreted in terms of specific paleoclimatic mechanisms, and we provide examples for 6, 97, 116, and 127 ka. The Calendar Effect is exacerbated in transient climate simulations in which, in addition to spatial or map-pattern Effects, it can influence the apparent timing of extrema in individual time series and the characterization of phase relationships among series. We outline an approach for adjusting paleo simulations that have been summarized using a modern fixed-length definition of months and that can also be used for summarizing and comparing data archived as daily data. We describe the implementation of this approach in a set of Fortran 90 programs and modules (PaleoCalAdjust v1.0).

  • Paleo Calendar-Effect adjustments in time-slice and transient climate-model simulations (PaleoCalAdjust v1.0): impact and strategies for data analysis
    2018
    Co-Authors: Patrick J Bartlein, Sarah L Shafer
    Abstract:

    <p><strong>Abstract.</strong> The “paleo Calendar Effect” is a common expression for the impact that the changes in the length of months or seasons over time, related to changes in the eccentricity of Earth's orbit and precession, have on the analysis or summarization of climate-model output. This Effect can have significant implications for paleoclimate analyses. In particular, using a “fixed-length” definition of months (i.e. defined by a fixed number of days), as opposed to a “fixed-angular” definition (i.e. defined by a fixed number of degrees of the Earth's orbit), leads to comparisons of data from different positions along the Earth's orbit when comparing paleo with modern simulations. This Effect can impart characteristic spatial patterns or signals in comparisons of time-slice simulations that otherwise might be interpreted in terms of specific paleoclimatic mechanisms, and we provide examples for 6, 97, 116, and 127 ka. The Calendar Effect is exacerbated in transient climate simulations, where, in addition to spatial or map-pattern Effects, it can influence the apparent timing of extrema in individual time series and the characterization of phase relationships among series. We outline an approach for adjusting paleo simulations that have been summarized using a modern fixed-length definition of months and that can also be used for summarizing and comparing data archived as daily data. We describe the implementation of this approach in a set of Fortran 90 programs and modules (PaleoCalAdjust v1.0).</p>

Abhijeet Chandra - One of the best experts on this subject based on the ideXlab platform.

  • stock market anomalies a test of Calendar Effect in the bombay stock exchange bse
    Indian Journal of Finance, 2011
    Co-Authors: Abhijeet Chandra
    Abstract:

    Various seasonal patterns in returns have been found in the stock markets across the world. These patterns often referred to as anomalies, can be seasonal. This study examines whether Calendar anomalies exist in the stock returns in the Bombay Stock Exchange (BSE). It investigates two types of Calendar anomalies such as the turn-of-the-month Effect and the time-of-the-month Effect in returns in one of the leading stock exchanges of India. Data pertaining to the ten-year period of 1998-2007 has been used for testing the two types of Calendar anomalies. Results reveal that the turn-of-the-month Effect and the time-of-the-month Effect have significantly existed in BSE Sensex returns. Returns in the first few days of the month are found to be positively significant compared to the remaining days of the month. Different time segments of a month, however, witness significantly varying returns. The evidence of this study strongly supports the existence of Calendar Effects in the returns of the BSE-Sensex.

  • stock market anomalies a survey of Calendar Effect in bse sensex
    2009
    Co-Authors: Abhijeet Chandra
    Abstract:

    Calendar Effect connotes the changes in security prices in stock market following certain trends based on seasonal Effects. Such trends or consistent patterns occur at a regular interval or at a specific time in a Calendar year. Presence of such anomalies in any stock market is the biggest threat to the concept of market efficiency as these anomalies may enable stock market participants beat the market by observing these patterns. This notion again violates the basic assumption of efficient market hypothesis (EMH) that no one can beat the market and earn the profit in excess of market. Daily stock returns are also different from each other at different points of time during a month. This study tried to test this difference by dividing a month into segments and then analyzing the returns for these segments separately in order to find out that in which segment daily stock returns are highest.This study has been conducted to find out whether Turn of the Month Effect and Time of the Month Effect in BSE-SENSEX. Data pertaining to daily stock index of SENSEX, the capital weighted index of Bombay Stock Exchange (BSE) for the period April 1998 to March 2008 has been used in this study. This study has been conducted to test the market efficiency in Indian stock market by examining Calendar Effect present in Bombay Stock Exchange, the largest stock exchange in India. In order to test the evidence of Calendar anomalies, BSE’s leading index BSE 30 SENSEX has been selected as a sample for this study. Results from this study reveal that a very anomalous behaviour towards returns has been found in BSE 30. For both the Effects, the Turn of the Month Effect as well as the Time of the Month Effect, significant values were found. Both the Effects are found to be almost same. Returns during a month are analyzed by dividing that month into three parts separately. And it was found that early days of the month witness higher mean returns than later days of the same month. The reason behind this trend could be the cognitive belief of investors with regard to new and positive changes in policies and newer information in the coming month. This results in selling pressure by investors with the hope to get positive benefits, leading to low returns at the end of month. With the beginning of new month, investors start buying into stocks following the same cognitive belief and incorporating new information.Existence of these anomalies in Bombay Stock Exchange is against the principle of market efficiency as it may offer abnormal economic rewards to the investors tracking these anomalies. Those at helm should chalk out policies to check this anomalous behaviour of the stock market so that the market could become really efficient.

  • Stock Market Anomalies: A Calender Effect in BSE-Sensex
    2009
    Co-Authors: Abhijeet Chandra
    Abstract:

    Whether inexplicable patterns of abnormal stock market returns are detected in empirical studies of the stock market, a return anomaly is said to be found. There are other similar anomalies existing in the stock market. Economically meaningful stock market anomalies not only are statistically significant but also offer meaningful risk adjusted economic rewards to investors. Statistically significant stock market anomalies have yet-unknown economic and/or psychological explanations. A joint test problem exists because anomalies evidence that is inconsistent with a perfectly efficient market could be an indication of either market inefficiency or a simple failure of Capital Asset Pricing Model (CAPM) accuracy. Some of the most-discussed about market anomalies are return anomaly, market capitalization Effect, value Effect, Calendar Effect, and announcement Effect. Though various studies have been conducted to find out the presence of these anomalies across the stock markets worldwide, very few studies with reference to Indian stock market are available in the financial literature. This study aims to find the evidence of one of the anomalies, Calendar Effect in BSE Sensex, India’s leading stock exchange.

Bohdan Petrushchak - One of the best experts on this subject based on the ideXlab platform.

Dragan Tevdovski - One of the best experts on this subject based on the ideXlab platform.

  • Stock Market Efficiency in South Eastern Europe: Testing Return Predictability and Calendar Effects
    Regaining Global Stability After the Financial Crisis, 2020
    Co-Authors: Vladimir Filipovski, Dragan Tevdovski
    Abstract:

    The purpose of this chapter is to empirically test the informational efficiency and to examine the presence of the Calendar Effects in 10 South Eastern European (SEE) stock markets' daily returns during the period 2007–2014. The authors use variance ratio test for exploration of random walk hypothesis. Regarding the Calendar Effects, the authors focus on the day-of-the-week Effect, the half-month Effect, and the turn-of-the-month Effect. The existence of each Calendar Effect is analyzed by applying regression models with dummy variables for the Effects in the mean returns and GARCH (1,1) models with dummy variables for the Effects in the volatility of returns. The results indicate that the day-of-the-week Effects in both mean and volatility are present in nine SEE stock markets. Contrary, the half-month Effect in mean returns is present only in one, while half-month Effect in volatility is present in five SEE stock markets. The turn-of-the- month Effect in mean returns is present in six, while the turn-of-the-month Effect in volatility is present in all 10 SEE stock markets.

  • Stock market efficiency in South Eastern Europe: testing return predictability and presence of Calendar Effects
    2017
    Co-Authors: Vladimir Filipovski, Dragan Tevdovski
    Abstract:

    This paper examines the Calendar Effects in ten South Eastern European (SEE) stock markets daily returns during the period 2007 - 2014. We focus on three Calendar Effects: the day of the week Effect, the half month Effect and the turn of the month Effect. Specifically, we analyze existence of each Calendar Effect separately in the mean and in the volatility of the index returns. We apply standard regression models with dummy variables for the Effects in the mean returns, while we apply GARCH(1,1) models with dummy variables for the Effects in the volatility of returns. The results present evidence that the day of the week Effects in both mean and volatility are present in nine out of ten SEE stock markets. Contrary, the half month Effect in mean returns is present only in one SEE stock market, while half month Effect in volatility is present in five out of ten SEE stock markets. The turn of the month Effect in mean returns is present in six out of ten SEE stock markets. The turn of the month Effect in volatility is present in all SEE stock markets.

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