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Journal articles on the topic 'Seasonalities'

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Published: 4 June 2021
Last updated: 1 February 2022

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1

KELOHARJU, MATTI, JUHANI T. LINNAINMAA, and PETER NYBERG. "Return Seasonalities." Journal of Finance 71, no. 4 (July 13, 2016): 1557–90. http://dx.doi.org/10.1111/jofi.12398.

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2

Chari, V. V., Ravi Jagannathan, and Aharon R. Ofer. "Seasonalities in security returns." Journal of Financial Economics 21, no. 1 (May 1988): 101–21. http://dx.doi.org/10.1016/0304-405x(88)90033-5.

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3

Peterson, David R. "Stock Return Seasonalities and Earnings Information." Journal of Financial and Quantitative Analysis 25, no. 2 (June 1990): 187. http://dx.doi.org/10.2307/2330823.

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4

GARCIA BLANDON, JOSE. "RETURN'S SEASONALITIES IN THE LATIBEX MARKET." Revista de análisis económico 25, no. 1 (June 2010): 3–14. http://dx.doi.org/10.4067/s0718-88702010000100001.

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5

Alford, Alan, and Daryl M. Guffey. "A re-examination of international seasonalities." Review of Financial Economics 5, no. 1 (December 1996): 1–17. http://dx.doi.org/10.1016/s1058-3300(96)90002-6.

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6

Ballocchi, Giuseppe, Michael Dacorogna, Ramazan Gençay, and Barbara Piccinato. "Time-to-Expiry Seasonalities in Eurofutures." Studies in Nonlinear Dynamics and Econometrics 4, no. 4 (December 1, 2000): 227–32. http://dx.doi.org/10.1162/108118200753392136.

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7

Harju, Kari, and Syed Mujahid Hussain. "Intraday Seasonalities and Macroeconomic News Announcements." European Financial Management 17, no. 2 (August 20, 2009): 367–90. http://dx.doi.org/10.1111/j.1468-036x.2009.00512.x.

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8

Hofmann, Daniel, and Karl Ludwig Keiber. "Seasonalities in the German stock market." Financial Markets and Portfolio Management 35, no. 2 (January 24, 2021): 151–92. http://dx.doi.org/10.1007/s11408-020-00373-1.

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AbstractThis paper suggests innovative investment strategies drawing on return seasonalities. By means of an out-of-sample study of the German stock market, we report that these long–short investment strategies earn on average raw returns up to 233 basis points per month throughout two decades from 1998 to 2017. On a monthly basis, this documents an outperformance of the corresponding Heston and Sadka (J Financ Econ 87(2):418–445, 2008) strategy by 66%. This outperformance is robust in magnitude even after adjusting for common risk factors along both the three-factor Fama and French (J Financ Econ 33(1):3–56, 1993) model and the four-factor Carhart (J Finance 52(1):57–82, 1997) model. Categorizing stocks into three risk profiles lets us conclude that long–short momentum portfolios of stocks with a low-risk profile generate robust investment performance.
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9

Gençay, Ramazan, Faruk Selçuk, and Brandon Whitcher. "Differentiating intraday seasonalities through wavelet multi-scaling." Physica A: Statistical Mechanics and its Applications 289, no. 3-4 (January 2001): 543–56. http://dx.doi.org/10.1016/s0378-4371(00)00463-5.

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10

Ho, Yan-Ki. "Stock Return Seasonalities in Asia Pacific Markets." Journal of International Financial Management & Accounting 2, no. 1 (March 1990): 47–77. http://dx.doi.org/10.1111/j.1467-646x.1990.tb00017.x.

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11

Hirshleifer, David, Danling Jiang, and Yuting Meng DiGiovanni. "Mood beta and seasonalities in stock returns." Journal of Financial Economics 137, no. 1 (July 2020): 272–95. http://dx.doi.org/10.1016/j.jfineco.2020.02.003.

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12

Powell, John G., Jing Shi, Tom Smith, and Robert E. Whaley. "Political regimes, business cycles, seasonalities, and returns." Journal of Banking & Finance 33, no. 6 (June 2009): 1112–28. http://dx.doi.org/10.1016/j.jbankfin.2008.12.009.

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13

Yamaguchi, Satoru, and Koji Fujita. "Modeling Glacier Behavior Under Different Precipitation Seasonalities." Arctic, Antarctic, and Alpine Research 45, no. 1 (February 2013): 143–52. http://dx.doi.org/10.1657/1938-4246-45.1.143.

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14

Ibrahim, Noor ‘Adilah. "MODELLING OF INTRADAY PHOTOVOLTAIC POWER PRODUCTION." Malaysian Journal of Science 40, no. 2 (June 30, 2021): 105–24. http://dx.doi.org/10.22452/mjs.vol40no2.8.

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Photovoltaic (PV) productions should occur within a time interval of sunlight. Time mismatches are detected between sunrise and first production hour as well as sunset and last production hour in a transmission system operator, Amprion, Germany. Hence, in this paper, we investigate this effect using an additive function of two seasonalities and a stochastic process. Both seasonalities are based on the mimicked locations, corrected by a weighing scale, depending on the first and last production hours' coordinates. The result shows that the proposed deterministic model could capture the effect of sunrise and sunset. Also, the dynamics of random components are sufficiently explained by an autoregressive process of order two. Finally, the Normal Inverse Gaussian distribution is shown as the best distribution in explaining noise behaviour, particularly heavy tails in the production's residuals, compared to the Gaussian distribution.
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15

Mitchell, Jason D., and Li L. Ong. "Seasonalities in China's Stock Markets: Cultural or Structural?" IMF Working Papers 06, no. 4 (2006): 1. http://dx.doi.org/10.5089/9781451862645.001.

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16

Santesmases, Migue. "An Investigation of the Spanish Stock Market Seasonalities." Journal of Business Finance & Accounting 13, no. 2 (June 1986): 267–76. http://dx.doi.org/10.1111/j.1468-5957.1986.tb00096.x.

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17

PeÑa, J. Ignacio. "Daily seasonalities and stock market reforms in Spain." Applied Financial Economics 5, no. 6 (December 1995): 419–23. http://dx.doi.org/10.1080/758538601.

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18

Wong, Kie Ann, and Kusnadi Yuanto. "Short-Term Seasonalities on the Jakarta Stock Exchange." Review of Pacific Basin Financial Markets and Policies 02, no. 03 (September 1999): 375–98. http://dx.doi.org/10.1142/s0219091599000205.

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This research attempts to uncover the presence of various stock market seasonalities on the Jakarta Stock Exchange (JSX). We find that most of the seasonal effects exist on the JSX, except for the January effect. There is a day-of-the-week effect with low Tuesday and high Friday returns. The "twist" effect is confirmed with a negative Tuesday return following a market decline in the previous week. The Tuesday "Rogalski" effect is present, with Tuesday return being positive in the month of January and negative for the other months. The monthly, turn-of-the-month, turn-of-the-year and pre-holiday effects are also confirmed in recent sub-periods after the reforms of the JSX in 1988.
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19

Ignatius, Roger. "The Bombay Stock Exchange: seasonalities and investment opportunities." Managerial Finance 24, no. 3 (March 1998): 52–61. http://dx.doi.org/10.1108/03074359810765426.

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20

Allez, Romain, and Jean-Philippe Bouchaud. "Individual and collective stock dynamics: intra-day seasonalities." New Journal of Physics 13, no. 2 (February 17, 2011): 025010. http://dx.doi.org/10.1088/1367-2630/13/2/025010.

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21

Zaremba, Adam. "Cross-sectional seasonalities in international government bond returns." Journal of Banking & Finance 98 (January 2019): 80–94. http://dx.doi.org/10.1016/j.jbankfin.2018.11.004.

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22

Mikutowski, Mateusz, Andreas Karathanasopoulos, and Adam Zaremba. "Return seasonalities in government bonds and macroeconomic risk." Economics Letters 176 (March 2019): 114–16. http://dx.doi.org/10.1016/j.econlet.2019.01.012.

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23

Keloharju, Matti, Juhani T. Linnainmaa, and Peter Nyberg. "Are return seasonalities due to risk or mispricing?" Journal of Financial Economics 139, no. 1 (January 2021): 138–61. http://dx.doi.org/10.1016/j.jfineco.2020.07.009.

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24

Wood, Bob G. "Seasonalities and the 1987 crash: The international evidence." International Review of Financial Analysis 3, no. 1 (January 1994): 65–91. http://dx.doi.org/10.1016/1057-5219(94)90016-7.

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25

Lauterbach, Beni, and Meyer Ungar. "Real vs. nominal stock return seasonalities: empirical evidence." International Review of Economics & Finance 4, no. 2 (January 1995): 133–47. http://dx.doi.org/10.1016/1059-0560(95)90014-4.

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26

Christopher, Ma, and Goebel Paul. "On the Seasonalities of Mortgage-Backed Security Prices." Journal of Real Estate Research 6, no. 1 (January 1, 1991): 19–38. http://dx.doi.org/10.1080/10835547.1991.12090637.

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27

Mitchell, Jason D., Li Lian Ong, and H. Y. Izan. "Idiosyncrasies in Australian petrol price behaviour: evidence of seasonalities." Energy Policy 28, no. 4 (April 2000): 243–58. http://dx.doi.org/10.1016/s0301-4215(00)00005-7.

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28

Dahlquist, Magnus, and Peter Sellin. "Stochastic dominance, tax-loss selling and seasonalities in Sweden." European Journal of Finance 2, no. 1 (March 1996): 1–19. http://dx.doi.org/10.1080/135184796337571.

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29

Whitehouse, Andrew. "Loudly sing cuckoo: More-than-human seasonalities in Britain." Sociological Review 65, no. 1_suppl (March 2017): 171–87. http://dx.doi.org/10.1177/0081176917693533.

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30

Felix Ayadi, O., Uric B. Dufrene, and Amitava Chatterjee. "Stock return seasonalities in low‐income African emerging markets." Managerial Finance 24, no. 3 (March 1998): 22–33. http://dx.doi.org/10.1108/03074359810765408.

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31

Ajdacic-Gross, Vladeta, Jen Wang, Matthias Bopp, Dominique Eich, Wulf Rössler, and Felix Gutzwiller. "Are seasonalities in suicide dependent on suicide methods? A reappraisal." Social Science & Medicine 57, no. 7 (October 2003): 1173–81. http://dx.doi.org/10.1016/s0277-9536(02)00493-8.

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32

Guevara Hidalgo, Esteban. "Bin size independence in intra-day seasonalities for relative prices." Physica A: Statistical Mechanics and its Applications 468 (February 2017): 722–32. http://dx.doi.org/10.1016/j.physa.2016.11.128.

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33

Milonas, Nikolaos T. "Measuring seasonalities in commodity markets and the half-month effect." Journal of Futures Markets 11, no. 3 (June 1991): 331–45. http://dx.doi.org/10.1002/fut.3990110307.

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34

Gaudry, Maria M. Cárdenas, Dieter Gutknecht, Juraj Parajka, Rui A. P. Perdigão, and Günter Blöschl. "Seasonality of runoff and precipitation regimes along transects in Peru and Austria." Journal of Hydrology and Hydromechanics 65, no. 4 (December 20, 2017): 347–58. http://dx.doi.org/10.1515/johh-2017-0018.

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AbstractThe aim of this study is to understand the seasonalities of runoff and precipitation and their controls along two transects in Peru and one transect in Austria. The analysis is based on daily precipitation data at 111 and 61 stations in Peru and Austria, respectively, and daily discharge data at 51 and 110 stations. The maximum Pardé coefficient is used to quantify the strength of the seasonalities of monthly precipitation and runoff. Circular statistics are used to quantify the seasonalities of annual maximum daily precipitation and annual maximum daily runoff. The results suggest that much larger spatial variation in seasonality in Peru is because of the large diversity in climate and topography. In the dry Peruvian lowlands of the North, the strength of the monthly runoff seasonality is smaller than that of precipitation due to a relatively short rainy period from January to March, catchment storage and the effect of upstream runoff contributions that are more uniform within the year. In the Peruvian highlands in the South, the strength of the monthly runoff seasonality is greater than that of precipitation, or similar, due to relatively little annual precipitation and rather uniform evaporation within the year. In the Austrian transect, the strength of the runoff seasonality is greater than that of precipitation due to the influence of snowmelt in April to June. The strength of monthly regime of precipitation and runoff controls the concentration of floods and extreme precipitation in Peruvian transects. The regions with strong monthly seasonality of runoff have also extreme events concentrated along the same time of the year and the occurrence of floods is mainly controlled by the seasonality of precipitation. In Austria, the monthly runoff maxima and floods occur in the same season in the Alps. In the lowlands, the flood seasonality is controlled mainly by summer extreme precipitation and its interplay with larger soil moisture. The analyses of precipitation and runoff data along topographic gradients in Peru and Austria showed that, overall, in Peru the spatial variation in seasonality is much larger than in Austria. This is because of the larger diversity in climate and topography.
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35

Monteiro, Andreia, Raquel Menezes, and Maria Eduarda Silva. "Modelling spatio-temporal data with multiple seasonalities: The NO2 Portuguese case." Spatial Statistics 22 (November 2017): 371–87. http://dx.doi.org/10.1016/j.spasta.2017.04.005.

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36

CLARK, ROBERT A., JOHN J. McCONNELL, and MANOJ SINGH. "Seasonalities in NYSE Bid-Ask Spreads and Stock Returns in January." Journal of Finance 47, no. 5 (December 1992): 1999–2014. http://dx.doi.org/10.1111/j.1540-6261.1992.tb04694.x.

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37

Vieira, Carlos, and Isabel Vieira. "Seasonalities in Eastern Foreign Exchange Markets: A Barrier to Euro Adoption?" Transition Studies Review 14, no. 2 (November 2007): 283–94. http://dx.doi.org/10.1007/s11300-007-0145-0.

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38

Cornett, Marcia Millon, Thomas V. Schwarz, and Andrew C. Szakmary. "Seasonalities and intraday return patterns in the foreign currency futures market." Journal of Banking & Finance 19, no. 5 (August 1995): 843–69. http://dx.doi.org/10.1016/0378-4266(95)00084-t.

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39

Halli, S. S. "The seasonality of births in Canada." Journal of Biosocial Science 21, no. 3 (July 1989): 321–27. http://dx.doi.org/10.1017/s0021932000018010.

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SummaryEarlier studies on the seasonality of births indicate that a major peak occurs in August and September and a minor peak in January and February. This study uses the 1984 Canadian Fertility Survey data on reproductive history to examine birth and pregnancy seasonalities, and shows that the ‘worst’ months for births are January and February and the ‘best’ months are March, April and May. There is no systematic pattern in the seasonality of pregnancies, possibly because effective birth control allows couples to plan the timing of births.
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40

Bildik, Recep. "Intra-day seasonalities on stock returns: evidence from the Turkish Stock Market." Emerging Markets Review 2, no. 4 (December 2001): 387–417. http://dx.doi.org/10.1016/s1566-0141(01)00026-7.

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41

Levis, Mario. "Market size and seasonalities: The case of the UK investment trust industry." Managerial and Decision Economics 8, no. 2 (June 1987): 101–11. http://dx.doi.org/10.1002/mde.4090080204.

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42

Heaney, Richard A., John G. Powell, and Jing Shi. "Share Return Seasonalities and Price Linkages of Chinese A and B Shares." Review of Pacific Basin Financial Markets and Policies 02, no. 02 (June 1999): 205–29. http://dx.doi.org/10.1142/s0219091599000138.

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This paper investigates share price linkages between Chinese corporations' foreign-designated B shares and the numerically dominant domestic A shares of the same companies. Chinese share return seasonalities are examined and the suggested satellite trading relationships are subsequently tested in order to provide an understanding of the linkages between A and B shares. The seasonality results along with arbitrage activity in the market for Chinese A and B shares suggest that a dominant-satellite relationship is likely to exist whereby the A share market is the dominant market for price formation and the B share market is the satellite. The paper identifies significant price linkages from the A to B share markets which are nevertheless weaker in an economic sense than might be expected.
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43

Graczyk, Michelle B., and Sílvio M. Duarte Queirós. "Intraday seasonalities and nonstationarity of trading volume in financial markets: Collective features." PLOS ONE 12, no. 7 (July 28, 2017): e0179198. http://dx.doi.org/10.1371/journal.pone.0179198.

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44

Ye, X., Y. Chen, J. Zhang, and X. Xia. "Effects of trends and seasonalities on robustness of the Hurst parameter estimators." IET Signal Processing 6, no. 9 (December 1, 2012): 849–56. http://dx.doi.org/10.1049/iet-spr.2012.0050.

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45

Alemu, W. G., and G. M. Henebry. "Land surface phenologies and seasonalities using cool earthlight in mid-latitude croplands." Environmental Research Letters 8, no. 4 (October 4, 2013): 045002. http://dx.doi.org/10.1088/1748-9326/8/4/045002.

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46

Bohl, Martin T., Michael Schuppli, and Pierre L. Siklos. "Stock return seasonalities and investor structure: Evidence from China's B-share markets." China Economic Review 21, no. 1 (March 2010): 190–201. http://dx.doi.org/10.1016/j.chieco.2009.12.004.

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47

Yadav, Pradeep K., and Peter F. Pope. "Intraweek and intraday seasonalities in stock market risk premia: Cash and futures." Journal of Banking & Finance 16, no. 1 (February 1992): 233–70. http://dx.doi.org/10.1016/0378-4266(92)90087-g.

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48

Wang, Rui Qing, and Zi Qian Xiao. "GARCHSK Based Risk Assessment in Electric Power Industry." Applied Mechanics and Materials 345 (August 2013): 368–71. http://dx.doi.org/10.4028/www.scientific.net/amm.345.368.

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The restructuring/deregulation in electric power industry has heightened the importance of risk assessment. A model to estimate value-at-risk via GARCHSK specification is proposed, in which the seasonalities, heteroscedasticities, skewnesses, kurtosises and relationship to system loads are jointly addressed. The impacts of probability distribution assumption for innovations on value-at-risk estimate validation are analyzed for three distributions: normal, student-t and Gram-Charlier series expansion of the normal density function. The numerical example shows that the proposed model performs better in predicting one-period-ahead VaR.
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49

Johnson, Travis L., Jinhwan Kim, and Eric C. So. "Expectations Management and Stock Returns." Review of Financial Studies 33, no. 10 (November 26, 2019): 4580–626. http://dx.doi.org/10.1093/rfs/hhz141.

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Abstract We establish a link between firms managing investors’ performance expectations, earnings announcement premiums, and cyclical patterns (i.e., seasonalities) in returns. Firms that are more likely to manage expectations toward beatable levels predictably earn lower returns before, and higher returns during, their earnings announcements. This pattern repeats across firms’ fiscal quarters, suggesting firms manufacture positive “surprises” by negatively biasing investors’ expectations ahead of announcing earnings. We corroborate these findings using non-price-based outcomes indicative of expectations management. Together, our findings are consistent with the pressure for firms to meet earnings targets shaping the cross-section of firms’ stock returns.
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50

Trull, Óscar, J. García-Díaz, and Alicia Troncoso. "Application of Discrete-Interval Moving Seasonalities to Spanish Electricity Demand Forecasting during Easter." Energies 12, no. 6 (March 21, 2019): 1083. http://dx.doi.org/10.3390/en12061083.

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Forecasting electricity demand through time series is a tool used by transmission system operators to establish future operating conditions. The accuracy of these forecasts is essential for the precise development of activity. However, the accuracy of the forecasts is enormously subject to the calendar effect. The multiple seasonal Holt–Winters models are widely used due to the great precision and simplicity that they offer. Usually, these models relate this calendar effect to external variables that contribute to modification of their forecasts a posteriori. In this work, a new point of view is presented, where the calendar effect constitutes a built-in part of the Holt–Winters model. In particular, the proposed model incorporates discrete-interval moving seasonalities. Moreover, a clear example of the application of this methodology to situations that are difficult to treat, such as the days of Easter, is presented. The results show that the proposed model performs well, outperforming the regular Holt–Winters model and other methods such as artificial neural networks and Exponential Smoothing State Space Model with Box-Cox Transformation, ARMA Errors, Trend and Seasonal Components (TBATS) methods.
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