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[{"key": "dc.contributor.advisor", "value": "Raatikainen, Juhani", "language": "", "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.author", "value": "Ahokas, Veera", "language": "", "element": "contributor", "qualifier": "author", "schema": "dc"}, {"key": "dc.date.accessioned", "value": "2021-06-11T11:44:14Z", "language": null, "element": "date", "qualifier": "accessioned", "schema": "dc"}, {"key": "dc.date.available", "value": "2021-06-11T11:44:14Z", "language": null, "element": "date", "qualifier": "available", "schema": "dc"}, {"key": "dc.date.issued", "value": "2021", "language": "", "element": "date", "qualifier": "issued", "schema": "dc"}, {"key": "dc.identifier.uri", "value": "https://jyx.jyu.fi/handle/123456789/76460", "language": null, "element": "identifier", "qualifier": "uri", "schema": "dc"}, {"key": "dc.description.abstract", "value": "Rahoitusmarkkinoiden on tutkittu kohtaavan useita kausittaisuuksia, joita kutsutaan anomalioiksi. Kuukausitasolla tammikuuilmi\u00f6 on kaikista tutkituin anomalia, ja my\u00f6s t\u00e4m\u00e4 tutkimus keskittyy siihen. Tehokkaiden markkinoiden hypoteesin mukaan aiempien osakekurssien avulla ei pit\u00e4isi pysty\u00e4 ennustamaan tulevia osakekursseja, ja tammikuuilmi\u00f6 onkin todiste t\u00e4t\u00e4 hypoteesia vastaan. Siit\u00e4 l\u00e4htien kun tammikuuilmi\u00f6 havaittiin ensimm\u00e4isen kerran, se on k\u00e4ynyt l\u00e4pi intensiivisi\u00e4 empiirisi\u00e4 tutkimuksia erilaisilla menetelmill\u00e4, jotka ovat tuottaneet ristiriitaisia tuloksia. Useimmissa tutkimuksissa tammikuuilmi\u00f6n on havaittu esiintyv\u00e4n markkina-arvoltaan pienten yritysten osakkeissa. Kolme yleisimmin ehdotettua mahdollista selitt\u00e4v\u00e4\u00e4 tekij\u00e4\u00e4 tammikuuilmi\u00f6lle ovat verohypoteesi, informaatiohypoteesi sek\u00e4 portfolion uudelleenmuodostamishypoteesi. Vaikka useissa tutkimuksissa havaitaan viel\u00e4kin tammikuuilmi\u00f6t\u00e4, sen on todettu pienenev\u00e4n tai jopa h\u00e4vi\u00e4v\u00e4n.\n\nT\u00e4ss\u00e4 tutkimuksessa tarkastellaan aiempaa kirjallisuutta, mutta sen laajuutta rajoittaa volatiilisuuden vaikutusta k\u00e4sittelevien tutkimusten pieni lukum\u00e4\u00e4r\u00e4. Tarkastelun kohteena olevassa kirjallisuudessa menetelmin\u00e4 on k\u00e4ytetty joko regiimin muutosmallia tai GARCH-mallia. Kirjallisuus, jossa k\u00e4ytet\u00e4\u00e4n j\u00e4lkimm\u00e4ist\u00e4 menetelm\u00e4\u00e4, toimii t\u00e4m\u00e4n tutkimuksen perustana.\n\nT\u00e4m\u00e4n tutkimuksen empiirisess\u00e4 osassa tutkitaan riskin toimimista selitt\u00e4v\u00e4n\u00e4 tekij\u00e4n\u00e4 joulu- ja tammikuuilmi\u00f6lle Yhdysvaltojen osakemarkkinoilla vuosien 1926\u20132021 aineistolla. Analyysi tehd\u00e4\u00e4n k\u00e4ytt\u00e4m\u00e4ll\u00e4 lineaarista GARCH-mallia. Lis\u00e4ksi tutkimuksessa tarkastellaan tammikuuilmi\u00f6n ja yrityskoon v\u00e4list\u00e4 suhdetta.\n\nT\u00e4m\u00e4n tutkimuksen tulokset osoittavat, ett\u00e4 yrityksen markkina-arvon kasvaessa joulukuuilmi\u00f6 kasvaa ja markkina-arvon laskiessa tammikuuilmi\u00f6 kasvaa. Tulokset osoittavat my\u00f6s, GARCH-in-Mean -ilmi\u00f6 esiintyy markkina-arvoltaan pienten yritysten osakkeissa.", "language": "fi", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.abstract", "value": "Financial markets have been researched to encounter several seasonal patterns, which are called anomalies. The January effect is the most studied anomaly at the monthly level, and this research studies it too. The Efficient Market hypothesis suggests that past stock prices should not have predictive power on future stock prices, and the January effect is a proof against it. Since the January effect was found, it has gone through intense empirical investigations with various methods causing conflicting results. In most of the research papers, January effect has been found to be in shares of the companies having the smallest market value. The three commonly suggested possible explanatory factors behind the January effect are the Tax-Loss-Selling hypothesis, the Information hypothesis, and the Portfolio Rebalancing hypothesis. Although in several researches the January effect is still observed, it has been stated to be diminishing or even disappearing.\n\nIn this research a review of previous literature is done, although regarding the impact of volatility on the January effect, it is somewhat limited by the small number of research papers on this subject. In the literature either Markov regime switching model or a time-series GARCH approach is used as the methodology. Literature, where the latter methodology is used, serve as the basis of this research.\n\nIn the empirical part of this research risk being the possible explanatory factor behind the December and January effect in the United States stock markets, with data from years 1926\u20132021, is studied. The analysis is done by using the multiple linear regression analysis and the GJR-GARCH approach. In addition, the relationship between the January effect and the firm size, is examined.\n\nThe results of this research show that when the market value of the companies increases the December effect increases and, on the opposite, when the value decreases the January effect increases. The results also show that a GARCH-in-Mean effect is observed in shares of small market value companies.", "language": "en", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Submitted by Miia Hakanen (mihakane@jyu.fi) on 2021-06-11T11:44:14Z\nNo. of bitstreams: 0", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Made available in DSpace on 2021-06-11T11:44:14Z (GMT). No. of bitstreams: 0\n Previous issue date: 2021", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.format.extent", "value": "34", "language": "", "element": "format", "qualifier": "extent", "schema": "dc"}, {"key": "dc.format.mimetype", "value": "application/pdf", "language": null, "element": "format", "qualifier": "mimetype", "schema": "dc"}, {"key": "dc.language.iso", "value": "eng", "language": null, "element": "language", "qualifier": "iso", "schema": "dc"}, {"key": "dc.rights", "value": "In Copyright", "language": "en", "element": "rights", "qualifier": null, "schema": "dc"}, {"key": "dc.subject.other", "value": "January effect", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "December effect", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "company size", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "stock returns", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.title", "value": "December and January effect and Volatility in the United States Stock Markets", "language": "", "element": "title", "qualifier": null, "schema": "dc"}, {"key": "dc.type", "value": "master thesis", "language": null, "element": "type", "qualifier": null, "schema": "dc"}, {"key": "dc.identifier.urn", "value": "URN:NBN:fi:jyu-202106113666", "language": "", "element": "identifier", "qualifier": "urn", "schema": "dc"}, {"key": "dc.type.ontasot", "value": "Pro gradu -tutkielma", "language": "fi", "element": "type", "qualifier": "ontasot", "schema": "dc"}, {"key": "dc.type.ontasot", "value": "Master\u2019s thesis", "language": "en", "element": "type", "qualifier": "ontasot", "schema": "dc"}, {"key": "dc.contributor.faculty", "value": "Jyv\u00e4skyl\u00e4 University School of Business and Economics", "language": "en", "element": "contributor", "qualifier": "faculty", "schema": "dc"}, {"key": "dc.contributor.faculty", "value": "Jyv\u00e4skyl\u00e4n yliopiston kauppakorkeakoulu", "language": "fi", "element": "contributor", "qualifier": "faculty", "schema": "dc"}, {"key": "dc.contributor.department", "value": "Taloustieteet", "language": "fi", "element": "contributor", "qualifier": "department", "schema": "dc"}, {"key": "dc.contributor.department", "value": "Business and Economics", "language": "en", "element": "contributor", "qualifier": "department", "schema": "dc"}, {"key": "dc.contributor.organization", "value": "Jyv\u00e4skyl\u00e4n yliopisto", "language": "fi", "element": "contributor", "qualifier": "organization", "schema": "dc"}, {"key": "dc.contributor.organization", "value": "University of Jyv\u00e4skyl\u00e4", "language": "en", "element": "contributor", "qualifier": "organization", "schema": "dc"}, {"key": "dc.subject.discipline", "value": "Taloustiede", "language": "fi", "element": "subject", "qualifier": "discipline", "schema": "dc"}, {"key": "dc.subject.discipline", "value": "Economics", "language": "en", "element": "subject", "qualifier": "discipline", "schema": "dc"}, {"key": "yvv.contractresearch.funding", "value": "0", "language": "", "element": "contractresearch", "qualifier": "funding", "schema": "yvv"}, {"key": "dc.type.coar", "value": "http://purl.org/coar/resource_type/c_bdcc", "language": null, "element": "type", "qualifier": "coar", "schema": "dc"}, {"key": "dc.rights.accesslevel", "value": "openAccess", "language": null, "element": "rights", "qualifier": "accesslevel", "schema": "dc"}, {"key": "dc.type.publication", "value": "masterThesis", "language": null, "element": "type", "qualifier": "publication", "schema": "dc"}, {"key": "dc.subject.oppiainekoodi", "value": "2041", "language": "", "element": "subject", "qualifier": "oppiainekoodi", "schema": "dc"}, {"key": "dc.subject.yso", "value": "anomaliat", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "GARCH-mallit", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "arvopaperimarkkinat", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "volatiliteetti", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "anomalies", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "GARCH models", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "security market", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "volatility (societal properties)", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": 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