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Statistisk undersökning av valutakurser: En jämförelse mellan olika prognosmodeller
Stockholm University, Faculty of Social Sciences, Department of Statistics.
2017 (Swedish)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
Statistical Research of Exchange Rates : Comparison between Different Forecasting Models (English)
Abstract [sv]

Valutamarknaden är världens största marknad och en nödvändig del av dagens globala samhälle, som gör det möjligt för företag att göra affärer i olika valutor och mellan olika gränser. Marknaden utgör en stor handelsplattform för både små och stora aktörer, för vilka det är viktigt att prognostisera valutakurser med gott resultat. Att modellera finansiella instrument i form av tidsserier är en av de vanligaste investeringsstrategierna och dess användningsområde sträcker sig från valutamarknaden till bland annat aktiemarknaden och råvarumarknaden. I denna uppsats undersöks fyra olika statistiska metoder för att modellera valutakursen Euro-US Dollar givet historisk data, och prognoser görs med de framtagna modellerna. Dessa metoder är slumpvandring, ARIMA, ARIMA-GARCH och VAR. Vidare undersöks för den dynamiska VAR-modellen hur valutamarkanden påverkar, och blir påverkad av, långa och korta räntan. Resultaten visar att ARIMA(3,1,2) förklarar valutakursen bäst medan VAR(2) med valutakursen och skillnaden mellan långa räntor som ingående variabler ger de bästa prediktionerna.

Abstract [en]

The foreign exchange market is the world’s largest market and is an essential part of the global society of today. The FX market enables companies to trade with different currencies across country borders. It is also a large trade-platform for both big and small financial actors, who greatly benefit from the advantages of good predictions. Modeling of financial instruments is one of the most commonly used investment strategies and its area of application ranges from the FX market to markets suchas the stock market and the commodity market. In this paper, four different statistical models are used to model the currency pair Euro-US Dollar. These methods are random walk, ARIMA, ARIMA-GARCH and VAR. Besides investigating which method that gives the best forecasts, the method that best describes the training datais also found. Furthermore, for the dynamic VAR model, it is explored how the FX market affects, and is affected by, the long term and short term interest. The results show that ARIMA(3,1,2) is the best at describing the exchange rate while VAR(2) with the exchange rate and the difference between long term interests as variables gives the best predictions.

Place, publisher, year, edition, pages
2017. , p. 39
Series
Stockholm studies in statistics, ISSN 0280-4018 ; 2017:14
Keywords [en]
Random Walk theorem, financial instruments, technical analysis, ARIMA, GARCH, VAR, impulse response functions
Keywords [sv]
Tidsserieanalys, Random Walk teoremet, finansiella instrument, teknisk analys, ARIMA, GARCH, vektor-autoregression, impulssvar
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:su:diva-152182OAI: oai:DiVA.org:su-152182DiVA, id: diva2:1178062
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Available from: 2018-02-09 Created: 2018-01-27 Last updated: 2018-02-09Bibliographically approved

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CiteExportLink to record
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