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Forecasting Stochastic Volatility for Exchange Rates using EWMA
Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics. (MAM)
Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics. (MAM)ORCID iD: 0000-0002-0139-0747
Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics. (MAM)ORCID iD: 0000-0001-9635-0301
Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics. (MAM)ORCID iD: 0000-0003-4554-6528
2019 (English)In: Proceedings of 18th Applied Stochastic Models and Data Analysis International Conference with the Demographics 2019 Workshop, Florence, Italy: 11-14 June, 2019 / [ed] Christos H. Skiadas, ISAST: International Society for the Advancement of Science and Technology , 2019, p. 583-591Conference paper, Published paper (Refereed)
Abstract [en]

In risk management, foreign investors or multinational corporations are highly interested in knowing how volatile acurrency is in order to hedge risk. In this paper, using daily exchange rates and the Exponential Weighted Moving Average (EWMA) model, we perform volatility forecasting. We will investigate how used available time series affect the forecastings, i.e. how reliable our forecasting is depending on the period of used available data. We will also experiment the effects of the decay factor appearing in the model used on the forecasts.The results show that for the data used, it is optimal to use a smaller value of the decay factor and also for longer out-of-sample periods the forecasts get closer to the reality.

Place, publisher, year, edition, pages
ISAST: International Society for the Advancement of Science and Technology , 2019. p. 583-591
Keywords [en]
Exchange rate, Stochastic Volatility, Forecasting, FX Option
National Category
Probability Theory and Statistics
Research subject
Mathematics/Applied Mathematics
Identifiers
URN: urn:nbn:se:mdh:diva-47124ISBN: 978-618-5180-33-1 (electronic)OAI: oai:DiVA.org:mdh-47124DiVA, id: diva2:1395070
Conference
ASMDA2019, 18th Applied Stochastic Models and Data Analysis International Conference
Funder
Sida - Swedish International Development Cooperation AgencyAvailable from: 2020-02-20 Created: 2020-02-20 Last updated: 2020-02-24Bibliographically approved

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Malyarenko, Anatoliy

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