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Monte Carlo simulation for risk approach

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dc.contributor.author NOVAC, Ludmila
dc.date.accessioned 2020-11-04T08:10:41Z
dc.date.available 2020-11-04T08:10:41Z
dc.date.issued 2018
dc.identifier.citation NOVAC, Ludmila. Monte Carlo simulation for risk approach. In: CAIM 2018: The 26th Conference on Applied and Industrial Mathematics: Book of Abstracts, Technical University of Moldova, September 20-23, 2018. Chişinău: Bons Offices, 2018, p. 76. en_US
dc.identifier.uri http://repository.utm.md/handle/5014/11088
dc.description Only Abstract en_US
dc.description.abstract Foreign exchange is a risk factor that is often overlooked by enterprises that wish to enter, grow, and succeed in the global marketplace. The currency rate depends on factors that affect the economy such as trade, inflation, employment, interest rates, growth rate and others. One of the best predictions of losses could be done by using the time series of daily exchange rates for some period and make financial forecasts for the near futures, taking in the view the parameters that have influences to the exchange rates. We also could apply some statistical simulation. At present, a widely used method is the value-at-risk (VaR) model. To calculate the VaR, there exists a variety of models. Among them, the more widely-used are: the historical simulation, the variance-covariance model, and Monte Carlo simulation, which assumes that future currency returns will be randomly distributed. Monte Carlo Methods are used for portfolio evaluation. A similar approach is used in calculating value at risk. en_US
dc.language.iso en en_US
dc.publisher Bons Offices en_US
dc.subject foreign exchange en_US
dc.subject exchange rates en_US
dc.subject risk en_US
dc.subject financial forecasts en_US
dc.subject value-at-risk model en_US
dc.subject Monte Carlo methods en_US
dc.title Monte Carlo simulation for risk approach en_US
dc.type Article en_US


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