A NEW GENETIC ALGORITHM TO SOLVE KNAPSACK PROBLEMS

Derya Turfan (), Cagdas Hakan Aladag () and Ozgur Yeniay ()
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Derya Turfan: Hacettepe University, Faculty of Science, Department of Statistics, Ankara, Turkey
Cagdas Hakan Aladag: Hacettepe University, Faculty of Science, Department of Statistics, Ankara, Turkey
Ozgur Yeniay: Hacettepe University, Faculty of Science, Department of Statistics, Ankara, Turkey

Journal of Social and Economic Statistics, 2012, vol. 1, issue 2, 40-47

Abstract: The volatility of currency exchange rates can be considered as an useful measure of uncertainty about the economic environment of a country.The paper aims to investigate the evolution of the daily RON/EURO exchange rate between January 5th, 2009 and October 12, 2012. Several appropriate models are used and discussed, from ARCH, GARCH models to EGARCH and TGARCH models, trying to capture the main features of the analysed data. The periods of low and high volatility are discussed and analysed in correlation to the negative and positive shocks. The used models are able to model asymmetries in volatility forecasts allowing for asymmetric responses in volatility to the positive and negative shocks.

Keywords: Genetic algorithms; Mean-variance optimization; Portfolio analysis; knapsack problem (search for similar items in EconPapers)
JEL-codes: C44 C61 G11 (search for similar items in EconPapers)
Date: 2012
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