Reducing arbitrage risk by fuzzy regression based prediction of exchange rates for composite currencies

Some financial instruments are denominated in several currencies rather than a single currency. This increases the volatility in exchange rates as well as the uncertainty in predictability. Therefore, fuzzy axiomatic structure is implemented to increase both mathematical tractability and physical realism of the problem for composite currency. We used the theoretical development from our earlier work on fuzzy regression analysis and utilized non-symmetric fuzzy coefficients to predict exchange rate for European Currency Unite (ECU). The significance of the research is in its ability to break newer grounds in the uncertain economic environment. The simulation results highlight both the timeliness and the efficiency of the proposed model