دانلود رایگان مقاله توقف ریسک نرخ ارز و تنوع چند ارز

عنوان فارسی
توقف ریسک نرخ ارز: تنوع چند ارز
عنوان انگلیسی
Hedging foreign exchange rate risk: Multi-currency diversification
صفحات مقاله فارسی
0
صفحات مقاله انگلیسی
6
سال انتشار
2016
نشریه
الزویر - Elsevier
فرمت مقاله انگلیسی
PDF
کد محصول
E3238
رشته های مرتبط با این مقاله
علوم اقتصادی
گرایش های مرتبط با این مقاله
اقتصاد مالی و اقتصاد پولی
مجله
مجله اروپایی مدیریت و اقتصاد کسب و کار - European Journal of Management and Business Economics
دانشگاه
گروه روش های کمی برای اقتصاد، دانشگاه مورسیا، اسپانیا
کلمات کلیدی
صلیب مصونیت، شرطی، ارزش در معرض خطر، تنوع چند ارزی، الگوریتم ژنتیک چند هدفه
چکیده

Abstract


This article proposes a multi-currency cross-hedging strategy that minimizes the exchange risk. The use of derivatives in small and medium-sized enterprises (SMEs) is not common but, despite its complexity, can be interesting for those with international activities. In particular, the reduction in the exchange risk borne through the use of natural multi-currency cross-hedging is measured, considering Conditional Value-at-Risk (CVaR) and Value-at-Risk (VaR) for measuring market risk instead of the variance. CVaR is minimized using linear programmes, while a multiobjective genetic algorithm is designed for minimizing VaR, considering two scenarios for each currency. The results obtained show that the optimal hedge strategy that minimizes VaR is different from the minimum CVaR hedge strategy. A very interesting point is that, just by investing in other currencies, a significant risk reduction in VaR and CVaR can be obtained.

نتیجه گیری

Conclusions


Movements in exchange rates are a major risk for companies with foreign currency-based activities. Different approaches, such as hedging via forwards, currency swaps, futures options and many other complex financial instruments, have been employed in order to effectively manage risk. Multi-currency cross hedging is relevant because it greatly expands the opportunity set of risk reducing alternatives. VaR and CVaR have been used for measuring currency risk exposure because they are suitable for asymmetric return distributions. This choice is consistent with the asymmetric return distribution functions exhibited in our data set.


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