Approching EUR/CHF Exchange Rate Volatility in Albanian Market

A. Todri
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Abstract

This paper explores the forecasting of EUR/CHF exchange rate volatility in short term period in Albanian market, being that Euro is the mostly used currency in financial and commercial transactions and furthermore together with Swiss franc are considered as safe currencies with a probabilistic volatility distribution statistically interesting. Precisely the latter, represents a continuous concern for the economic agents dealing with the above mentioned exchange risk, hence the measurement of its volatility helps them in the assessment and maintenance of capital needed for coverage purposes almost referring to trade balance trend toward Euro-Area and not as well as to the Eurobond issued. Under these circumstances, the financial time series dynamic models such as ARMA (1;1), ARCH (1) and GARCH (1;1) are used to estimate the EUR/CHF exchange rate volatility in short term period. The last one, which at 95% confidence level displays satisfactory statistical parameters in confront of the others in terms of normal residuals distribution is also used to forecast EUR/CHF exchange rate during 2015 in correspondence of moving average method based on latest 252 exchange rate values. In statistical terms the comparison of EUR/CHF exchange rate forecasted data through GARCH (1;1) model with the current ones demonstrated a good robustness of the latter at the confidence level taken into consideration. Therefore, the research in question suggests to the economic agents dealing with these kinds of transactions the implementation of GARCH models for the estimation and forecasting of EUR/CHF exchange rate volatility in the short term period, necessary for risk management purposes.
接近阿尔巴尼亚市场的欧元/瑞士法郎汇率波动
本文探讨了阿尔巴尼亚市场短期内欧元/瑞士法郎汇率波动的预测,因为欧元是金融和商业交易中使用最多的货币,而且与瑞士法郎一起被认为是安全货币,其概率波动分布具有统计学意义。正是后者,代表了处理上述汇率风险的经济主体的持续关注,因此其波动性的测量有助于他们评估和维持覆盖目的所需的资本,几乎指的是向欧元区的贸易平衡趋势,而不是欧元债券的发行。在这种情况下,我们使用ARMA(1;1)、ARCH(1)、GARCH(1;1)等金融时间序列动态模型来估计欧元/瑞郎短期内的汇率波动。最后一个在95%置信水平下,在正态残差分布方面显示出令人满意的统计参数,也用于根据最新的252个汇率值,对应于移动平均法预测2015年欧元/瑞郎汇率。在统计方面,通过GARCH(1;1)模型对欧元/瑞郎汇率预测数据与当前模型的比较表明,在考虑置信水平的情况下,后者具有良好的稳健性。因此,本研究建议处理这类交易的经济主体采用GARCH模型来估计和预测短期内欧元/瑞郎汇率波动,这是风险管理所必需的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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