Smoothing Techniques for the Solution of Finite and Semi-Infinite Min-Max-Min Problems

Author(s):  
Elijah Polak
Keyword(s):  
1985 ◽  
Vol 16 (1) ◽  
pp. 29-34 ◽  
Author(s):  
W.J.M. Gerver ◽  
C.G. v.d. Laan ◽  
N.M. Drayer ◽  
W. Schaafsma

2021 ◽  
Author(s):  
Zhelun Chen ◽  
Jin Wen ◽  
Anthony Kearsley ◽  
Amanda Pertzborn

2021 ◽  
Vol 6 (2) ◽  
pp. 1-10
Author(s):  
Noreha Mohamed Yusof ◽  
Norani Amit ◽  
Nor Faradilah Mahad ◽  
Noorezatty Mohd Yusop

Forecasting the foreign currency exchange is a challenging task since it is influenced by political, economic and psychological factors. This paper focuses on the forecasting Malaysian Ringgit (MYR) exchange rate against the United States Dollar (USD) using Exponential Smoothing Techniques which are Single Exponential Smoothing, Double Exponential Smoothing, and Holt’s method. The objectives of this paper are to identify the best Exponential Smoothing Technique that describes MYR for 5 years period and to forecast MYR 12 months ahead by using the best Exponential Smoothing Technique. The comparison between these techniques is also made and the best one will be selected to forecast the MYR exchange rate against USD. The result showed that Holt’s method has the smallest value of error measure which depending on the Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE) for the evaluation part. The MSE is 1.43915x10-14 and MAPE is 2.5413 x 10-6. Meanwhile, the forecast value of MYR in August 2019 is RM 4.30226.


2012 ◽  
Vol 28 (2) ◽  
pp. 171 ◽  
Author(s):  
Paraschos Maniatis

<span style="font-family: Times New Roman; font-size: small;"> </span><p style="margin: 0in 0.5in 0pt; text-align: justify; mso-pagination: none;" class="MsoNoSpacing"><span style="color: black; font-family: &quot;Times New Roman&quot;,&quot;serif&quot;; font-size: 10pt; mso-themecolor: text1; mso-ansi-language: EN-US;">This study attempts to model the exchange rate between Euro and USD using univariate models- in particular ARIMA and exponential smoothing techniques. The time series analysis reveals non stationarity in data and, therefore, the models fail to give reliable predictions. However, differencing the initial time series the resulting series shows strong resemblance to white noise. The analysis of this series advocates independence in data and distribution satisfactorily close to Laplace distribution. The application of Laplace distribution offers reliable probabilities in forecasting changes in the exchange rate.</span></p><span style="font-family: Times New Roman; font-size: small;"> </span>


2015 ◽  
Vol 51 (4) ◽  
pp. 659-670
Author(s):  
Mohamed Abdelazeem ◽  
Rahmi N. Çelik ◽  
Ahmed El-Rabbany

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