Evaluating forecasting performance for interval data
نویسندگان
چکیده
منابع مشابه
Evaluating the Performance of Forecasting Models for Portfolio Allocation Purposes with Generalized GRACH Method
Portfolio theory assumes that investors accept risk. This means thatin the equal rate of return on the two assets, the assets were chosenthat have a lower risk level. Modern portfolio theory is accepted byinvestors who believe that they are not cope with the market. Sothey keep many different types of securities in order to access theoptimum efficiency rate that is close to the rate of return o...
متن کاملEvaluating the Performance and Classifying the Interval Data in Data Envelopment Analysis
Standard data envelopment analysis (DEA) supposes that measure status from point of view input or output is known. Nevertheless, in some situations, determining the status of a performance measure is not easy. Measures with unknown status of input /output are called flexible measures. Moreover, traditional DEA models do not deal with imprecise data and assume that all input and output are exact...
متن کاملA Data Envelopment Analysis Method for Evaluating Performance of Customer Relationship Management
Customer relationship management (CRM) is one of the fastest growing management approaches which can lead to stronger competitive position, resulting in larger market share and profitability. In this study, CRM efficiency among the customers of the Iranian banks is analyzed using a network data envelopment analysis (NDEA) approach. To implement CRM in the NDEA model, input, intermediate and out...
متن کاملMachine Learning Models for Housing Prices Forecasting using Registration Data
This article has been compiled to identify the best model of housing price forecasting using machine learning methods with maximum accuracy and minimum error. Five important machine learning algorithms are used to predict housing prices, including Nearest Neighbor Regression Algorithm (KNNR), Support Vector Regression Algorithm (SVR), Random Forest Regression Algorithm (RFR), Extreme Gradient B...
متن کاملForecasting with interval and histogram data Some financial applications∗
Data sets across many disciplines are becoming consistently large and they bring with them the need of new methods for processing information. We introduce the analysis of interval-valued and histogram-valued data sets as an alternative to classic single-valued data sets and we show the promise of this approach on dealing with economic and financial data. Being our current focus the prediction ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Computers & Mathematics with Applications
سال: 2008
ISSN: 0898-1221
DOI: 10.1016/j.camwa.2008.03.042