Seasonal ARIMA model to Nigerian consumer price index data
نویسندگان
چکیده
منابع مشابه
An Introduction to Consumer Price Index Methodology
1.1 A price index is a measure of the proportionate, or percentage, changes in a set of prices over time. A consumer price index (CPI) measures changes in the prices of goods and services that households consume. Such changes affect the real purchasing power of consumers’ incomes and their welfare. As the prices of different goods and services do not all change at the same rate, a price index c...
متن کاملElectricity price forecasting – ARIMA model approach
Electricity price forecasting is becoming more important in everyday business of power utilities. Good forecasting models can increase effectiveness of producers and buyers playing roles in electricity market. Price is also a very important element in investment planning process. This paper presents a forecasting technique to model day-ahead spot price using well known ARIMA model to analyze an...
متن کاملGold Price Forecasting Using ARIMA Model
This study gives an inside view of the application of ARIMA time series model to forecast the future Gold price in Indian browser based on past data from November 2003 to January 2014 to mitigate the risk in purchases of gold. Hence, to give guideline for the investor when to buy or sell the yellow metal. This financial instrument has gained a lot of momentum in recent past as Indian economy is...
متن کاملForecasting Electricity Price Using Seasonal ARIMA model and Implementing RTP Based Tariff in Smart Grid
-A Smart Grid has a two-way digital communication system and it encourages customers to actively participate in different types of Demand Response (DR) programs. In the Smart Grid market, both the supplier and broker agent earn profit while distributing the electrical energy. They have to balance the supply and demand during the distribution of energy. They also participate in energy trading to...
متن کاملCombining neural network model with seasonal time series ARIMA model
This paper proposes a hybrid forecasting model, which combines the seasonal time series ARIMA (SARIMA) and the neural network back propagation (BP) models, known as SARIMABP. This model was used to forecast two seasonal time series data of total production value for Taiwan machinery industry and the soft drink time series. The forecasting performance was compared among four models, i.e., the SA...
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: American Journal of Scientific and Industrial Research
سال: 2012
ISSN: 2153-649X
DOI: 10.5251/ajsir.2012.3.5.283.287