Efficacy of time series forecasting (ARIMA) in post-COVID econometric analysis

a time-series analysis of the demand for life insurance in iran

با توجه به تجزیه و تحلیل داده ها ما دریافتیم که سطح درامد و تعداد نمایندگیها باتقاضای بیمه عمر رابطه مستقیم دارند و نرخ بهره و بار تکفل با تقاضای بیمه عمر رابطه عکس دارند

Short-Term Forecasting with ARIMA Time Series Models

Forecasting Economics and Financial Time Series: ARIMA vs. LSTM

Forecasting time series data is an important subject in economics, business, and finance. Traditionally, there are several techniques to effectively forecast the next lag of time series data such as univariate Autoregressive (AR), univariate Moving Average (MA), Simple Exponential Smoothing (SES), and more notably Autoregressive Integrated Moving Average (ARIMA) with its many variations. In par...

Theoretical Foundations of Using Econometric Methods of Time Series Forecasting

the human, ever since his emergence on the Earth, has always wanted to know what the future would bring, what events could happen. People wanted to know this not out of idle curiosity, but to be better prepared for these events. That’s the way forecasting appeared.Currently, there are different kinds of forecasts. Forecasts can be divided into short-term, middle-term and longterm. They can also...

Time series forecasting of Bitcoin price based on ARIMA and machine learning approaches

Bitcoin as the current leader in cryptocurrencies is a new asset class receiving significant attention in the financial and investment community and presents an interesting time series prediction problem. In this paper, some forecasting models based on classical like ARIMA and machine learning approaches including Kriging, Artificial Neural Network (ANN), Bayesian method, Support Vector Machine...