পদ্ধতির তুলনা করুন

	Realized Volatility এবং HAR মডেল	ARIMA (Autoregressive Integrated Moving Average) মডেল	জোহানসেন কোইন্টিগ্রেশন পরীক্ষা এবং ভেক্টর এরর কারেকশন মডেল
ক্ষেত্র	অর্থায়ন	অর্থমিতি	অর্থায়ন
পরিবার	Regression model	Regression model	Regression model
উদ্ভবের বছর	2009	2015	1991
প্রবর্তক	Corsi (HAR model); Andersen, Bollerslev, Diebold & Labys (realized volatility)	Box & Jenkins (Box-Jenkins methodology)	Søren Johansen
ধরন	Time-series regression of realized variance	Univariate time-series model	Multivariate cointegration / vector error correction model
মৌলিক উৎস	Corsi, F. (2009). A Simple Approximate Long-Memory Model of Realized Volatility. Journal of Financial Econometrics, 7(2), 174-196.	Box, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021	Johansen, S. (1991). Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models. Econometrica, 59(6), 1551-1580.
অপর নাম	realized variance, HAR model, heterogeneous autoregressive model of realized volatility, HAR-RV	Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli	Johansen test, VECM, vector error correction model, multivariate cointegration
সম্পর্কিত	5	5	3
সারসংক্ষেপ	Realized volatility estimates an asset's variance directly from high-frequency intraday returns rather than from a parametric latent process. The Heterogeneous Autoregressive (HAR) model of Corsi (2009), building on the realized-volatility framework of Andersen, Bollerslev, Diebold and Labys (2003), forecasts this measure by combining daily, weekly, and monthly volatility components, and is a strong alternative to GARCH for volatility prediction.	ARIMA is a univariate time-series forecasting model that combines autoregressive, integrated (differencing), and moving-average components to predict a single continuous series from its own past. It is the centrepiece of the Box-Jenkins methodology set out in Box, Jenkins, Reinsel & Ljung's Time Series Analysis (5th ed., 2015).	The Johansen procedure is a multivariate cointegration framework, introduced by Søren Johansen in 1991, that tests for long-run equilibrium relationships among several I(1) time series. It determines how many cointegrating vectors link the series and then builds a Vector Error Correction Model (VECM) to describe the short-run dynamics around that equilibrium.