Linganisha mbinu

	Mfumo wa HAR-RV wa Matumizi Halisi ya Kutikisika	Urejeshaji wa Njia ya Viwango Vidogo vya Kawaida (OLS)
Nyanja	Fedha	Ekonometriki
Familia	Regression model	Regression model
Mwaka wa asili	2009	2019
Mwanzilishi	Fulvio Corsi	Wooldridge (textbook treatment); classical least squares
Aina	Linear time-series regression for volatility	Linear regression
Chanzo asilia	Corsi, F. (2009). A Simple Approximate Long-Memory Model of Realized Volatility. Journal of Financial Econometrics, 7(2), 174–196.	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
Majina mbadala	HAR-RV, heterogeneous autoregressive realized volatility, Corsi HAR model, HAR-RV Modeli (Heterogeneous Autoregressive Realized Volatility)	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Zinazohusiana	5	5
Muhtasari	The HAR-RV model, introduced by Fulvio Corsi in 2009, forecasts realized volatility by decomposing it into daily, weekly, and monthly components. It is a simple linear regression that mirrors how market participants with different investment horizons react to volatility, and it naturally captures the long-memory behaviour of volatility.	Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE).