Сравнение на методи

	Квантил-върху-квантилна (КвКв) регресия	Векторна авторегресия (VAR)
Област	Иконометрия	Иконометрия
Семейство	Regression model	Regression model
Година на възникване	2015	1980
Създател	Sim and Zhou	Christopher A. Sims
Тип	Nonparametric quantile regression	Multivariate time-series model
Основополагащ източник	Sim, N., & Zhou, H. (2015). Oil prices, US stock return, and the dependence between their quantiles. Journal of Banking and Finance, 55, 1-8.	Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48.
Други названия	QQ regression, QQ approach, quantile-on-quantile approach, nonparametric quantile regression	VAR, VAR model, vector autoregressive model, multivariate autoregression
Свързани	6	5
Резюме	Quantile-on-quantile regression is a nonparametric technique that estimates how the quantiles of one variable depend on the quantiles of another. By combining standard quantile regression with local linear smoothing, it produces a full two-dimensional surface of slope coefficients indexed by both the quantile of the outcome and the quantile of the predictor, revealing heterogeneous and asymmetric dependency structures invisible to standard regression.	Vector Autoregression is a multivariate time-series model in which each variable is regressed on its own lags and the lags of all other variables in the system. Originally proposed by Sims (1980) as a data-driven alternative to large structural macroeconomic models, VAR has become the standard workhorse for dynamic analysis in empirical economics and finance.