مقایسهٔ روش‌ها

	معیارهای ریسک دنباله (کسری مورد انتظار، طیفی، انتظار)	رگرسیون حداقل مربعات معمولی (OLS)
حوزه	مالی	اقتصادسنجی
خانواده	Regression model	Regression model
سال پیدایش	1999	2019
پدیدآور	Artzner, Delbaen, Eber & Heath (coherent risk axioms); Acerbi & Tasche (Expected Shortfall)	Wooldridge (textbook treatment); classical least squares
نوع	Coherent tail risk measure	Linear regression
منبع بنیادین	Artzner, P., Delbaen, F., Eber, J.-M. & Heath, D. (1999). Coherent Measures of Risk. Mathematical Finance, 9(3), 203–228.	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
نام‌های دیگر	expected shortfall, conditional value at risk, CVaR, spectral risk measure	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
مرتبط	5	5
خلاصه	Tail risk measures quantify the loss distribution beyond Value-at-Risk (VaR). Expected Shortfall — the expected loss given that VaR is exceeded — is the leading coherent risk measure, formalised by Artzner, Delbaen, Eber and Heath (1999) and shown to be coherent by Acerbi and Tasche (2002). Spectral and expectile-based measures generalise it.	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).