قارن الطرق

	نموذج ARIMA (الانحدار الذاتي المتكامل للمتوسط المتحرك)	القيمة المعرضة للخطر المشروطة (النقص المتوقع)
المجال	الاقتصاد القياسي	التمويل
العائلة	Regression model	Regression model
سنة النشأة	2015	2000
صاحب الطريقة	Box & Jenkins (Box-Jenkins methodology)	Rockafellar & Uryasev (2000); Acerbi & Tasche (2002)
النوع	Univariate time-series model	Coherent tail-risk measure
المصدر التأسيسي	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	Rockafellar, R. T. & Uryasev, S. (2000). Optimization of Conditional Value-at-Risk. Journal of Risk, 2(3), 21-41.
الأسماء البديلة	Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli	CVaR, expected shortfall, average value-at-risk, tail VaR
ذات صلة	5	5
الملخص	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).	Conditional Value-at-Risk (CVaR), also called Expected Shortfall, is a coherent tail-risk measure that quantifies the conditional expectation of losses beyond the Value-at-Risk threshold. It was introduced for optimization by Rockafellar and Uryasev (2000) and shown to be coherent by Acerbi and Tasche (2002), and it has replaced VaR as the regulatory standard under Basel III/IV.