เปรียบเทียบวิธี

	Conditional Value-at-Risk (Expected Shortfall)	ความผันผวนที่รับรู้ได้และแบบจำลอง HAR
สาขาวิชา	การเงิน	การเงิน
ตระกูล	Regression model	Regression model
ปีกำเนิด	2000	2009
ผู้ริเริ่ม	Rockafellar & Uryasev (2000); Acerbi & Tasche (2002)	Corsi (HAR model); Andersen, Bollerslev, Diebold & Labys (realized volatility)
ประเภท	Coherent tail-risk measure	Time-series regression of realized variance
แหล่งต้นตำรับ	Rockafellar, R. T. & Uryasev, S. (2000). Optimization of Conditional Value-at-Risk. Journal of Risk, 2(3), 21-41.	Corsi, F. (2009). A Simple Approximate Long-Memory Model of Realized Volatility. Journal of Financial Econometrics, 7(2), 174-196.
ชื่อเรียกอื่น	CVaR, expected shortfall, average value-at-risk, tail VaR	realized variance, HAR model, heterogeneous autoregressive model of realized volatility, HAR-RV
ที่เกี่ยวข้อง	5	5
สรุป	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.	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.