विधियों की तुलना करें

	कंडिशनल वैल्यू-एट-रिस्क (अपेक्षित कमी)	वास्तविक अस्थिरता और HAR मॉडल
क्षेत्र	वित्त	वित्त
परिवार	Regression model	Regression model
उद्भव वर्ष	2000	2009
प्रवर्तक	Rockafellar & Uryasev (2000); Acerbi & Tasche (2002)	Corsi (HAR model); Andersen, Bollerslev, Diebold & Labys (realized volatility)
प्रकार	Coherent tail-risk measure	Time-series regression of realized variance
मौलिक स्रोत	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.
उपनाम	CVaR, expected shortfall, average value-at-risk, tail VaR	realized variance, HAR model, heterogeneous autoregressive model of realized volatility, HAR-RV
संबंधित	5	5
सारांश	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.