ScholarGate
Pembantu

Bandingkan kaedah

Semak kaedah pilihan anda secara bersebelahan; baris yang berbeza akan diserlahkan.

Model HAR-RV bagi Volatiliti Terealisasi×Ukuran Risiko Ekor (Jangkaan Kerugian Terkurang, Spektral, Ekspektil)×
BidangKewanganKewangan
KeluargaRegression modelRegression model
Tahun asal20091999
PengasasFulvio CorsiArtzner, Delbaen, Eber & Heath (coherent risk axioms); Acerbi & Tasche (Expected Shortfall)
JenisLinear time-series regression for volatilityCoherent tail risk measure
Sumber perintisCorsi, F. (2009). A Simple Approximate Long-Memory Model of Realized Volatility. Journal of Financial Econometrics, 7(2), 174–196. DOI ↗Artzner, P., Delbaen, F., Eber, J.-M. & Heath, D. (1999). Coherent Measures of Risk. Mathematical Finance, 9(3), 203–228. DOI ↗
AliasHAR-RV, heterogeneous autoregressive realized volatility, Corsi HAR model, HAR-RV Modeli (Heterogeneous Autoregressive Realized Volatility)expected shortfall, conditional value at risk, CVaR, spectral risk measure
Berkaitan55
RingkasanThe HAR-RV model, introduced by Fulvio Corsi in 2009, forecasts realized volatility by decomposing it into daily, weekly, and monthly components. It is a simple linear regression that mirrors how market participants with different investment horizons react to volatility, and it naturally captures the long-memory behaviour of volatility.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.
ScholarGateSet data
  1. v1
  2. 1 Sumber
  3. PUBLISHED
  1. v1
  2. 2 Sumber
  3. PUBLISHED

Pergi ke carian Muat turun slaid

ScholarGateBandingkan kaedah: HAR-RV Model · Tail Risk Measures. Dicapai 2026-06-18 daripada https://scholargate.app/ms/compare