On the public citation graph

Advancing Financial Risk Estimates by Incorporating GARCH Into Value at Risk

https://doi.org/10.2139/ssrn.3137587
0 signed · 31 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/(sici)1099-131x(199604)15:3<229::aid-for620>3.0.co;2-3openalex-extracted
Forecasting stock market volatility using (non-linear) Garch models
inferredcites →https://doi.org/10.1002/(sici)1099-131x(199604)15:3<229::aid-for620>3.3.co;2-vopenalex-extracted
Forecasting stock market volatility using (non‐linear) Garch models
inferredcites →https://doi.org/10.1002/9781119202172.app1openalex-extracted
Data Description: The MSCI World Index
inferredcites →https://doi.org/10.1002/jae.800openalex-extracted
A forecast comparison of volatility models: does anything beat a GARCH(1,1)?
inferredcites →https://doi.org/10.1016/0304-405x(94)00821-hopenalex-extracted
All in the family Nesting symmetric and asymmetric GARCH models
inferredcites →https://doi.org/10.1016/0304-4076(86)90063-1openalex-extracted
Generalized autoregressive conditional heteroskedasticity
inferredcites →https://doi.org/10.1016/0304-4076(95)01736-4openalex-extracted
Modeling and pricing long memory in stock market volatility
inferredcites →https://doi.org/10.1016/0927-5398(93)90006-dopenalex-extracted
A long memory property of stock market returns and a new model
inferredcites →https://doi.org/10.1016/c2009-0-22827-3openalex-extracted
Elements of Financial Risk Management
inferredcites →https://doi.org/10.1016/j.ijforecast.2003.10.003openalex-extracted
Forecasting volatility: A reality check based on option pricing, utility function, value-at-risk, and predictive likelihood
inferredcites →https://doi.org/10.1016/j.intfin.2005.02.001openalex-extracted
Empirical analysis of GARCH models in value at risk estimation
inferredcites →https://doi.org/10.1016/j.jbankfin.2005.04.013openalex-extracted
The hidden dangers of historical simulation
inferredcites →https://doi.org/10.1016/s0378-4266(02)00283-2openalex-extracted
On the coherence of expected shortfall
inferredcites →https://doi.org/10.1017/cbo9780511753978.020openalex-extracted
A Long Memory Property of Stock Market Returns and a New Model
inferredcites →https://doi.org/10.1017/s0022109014000027openalex-extracted
On the Relation between EGARCH Idiosyncratic Volatility and Expected Stock Returns
inferredcites →https://doi.org/10.1080/09603101003636188openalex-extracted
Forecasting accuracy of stochastic volatility, GARCH and EWMA models under different volatility scenarios
inferredcites →https://doi.org/10.1093/biomet/62.2.243openalex-extracted
Omnibus Test Contours for Departures from Normality Based on √b 1 and b 2
inferredcites →https://doi.org/10.1111/j.1540-6261.1993.tb05127.xopenalex-extracted
Measuring and Testing the Impact of News on Volatility
inferredcites →https://doi.org/10.1177/0049124104268644openalex-extracted
Multimodel Inference
inferredcites →https://doi.org/10.1198/07350010152596718openalex-extracted
Testing Density Forecasts, With Applications to Risk Management
inferredcites →https://doi.org/10.1201/9781584888949openalex-extracted
Understanding Risk
inferredcites →https://doi.org/10.2139/ssrn.1028807openalex-extracted
Evaluation of Value-at-Risk Models Using Historical Data
inferredcites →https://doi.org/10.2139/ssrn.1660170openalex-extracted
inferredcites →https://doi.org/10.2139/ssrn.2603976openalex-extracted
A Simple Traffic Light Approach to Backtesting Expected Shortfall
inferredcites →https://doi.org/10.3982/ecta5771openalex-extracted
The Model Confidence Set
inferredcites →https://doi.org/10.1016/j.stamet.2004.08.004openalex-snapshot
The use of GARCH models in VaR estimation
inferredcites →https://doi.org/10.2139/ssrn.356220openalex-snapshot
Value at Risk Models in Finance
inferredcites →https://doi.org/10.3905/jod.1995.407942openalex-snapshot
Techniques for Verifying the Accuracy of Risk Measurement Models

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/s10690-023-09424-9openalex-snapshot
The Effects of Overnight Events on Daytime Return: A Market Microstructure Analysis of Market Quality
inferred← citeshttps://doi.org/10.12688/f1000research.184626.1openalex-snapshot
GARCH-Based Analysis of Stock Price Volatility and Its Role in Auditing the Going Concern Assumption under ISA 570: A Case Study of Al-Taif Islamic Bank in Iraq
inferred← citeshttps://doi.org/10.4018/978-1-7998-7634-2.ch003openalex-snapshot
Comparative Analysis of Value at Risk(VaR) of MSCI-EMI With Traditional Time Series Methods and ANN
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.