Questions tagged [garch]

Question 1

GARCH assumes constant drift $\mu$ - this imply $E[e^r]$ won't be constant and jump wildly. And it contradicts the reality, for stock prices $E[S_{t}/S_{t-1}]=E[e^r]$ doesn't jump with each time step. ...

Question 2

Taleb criticised GARCH, saying that for daily stock returns with tail exponent ~3 the 4th moment doesn't exist and so Var of Var doesn't exist. The whole concept of conditional variance breaks apart. ...

Question 3

I found that daily stock prices have different left ~3 and right ~3.7 tail exponents. The $\text{SkewStudentT}(\mu,\sigma,\nu,\lambda)$ (Hansen and other variants) can't model that, it uses same tail ...

Question 4

I study FRM part II (P2.T5.25.5 Conceptual Soundness and Sensitivity Analysis in VaR Models) and encounter this question in Bionic Turtle, please help. Would really appreciate if you can provide with ...

Question 5

Lets predict stock price distribution 1 year ahead using historical data. Price path in between not needed, only on the price on the final day. It's assumed that stock price may be affected by a) ...

Question 6

In 2004 in their paper Kluppelberg, Lindner and Maller proposed a continuous vesrion of GARCH(1,1) model (COGARCH). Below is the derivation of model formulae as presented in the original paper: ...

Question 7

Below is code using the rugarch package for the daily returns of the NDX, XAU and XAGm. The issue is that when I simulate the data 200 steps ahead for 50k sims, calculate the standard deviation of the ...

Question 8

I was reading this link on volatility prediction. It first defined realized volatility as below, so my understanding is that realized volatility is equal to $\sigma$: ...

Question 9

I understand there are limitations and practicality issues with GARCH, but does any company actually use it in their risk-management system when calculating their expected-shortfalls? Even as a basis ...

Question 10

I am comparing 2 different sentiment datasets in predicting volatility, I would have 2 questions regarding this. 1, Does it make sense to use both GARCH and HAR models for this research to cover a ...

Question 11

I'm trying to compute the standardized residuals in GARCH-MIDAS model but I think that the calculation is not similar to GARCH standard models in R. As reference I have only Engle's (2012) paper in ...

Question 12

I am doing my final paper at my bachelor. For this, I am testing mean reversion in an asset. I found this paper (Mean reversion in international markets: evidence from G.A.R.C.H. and half-life ...

Question 13

Please be easy on me since quant finance is not my strength. I have the following Python code that models volatility under GARCH(1,1) for the S&P500: ...

Question 14

I am trying to understand how climate risk impacts the financial market and I am calculating VaR and ES. I am applying the GARCH-MIDAS model to the FTSE MIB, using the Climate Policy Uncertainty Index ...

Question 15

I'm writing a research paper in economics, and would like to research the impact of both financial and macroeconomic variables on the NIFTY50 index. My plan was to use a GARCH model. I've stumbled ...

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Questions tagged [garch]

Is GARCH assumption on constant drift wrong in log space?

GARCH, Infinite Variance of Variance

Extension of SkewStudentT with different left and right tail exponents?

Adapting VaR model in a dynamic trading environment

How Random Walk with Weighted Sampling different from GARCH/ARIMA?

COGARCH (continuous GARCH) model definition

GARCH parameters generating simulations that have a lot higher standard deviation's than the historical standard deviation

modelling and forecasting volatility with python's ARCH package

Is GARCH (and or it's variations) actually used in risk-modelling for expected-shortfall?

Volatility forecast, GARCH and/or HAR?

How to compute standardized residuals in GARCH-MIDAS model?

Does it makes sense to use GARCH to measure mean reversion?

Continuation of GARCH(1,1) without data

How can I apply the GARCH-MIDAS model to the FTSE MIB using the CPU as an explanatory variable?

Is there any way to implement GARCH-MIDAS model in R for multivariate estimation?

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