Questions tagged [garch]

Question 1

I want to fit Hansen $\text{SkewT}(μ, σ, ν, λ)$ with GARCH, fixing $E[e^{r_t}]$ instead of $\mu$. This means at each step the $\mu_t$ will be adjusted. For normal case the adjustment is simple $\mu_t=\...

Question 2

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 3

I'm deep diving into the ARCH model and i had a doubt. While in AR or ARDL model the autocorrelation is a huge problem and the models themselves are shaped for fixing it, I've been reading that, in ...

Question 4

In implementing the dynamic EVT approach using the Peak Over Threshold (POT) method combined with GARCH(1,1) modeling for forecasting Value-at-Risk (VaR) and Expected Shortfall (ES). When fitting the ...

Question 5

I have a question connected with DCC-GARCH models. Let's have K timeseries, some of them are I(1) series, some - trend-stationary (T) series. For TS time series I can substract trend directly (this ...

Question 6

Most DCC-GARCH tutorials and guides I found online often use "replicate" in creating their DCC specification, i.e. ...

Question 7

DCC-GARCH is comprised of two stages: (1) estimating the univariate GARCH and (2) estimating the correlations through DCC. My time series (bond yields) is not normally distributed, as they rejected ...

Question 8

I estimated the univariate GARCH models for each series, and all coefficients are statistically significant. However, upon putting them into one DCC-GARCH model with a DCC(1,1) spec, the individual ...

Question 9

I also learned that in specifying the GARCH model, whether it's a GARCH(1,1) or whatever, that the mean model must be estimated simultaneously and not separately. To put this in to context, sometimes ...

Question 10

I read that one of the preliminary steps before fitting a GARCH model to a series is to test for stationarity. However, DCC-GARCH is modeling the time-varying correlation between two GARCH models. ...

Question 11

I use rmgarch package for DCC-GARCH model fitting and making forecasts (covariance matrix and MUs) of my portfolio based on it (one-step). So, I use ...

Question 12

I have encountered different existence conditions for the $m$-th-order unconditional moments of $\epsilon_t$ in the EGARCH process defined as $$\epsilon_t=\sigma_t\eta_t$$ $$\eta_t\sim iid(0,1)$$ $$ \...

Question 13

An ARMA(p,q)-GARCH(r,s) model specifies the conditional distribution of a time series $x_t$: \begin{aligned} x_t &= \mu_t + u_t, \\ \mu_t &= \varphi_0 + \varphi_1 x_{t-1} + \dots + \varphi_p ...

Question 14

I noticed that there is a difference between the original EGARCH process proposed by Nelson (1991) and the applied versions in standard software. For the original process (I) Nelson already stated ...

Question 15

I would like to have a reliable measure of similarity between several time series. These represents swap rates of different currencies. I would like to start simple but also make sure I am not missing ...

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Questions tagged [garch]

Hansen SkewT fast numerical approx for E[exp x] and inverse?

Is GARCH assumption on constant drift wrong in log space?

Autocorrelation between shocks in ARCH(1) model

Fitting dynamic EVT POT on standardized residuals of GARCH with rolling window

DCC-GARCH for series with unit root

DCC-GARCH: Valid to have different GARCH models for each series?

DCC-GARCH: Correct way of choosing between the normal distribution and t-distribution

DCC GARCH - Is there any merit in setting omega to zero?

Should the parameters of the DCC-GARCH model be specified simultaneously?

DCC-GARCH: Should I get the first difference of both variables even if one is stationary?

Value-at-risk calculation for DCC-GARCH model in rmgarch package

What is the actual existence condition for moments in the EGARCH process?

Combine conditional mean and variance equation to estimate point predictions in ARMA-GARCH model?

Stationarity conditions for EGARCH

Similarity between time series using GARCH residuals

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