Questions tagged [garch]

Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model is used for time series in which the conditional variance is time-varying and autocorrelated. The conditional variance is a linear combination of lagged conditional variances and lagged squared errors. The conditional variance equation in GARCH models is deterministic, in contrast to Stochastic Volatility (SV) models.

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2answers
138 views

Volatility clustering and Behavioral Finance, possible explanation

Currently studying about time series modelling of financial data and faced the known GARCH$(p,q)$ model for modelling volatility. We observe that big changes are followed by large changes and vice ...
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218 views

Kurtosis in GARCH

In a GARCH(1,1) model $$ x_t = \sigma_tz_t$$ $$\sigma_{t+1}^2=a_0 + a_1x_t^2 + b_1\sigma_t^2$$ the kurtosis (when it exists) can be shown to be equal to $$ \kappa_x = \kappa_z \frac{1-(a_1+b_1)^2}...
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40 views

Unconditional correlation in CCC GARCH

What is the unconditional correlation (covariance) in CCC GARCH model $$\mathbf{x}_{t+1} = \mathbf{H}_{t+1}^{1/2} \mathbf{z}_{t+1}$$ $$\mathbf{H}_{t+1} = \mathbf{D}_{t+1}^{1/2} \mathbf{R} \mathbf{D}_{...
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186 views

GARCH fit: “failure to achieve convergence”… a problem?

Sometimes when one is trying to fit a GARCH model may happen that in the estimation summary (whatever software is) there is written "failure to achieve convergence after n iteration" or similar things....
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1answer
66 views

Negative signs in GARCH equation

When one try to fit a GARCH on a time series it may happen that one or more coefficients in the estimation output have negative sign. In these cases: all the negative coefficients (and relative ...
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51 views

Double sign for the error term in an ARMA-GARCH model

Why in an ARMA-GARCH model for a stationary series $r$ (without $c$ for simplicity) is $r_{forecast} = ARMA + \sqrt{GARCH} \cdot inn$ and not $r_{forecast} = ARMA \pm \sqrt{GARCH} \cdot inn$? The ...
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1answer
54 views

What's the correct graphical comparison in a GARCH fit?

Suppose that the stationary series $r_t$ is well fitted by an $ARMA(p,q)+c$ and $GARCH(r,s)$ model, where $GARCH(r,s) = \sigma_t ^2$ If in the testing sample I have to graphically compare the ...
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141 views

Error distribution assumption in a simple ARIMA model

why in an ARIMA-GARCH structure I have to assume an error distribution to run the estimation while in a simple ARIMA model it is not required? Thank you
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31 views

Finding the distribution and moments of returns with GARCH models (in R if possible)

I understand the GARCH type models and I know how to fit a model to a time series. But, there is a paper which calculates the moments of the distribution of returns (Variance, Skewness, and Kurtosis) ...
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1answer
49 views

Can GARCH volatility simulations generally be applied to return-modelling models?

This may be a naive question, but I still hope some discussion can elucidate a (so far) totally nebulous point for me. I've recently learned that GARCH models can give one simulations of ...
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64 views

EWMA Volatility vs Volatility of EWMA

Is taking the standard deviation of a EWMA smoothed series equivalent to getting the EWMA volatility for that series?
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94 views

ARCH Model: Which part does AR refer to?

My background is signal processing and I am fairly new to (financial) time series analysis. I was reading the article about autoregressive conditional heteroskedasticity (ARCH) models on Wikipedia. ...
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40 views

Drop weekend data Vs fill weekend data for GARCH-type modelling

I have a dilemma for an analysis I'm currently on. I doing some GARCH modelling of bitcoin and a fiat currency. There are some null values with the fiat datasets in comparison with bitcoin data as ...
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61 views

ARMA/GARCH forecasting prices?

i am dealing with brent crude oil price data and i am trying to forecast prices via ARMA/GARCH. I first convert prices into returns (return=diff(ln(P(t)-lnP(t-1))*100) and i obtained a stationnary ...
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1answer
629 views

Hedging with variance swaps: how to calculate the notional

Returns on an asset are negatively correlated with own variance, and I would like to set up a hedge with a variance swap (no options are traded). I need to decide on the notional of the swap: any ...
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102 views

Asset class dynamics differences

If we compare daily return dynamics of the main asset class time series (e.g. Stock indexes, bonds, precious commodities, etc) do we observe quantifiable differences? Are there some reference paper on ...
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60 views

ARIMA vs ARIMA + GARCH [closed]

If an ARIMA model converges quickly, would using GARCH improve the forecast performance? By improve I mean provide longer time periods for forecasts. Basically trying to forecast returns.
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326 views

Accuracy for GARCH models

How does one calculate the accuracy of forecasts given by GARCH models considering GARCH is run on returns. Assuming GARCH is a derivative of a regression based prediction model, would regular ...
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593 views

GARCH modeling - sliding or expanding window?

In practice, when modeling volatility do people tend to use expanding or sliding windows to fit GARCH models? For example see rolling forecast generation vs recursive forecast generation in the ...
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114 views

Explanation and Application of Quantile Regression of Value-At-Risk

Self-learner here. Please, excuse me if I am asking a Question already answered, but the explanations that I find online, just seem to be a bit hard for me. I am currently trying to apply the Basel ...
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1answer
364 views

Criticise GARCH relative to Realized Volatility

I would like to have your opinion about a simple question. While GARCH would be useful to calculate the conditional volatility, and the RV being in some sense the "historical" volatility, what would ...
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150 views

Measure how different forecasted volatility is from realized volatility

Hi Quantitative Finance Stack Exchange, I'm looking for an opinion on a simple question. Suppose I use a Garch(1,1) model to make a volatility forecast. At time $t$, I have realized volatility $\...
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64 views

Determine GARCH(1,1) from a mean reverting time series recursion

Let $(v_t)$ be a discrete time series of variance obeying a mean-reverting variance process $v_t$, which is actually the discrete version of the Heston model in finance. \begin{align} x_t &= \sqrt{...
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1answer
476 views

How to add controls (regressors) to GARCH model in R?

How can I estimate a GARCH(1,1) model with control variables like this: $$Y_t=a_0+a_1X_t+e_t$$ where$$ e_t\sim N(0,h_t)$$ $$h_t=b_0+b_1e_{t-1}^2+b_3h_{t-1}+b_3Z_t$$ I've checked some packages but can'...
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82 views

Typical SPX variance GARCH(1,1) coefficients

Can someone provide a typical numerical values of GARCH(1,1) coefficients $(\omega,\alpha,\beta)$ for estimating SPX index variance? I will appreciate it if some references could be provided.
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184 views

Garch(1,1) in R [closed]

I'm evaluating the impact of two variables on stock returns. For this I am using a Garch(1,1)-model in RStudio. This is the result I am getting. Why is the garch model not a valid choice? The external ...
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137 views

ARMA-GARCH Forecasting [closed]

I want to forecast a differenced time series of an Index using the combined ARMA-GARCH model (because I want to forecast the mean and not the variance). My model is a ARMA(2,2)-GARCH(1,1) model. So ...
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1answer
778 views

VaR : Student-t GARCH

I have a question on the VaR estimation via the student t GARCH model. Under this framework, the one day ahead VaR estimate is calculated by the following formula: $$VaR_{p}=\mu_{t+1}+\sigma_{t+1}\...
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65 views

Deduce GARCH(1,1) to the stochastic variance model

Here is the proof that the limit of GARCH(1,1) $$\sigma_n^2 = \gamma V_L + \alpha u_{n-1}^2 + \beta\sigma_{n-1}^2$$ is equivalent to stochastic process of variance $$d V = \alpha(V_L - V) dt + \xi VdW....
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180 views

Unconditional variance of an E-GARCH model

I am attempting to calculate the unconditional variance of an E-GARCH model: $$\log(h_{t+1}) = \beta_{0} + \beta_{1}\log(h_{t}) + \beta_{2}\left[|\varepsilon_{t} - \lambda| + \gamma(\varepsilon_{t} - \...
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79 views

VaR estimation when returns are not independent, e.g. ARCH

Time series of returns, $r_t$, in finance are often modeled with some type of conditional heteroskedasticity model, e.g. ARCH(1): $$r_t = \sigma_t z_t$$ $$\sigma_t^2 = a_0 +a_1 r_{t-1}^2$$ where, ...
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487 views

GARCH Option Pricing Model (Duan 1995)

I am trying to replicate Duan's results from his 1995 Paper, "The GARCH Option Pricing Model". I have written this code in Python myself, and using his parameters I consistently seem to obtain results ...
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115 views

I am trying to fit an GARCH(p,q) model to FX volatility. Should I be interested in the t-value of GARCH parameters?

So what I am trying to do is to model the volatility for different currencies by fitting a GARCH(p, q) model. I am selecting the values of (p, q) by iteratively going through p & q such that max(p,...
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3k views

Can I forecast stock returns using GARCH?

I know this is a rookie question, but I have seen some comments about using GARCH to forecast stock returns. Is it something people do? Wasn't GARCH just for volatility? Also, can you suggest any (...
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126 views

Information criteria via different GARCH models

I have a question about comparison of different GARCH models via information criteria. I use rugarch package. So, let's have 3 model types: "sGARCH", "eGARCH", "gjrGARCH". I fit all 3 type models for ...
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777 views

What are the significant implications of the long-run average variance rate and why Engle won the Nobel Prize for ARCH model development?

In a ARCH(m) model we have $$ \sigma_n^2=\sum_{i=1}^{m} \alpha_i u_{n-i}^2 $$ where $u_i$ is defined as the continuously compounded return during day $i$ (between the end of day $i-1$ and the end of ...
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1answer
83 views

Ljung_Box Statistic of R and R^2 values in Return analysis

I have found a result that I find truly puzzling. Here is an extract from a GARCH-Analysis I have performed: Test______________Statistic_______p-Value Ljung-Box Test_____R Q(10)_____0....
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1answer
629 views

R fGARCH fitted Values

I am using the fGARCh package in R to analyze volatility of stock returns. More precisely I am using a garch(1, 1) fit. The code ...
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136 views

simulating from GARCH model with copula innovations

I have a GARCH model fitted on stock returns as: ...
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1answer
649 views

How can I compare 30 day implied volatility forecasts with GARCH forecasts?

I'm trying to understand whether there is a good way to compare forecasts for volatility from different sources i.e., implied volatility and GARCH. I'll outline a few statements that I believe and if ...
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1answer
685 views

EGARCH fitting in R

I am using the fGarch package in R to analyze stock volatility. To do this I am using the garchFit formula on my time series. ...
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1answer
213 views

Under which circumstances can conditional distribution of asset returns be less Gaussian than the unconditional distribution?

I looked into the unconditional and the conditional distribution of a return series, where the unconditional distribution is simply the marginal distribution of the returns, and the conditional ...
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102 views

Investigating a question: “Does commodity price volatility scale with price level?”

I'm trying to answer a simply posed question using a GARCH model: can we expect larger price shocks in a commodity when it's price is higher? (i.e., may we expect larger price shocks at \$100 per ...
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1answer
286 views

VAR-aDCC full ARCH and GARCH parameter matrices in R

I am working with the rmgarch package in R and I estimated a VAR-aDCC model. Is there any way to extract the extended version of estimates (allowing for volatility ...
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1answer
535 views

GARCH mean and volatility spillover R commands needed

I analyzed an MA(1)-GARCH(1,1) model in R, and now I want to test the conditional mean and volatility spillover effect between the two time series (exchange rates) (based on Hamao et al., 1990). ...
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100 views

What are the current gold standards for volatility prediction error?

I'm working on volatility forecasting models for equities and currencies. I am using daily data and am interested in producing forecasts for the next n days. To ...
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1answer
324 views

Joint estimation of GARCH models with ARMA terms in the conditional mean: a necessity?

Supposing I am using the following models to forecast conditional volatility of index returns, whereby In-sample data is 1996-2007 and out of sample data is 2007-2012, using GARCH type models. I have ...
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143 views

Questions on the concept of GARCH model [closed]

As we all know, the GARCH model is stated as $\epsilon_t = \sigma_tz_t$ $\sigma_t^2 = w + \sum^q_{i=1}\alpha_i\epsilon_{t-i}^2 + \sum^q_{i=1}\beta_i\sigma_{t-i}^2$ In application, the estimate $\hat{\...
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217 views

Most GUI user friendly Time series Econometrics software for modelling and Forecasting GARCH models [closed]

I think the question is simple enough. I have been using Eviews, but it is unable to do recursive one step ahead forecasting directly and requires me to use coding, which I'm not very good at. I need ...
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1answer
739 views

Correct procedure for modelling GARCH for forecasting volatility of stock Index returns

I will be using Eviews and am looking to forecast volatility of stock index returns using ARCH/GARCH models. I've generated the logarithmic returns and done the unit root tests. I then proceeded to ...