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Questions tagged [garch]

A model for time series in which the conditional variance is time-varying and autocorrelated.

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On assumptions of local projection method

It is well known that Jorda(2005) proposed the following model called local projection: $$y_{t+h} - y_{t-1} = \beta_h shock_{t} + \gamma_h ctr_{t-1} + \epsilon_{t,h}, h = 0,1,2,\dots,H.$$ I am trying ...
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Understanding Volatility Clustering: Conditional or Unconditional Variance?

A stylized fact observed in financial time series is volatility clustering. Volatility clustering is commonly described as the fact that large changes in asset prices are followed by large changes, ...
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Dependence in ARCH empirical residuals

Suppose $R_1, R_2, \dots, R_T$ are observed values of ARCH(1) process ($R_i = \sigma_i z_i$). I then estimate ARCH(1) parameters $\hat{\omega}, \hat{\alpha}$ and calculate empirical standardized ...
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How to calibrate and simulate a copula-garch model in R using rmgarch package

So I have been trying to calibrate and simulate cryptocurrencies for VaR and ES analysis using the rmgarch package in R. I have been using the t-copula, my reason being that cryptocurrencies' ...
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Rank probabilities for dependent data

It is well known that for iid sample $X_1, \dots, X_T$ rank probabilities are uniform over $1, \dots, T$. In other words, fixing $1 \le i_0 \le T$, probability of $X_{i_0}$ having rank $k$ (i.e., $X_{...
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Manual maximum likelihood estimation of realized GARCH behaving poorly

I'm trying to estimate the maximum likelihood of a realized GARCH model. Below are the equations and the parameters I want to estimate I'm using the below function to maximise the likelihood, but it ...
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Residual autocorrelation in ARMA-GARCH model

I have used the auto.arima function on my data set, which is the Ethereum-USD exchange rate, and I end up with an ARMA(2,2) model based on the AIC. I have estimated ...
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ARIMAX-GARCH flattens when using daily return, but not level

Whenever I do my ARIMAX-GARCH model for forecasting n-ahead with sentiment from news as my exogenous variable, the predictions seems normal when forecasting using level price of the stock, but it ...
BarneGeniet's user avatar
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How do I model the volatility of financial returns with an EGARCH model based on the EGB2 distribution in R?

Since this is super specific, the EGB2-distribution is not built in to the "rugarch"-package in R and I can not seem to figure out how to do this. I have formulas and equations for the PDF ...
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Different estimates of conditional mean parameters from OLS vs ARCH

Consider the market model for security $i$: $$ R_{i,t}=\alpha_i + \beta_i R_{m,t} + e_{i,t}. $$ I estimated the parameters with the OLS method. ...
Mattia's user avatar
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Conditional and unconditional mean in GARCH(1,1) model

Say I have a stationary time series and want to fit a GARCH(1,1) model. Does this mean that the conditional mean, which is used in GARCH, would always be the same as the unconditional mean of the ...
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Deriving the multivariate asset returns model and interpreting cholesky factorization

I am trying to understand the multivariate asset returns model for a portfolio of assets from chapter 4 DCC-GARCH of Orskaug "Multivariate DCC-GARCH Model With Various Error Distributions" (...
Jose_Peeterson's user avatar
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Conditional Expectation Notation in ARCH Model

I'm new to ARCH models, and I have a question about the correct notation for expressing the conditional expectation of the return at time $t(r_t)$ given the information available up to time t-1. I'd ...
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Question about the unconditional variance in the ARCH(1) model

I am studying the ARCH model for the first time and have encountered a step in the derivation that I don't fully understand. The context is as follows: ARCH(1) model is defined by the equations (as ...
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Modeling timeseries with strong seasonality

I have monthly national home price index data, from CoreLogic. Data is seasonally adjusted. But still has strong seasonal effect. Here is the plot for monthly changes. ...
deb's user avatar
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Loss function for volatility forecasts from GARCH

What are the options for loss functions, when trying to compare the volatility (sigma) forecasts from different GARCH models? I was thinking about the Qlike function but am not sure if this would give ...
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Calculating VaR from copula-GARCH using rmgarch

I'm new to both R and copula, nevertheless I want to compare VaR estimations for 25 days ahead using a GARCH and a copula-GARCH model in R. To calculate VaR for the GARCH model seems pretty straight ...
hehan123's user avatar
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How many lags to insert into a GARCH(m,p) model?

My question might be trivial, but the doubt arises due to different ways of dealing with modeling that I have found in different research papers. In particular, I was able to observe that (in time ...
Giuseppe Vonella's user avatar
1 vote
1 answer
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How to interpret the differences in estimated variances?

I estimated the variance of Bitcoin in several ways using the var command in R, and within a GARCH model. I get series that look a bit similar, but the y-axis gives ...
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Independence of Shocks in ARCH(1): A Doubt from Hayashi’s Book

I am reading Hayashi's Econometrics book, and on pages 104 and 105 he defines the ARCH(1) model for a time series $g_i$ as: \begin{aligned} g_i &= \sqrt{h_i} \varepsilon_i, \\ h_i &= \zeta + \...
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How to choose the best one model from ARIMAX, ARCH/GARCH and VAR?

Now I have 3 models to find what economic factors have an effect on gold price: ARIMAX model ARCH/GARCH model VAR model What is the tool to find the best model? In linear regression, we can ...
Susan's user avatar
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How to interpret DCC GARCH alpha and beta (dcca1 and dccb1 in R)

I have just run a DCC GARCH model in R and am trying to interpret the output. I have run the model with 3 time series. I know that alpha and beta tell about the short- and long-term spillover effect. ...
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Exogeneity of volatility shocks in Local projection model

I want to estimate the impact of volatility shocks on cross-assets spillovers. I have series of spillovers, and I want to use a Local Projection model, and the volatility of some financial assets ...
krauuuus's user avatar
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2 answers
235 views

White's test interpretation

I am running a regression in python (a basic market model with just one index as regressor). After doing that I conduct the heteroscedasticity test on residuals using two tests, White and ARCH. I am ...
Mattia's user avatar
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Show that the conditional variance $\{h_t\}$ of a GARCH process is an ARMA($m,p-1$) process

This is question 10.6(c) from Time Series and Forecasting (2nd Edition) by Brockwell and Davis. The parts (a) and (b) of this question can be found here in another SE question. Question: Suppose that $...
Balkys's user avatar
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GARCH diagnostics via standardized residuals: interpreting my findings

I have fit a GARCH(1,) model in Python, assuming the residuals are $t$ distributed. I am checking the standardized residuals. ARCH and Ljung-Box tests don't reject the null hypothesis. However, I am ...
Mattia's user avatar
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standardized residuals GARCH

I am having a hard time understanding ACF and PACF. I estimated a GARCH(1,1) model and now I am checking its standardized residuals. This is what I get: I can not really understand why the lag 0 has ...
Mattia's user avatar
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3 votes
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180 views

What aspects should I test from a fitted GARCH model?

I estimated a GARCH(1,1) assuming that the residuals follow Student-$t$ distribution. ...
Mattia's user avatar
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An ARMA model with white noise errors, that are ARCH? (How is that possible?)

First my assumption was that ARMA models take only the autocorrelation of the time series into consideration but not of the error terms (wrong!). But this assumption is wrong! As the within ARMA ...
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ANOVA of Returns and Volatilities forecast

In my GARCH(1,1) model simulations, I generated (based on two different distribution assumptions) returns and conditional volatilities for 8 stocks across 3 scenarios over a 20-day forecasting period. ...
Barbab's user avatar
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71 views

How to predict residuals using ARCH model

I have been reading about the autoregressive conditional heteroskedasticity (ARCH) models and they seem amazing. I Understand that the model captures the volatile of the variance of residuals. However,...
makala's user avatar
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Calculate price forecasts from forecasted returns

I have a question which makes me so hurt. Let's have a price time series $y_{t}$ for the same asset (for example, daily S&P 500 values) $y_{t}$ It can be trendy (trend stationary or difference ...
Dmitriy's user avatar
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Normalization of Time Series for GARCH

It is generally observed that financial times series is not normally distributed. So I want to clear the following doubts: Is it necessary to normalize time series data especially before proceeding ...
kavita d's user avatar
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Is it possible average an information criterion across models?

Is it possible to take the average of information criterion like the AIC? For my model comparison, I have 24 different models. I use 4 different GARCH models each with 6 different distributions for ...
Hello there's user avatar
1 vote
1 answer
77 views

Residuals in GARCH (1,1) is the same as the original data

I am trying to fit a GARCH(1,1) model using the rugarch package. When I use residuals to extract the residuals, I find the data ...
Ziran's user avatar
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4 votes
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MCMC predict volatility with GARCH

This is using MCMC (MH) algo to predict volatility from GARCH model: https://www.oreilly.com/library/view/machine-learning-for/9781492085249/ch04.html For simplication, consider (0,10)-GARCH (only ...
user6703592's user avatar
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1 answer
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BEKKS package in R. Are you supposed to feed residual of a mean equation model into the BEKK.fit or the return series?

I am trying to use the BEKKs Package in R. For context, my plan is to fit a VAR model of index prices to obtain the residuals. Then feed the residual into the BEKK.fit function. However, I am not sure ...
long nguyen's user avatar
2 votes
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54 views

Likelihood function of VAR-MGARCH-BEKK model?

I am doing my dissertation on the spillover effect between countries' markets and looking to use VAR-MGARCH model to do it. For example how would a change/shock of US market index affect Thailand ...
long nguyen's user avatar
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Fast algorithm of ARIMA-GARCH model selection

I use ARFIMA(p, x, q)-GARCH(P, Q) models for time series forecasting and when I calibrate models for selection the best via BIC criteria, I use "slow" approach when I calculate BIC for every ...
Dmitriy's user avatar
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3 votes
1 answer
101 views

How to Implement Newey-West covariance matrix properly for MDE estimation

I am trying to implement the MDE method for GARCH given by Baillie and Chung '01 (Estimation of GARCH Models from the Autocorrelations of the Squares of a Process, Jrl. of Time Series Analysis) but I ...
Erdem Şen's user avatar
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using the GARCH model, the result of 10 forecasting values are (erroneously) equal. Any suggestion?

I am currently facing a problem with my GARCH model, specifically with the forecasted results. It appears that all the forecasted values are turning out to be identical, which leads me to suspect that ...
Milton Bertin-Jones's user avatar
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Why the result of forecasting GARCH being constant?

I am new to researching modeling and forecasting using the GARCH model. So I am still confused about the result that I get. I forecast stock return volatility using Eviews. The best ARIMA model in my ...
LIN_Nisa's user avatar
2 votes
0 answers
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Bayesian variant of Ljung-Box test?

I am using Bayesian MCMC estimation methods for GARCH models and I want to check, if model residuals are uncorrelated. In classical frequentist approach, one would use standard Ljung-Box test to check ...
Alex Slavik's user avatar
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1 answer
333 views

Interpreting test results for ARCH effects in ARIMA model

I would like to ask you, how to correctly interpret different results for different number of lags in arch.test (R)? We reject the null hypothesis (homoscedasticity)...
lucas spring's user avatar
1 vote
0 answers
60 views

How to implement Girardi & Ergun's (2013) three-step multivariate GARCH estimation of CoVaR in R?

I'm trying to calculate multivariate GARCH estimation of conditional value-at-risk, by adopting a three-step model from Girardi & Ergun (2013) paper entitled "Systemic risk measurement: ...
Restu's user avatar
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1 vote
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GARCH (sGARCH) with ARFIMA (ARIMA) model in Rugarch equation formula output

Could you please help to write down the exact equation? It is clear for Garch part but not clear how to add ARFIMA (1,0,1) or here just ARMA(1,1) in model equation specification. Should we also type ...
Neophyte's user avatar
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97 views

How to compare the performance of a volatility forecast like GARCH (1,1) with exogenous variables (MSE?)

I want to investigate, weather financial news have an influence on the volatility prediction of asset returns (daily data) when including them into the variance model/mean model. I have fit a GARCH/...
Jascäcilie's user avatar
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1 answer
207 views

Unconditional variance of MA(1)-GARCH(1,1) process

Let $y_t = \Delta{p_t}$ denote a time series of asset log-returns, where $p_t$ are logarithmic prices; $y_t$ is generated by the conditionally heteroscedastic MA(1) process $y_t = \epsilon_t + \theta \...
user avatar
1 vote
1 answer
64 views

Auto_arima and ARCH

I have an auto_arima model that works in Python but I want to optimize it using ARCH. I have run an ARCH model on my ARIMA residuals but I do not know what to do ...
kostas1234567890's user avatar
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42 views

Full time-series analysis steps

I had a few classes related to time-series econometrics, however most were theory heavy. I would like to practice this, so I will try to analyse few stock prices, however I am not fully sure about the ...
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