# 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.

277 questions
Filter by
Sorted by
Tagged with
798 views

### High frequency price forecast model ARMA GARCH or another?

Can you reccomend model for high frequency data (1 second and less) (returns and volatility forecasting)? Most papers use ARMA, GARCH etc in 1 minute and lower time frame. PROBLEM ARMA does not know ...
895 views

### Constant Conditional Correlation GARCH (1,1)

I am a beginner in R and my econometrics background is not very sound either. I want to build a constant conditional correlation GARCH (1,1) model in R and I found the function, the description of ...
684 views

### Explain the unconditional covariance in Dynamic Conditional correlation( DCC ) GARCH model

Confused about the unconditional covariance matrix in a DCC GARCH model. Could anyone help me understand it? My understanding is that we get the unconditional covariance before based on the data sets. ...
599 views

3k views

### How to fit a SARIMA + GARCH in R?

I'd like to fit a non stationary time series using a SARIMA + GARCH model. I have not found any package that allow me to fit this model. I'm using rugarch: model=ugarchspec( variance.model = list(...
645 views

483 views

### The use of GARCH

I have a conceptual question that I haven't managed to grasp yet and is most likely a econometrics 101 question by here it goes: If we estimate a GARCH model for a time series, how do we then use ...
605 views

17k views

### GARCH model and prediction

I have a question about the prediction of volatility and returns of a time series. Basically it is a question about predict in the ...
20k views

### GARCH(1,1) good fit found, how to predict one day volatility ahead?

I used SPY data to fit GARCH(1,1) in my model. My data starts from Jan, 2000 until Dec, 2013. I compared the volatility using runSD on the 21 rolling window and GARCH(1,1). It looks a pretty good fit ...
476 views

### How would you correct a GARCH model to deal with non mean reverting volatility?

I am currently attempting to model and forecast volatility of bitcoin but have not been able to find a GARCH model that fits the data appropriately. I've used tick data sampled at 1 hour intervals ...
182 views

### What impact does arbitrage have on realised volatility estimates?

Doing some research modeling/estimating volatility in the bitcoin market. There is quite a bit of scope for arbitrage within crypto-currency markets. Wonder if this has any impact on my volatility ...
2k views

### Optimal lag length selection criterion in GARCH(p,q) model using MATLAB

As assessed by the title, I'm trying to estimate a GARCH(p,q) model to forecast stock market volatility and, in order to be able to do that, I've to identify the optimal number of lags, p and q, to ...
225 views

### What return equation is Engle referring to in his Nobel lecture?

Engle comments in "Risk and Volatility: Econometric models and Financial Practice" that If the price of risk were constant over time, then rising conditional variances would translate linearly ...
372 views

### How come the existence of ARCH effect is not a violation of Random Walk Hypothesis 3?

An ARCH (autoregressive conditional heteroscedastic) (1) model is: $r_t=\mu +a_t$, where $a_t=$return residual, and $\mu$ is the drift of the stock return $a_t=\sigma_t\epsilon_t$, where $\sigma_t=$...
177 views

### Time-Varying Volatility and Conditional Likelihood

Engle's comment in his seminal paper "Risk and Volatility: Econometric models and Financial Practice" mentions that I had recently worked extensively with the Kalman Filter and knew that a ...
133 views

### Can we model components in a set of multivariate multi-period time-series data?

There are N data sets in periods occurring weekly/monthly, across a 10-year historical timeline. In each period, five dates are observed (labelled a to e), where a denotes the day the period starts/...
3k views

I am analyzing the volatility of financial stock returns and let's say I have a pretty good model to forecast tomorrows volatility of the stock returns. So let's say for simplicity reasons I have a ...
977 views

### Fitting Student t-distributions to log-returns

It seems that some tail-risk centric groups are bent on using Paretian and t-distributions to account for tail risk when fitting log-returns. It has been observed, however, that with and without ...
331 views

### Evaluation volatility with Garch model

I want to forecast the volatility (with Garch) of a canadian stock in 5 months with daily returns. How many data do I have to collect ? Thanks.
675 views

### Does Matlab support exogenous variables in GARCH models?

Is it possible to introduce dummy variables or explanatory variables in the GARCH variance equation (garchset and garchfit) in ...
504 views

### Cross validation of a garch model

Suppose I divide a time series into 10 sequential time windows, where each window contains 1000 data points. I want to do test 5 different garch models using cross validation. So for each model, I ...
7k views

### Algorithm to fit AR(1)/GARCH(1,1) model of log-returns

I am fitting numerically an AR(1)/GARCH(1,1) process to index and stock log-returns, $r_t=\log(P_t/P_{t-1})$, where $P_t$ is the price at time $t$, and thus far am not clear on where the observed log ...
2k views

### How to compare volatility models?

What are the most popular ways to compare volatility models? Suppose I wanted to compare the forecasting accuracy of a GARCH(1,1) model with the historic 30 day volatility. What method should I use?
1k views

### GARCH(1,1) prediction in R - Basic Questions

Background to question: Hi, I was trying to fit a GARCH(1,1) model to the variance of log returns of a series, and ARMA(0,0) for the mean. I was using the fGarch package to do this. The aim of the ...