All Questions
Tagged with forecasting garch
49
questions
0
votes
1
answer
65
views
Profitability on Value at Risk forecasting
I'm conducting a research related to Value at Risk forecasting using volatility models like GARCH and others. My predictions are turning out quite well with some models. Is there a way to capitalize ...
0
votes
0
answers
222
views
Is my time horizon for GARCH(1,1)/ARCH(1)/EGARCH(1,1) reasonable?
I am trying to learn about volatility forecasting using three models: ARCH(1), GARCH(1, 1) and EGARCH(1, 1) using python. I wanted to know if my general procedure is correct, and specifically if my ...
- 31
2
votes
2
answers
473
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Assessing the GARCH model out-of-time
I have fitted two competing GARCH models, one GARCH(1,2) model and another EGARCH(1,1,1) both with t-distributed errors, on the ...
- 281
1
vote
1
answer
923
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Multistep ahead forecasts in GARCH equations
If my one step ahead forecasts from GARCH(1,1)-X are:
\begin{equation}
\hat{h}_{t+1} = \hat{\alpha}_0 + \hat{\alpha}_1 \hat{u}^2_t + \hat{\beta}_1 \hat{h}_t + \hat{\psi} X_t
\end{equation}
Where ...
- 43
0
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0
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416
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Forecasting VIX with GARCH(1,1)
Aim: Forecast VIX using GARCH(1,1)
Reason: I want to be able to forecast VIX on several horizons, in order to be able to forecast the SP500 index through linear regression.
Tools used: Python, ...
- 1
0
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0
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46
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Perfect in-sample size for out-sampling volatility prediction (EGARCH(1,1)
I have a few questions regarding in-sample size for volatility forecasting in EGARCH(1,1). I'm currently sitting with a dataset consisting of 1387 trading days of the S&P-500 index. I would like ...
3
votes
1
answer
393
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Is there a HAR that deals with the leverage effect?
The EGARCH is a special GARCH model that treats the leverage effect of the volatility. The HARV does not make a distinction between negative and positive returns. Is there a special HARV that deals ...
- 2,806
2
votes
1
answer
167
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forecasting hourly variance with higher resolution data available
Assume one has price data $P_{1}, P_{2}, \dots, P_{n}$ with one hour resolution and aims to forecast the variance for one hour ahead return. The first approach to try is ARCH or GARCH models. There ...
- 126
0
votes
1
answer
771
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Use of ugarchroll vs ugarchforecast: setting parameters
I would like to generate 21 day ahead forecast volatility with ugarchroll.
I know it is similar to ugarchforecast with the exception that ugarchroll is a rolling average which considers initially the ...
- 326
1
vote
0
answers
140
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Modelling volatility for higher frequency data
I'm doing some academic work on volatility forecasting. I've got 1-minute bar data. It is not clear to me what model is best suited for forecasting volatility when higher frequency data is available.
...
- 442
0
votes
2
answers
2k
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How to obtain one-step ahead forecast in Python based on GARCH?
I am trying to produce one-step ahead forecast using GARCH in Python using a fixed windows method. I ultimately want to put the code below in a for loop, but this code snippet does not perform as I ...
- 103
1
vote
1
answer
2k
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GARCH(1,1) forecast plot in R with training data
I've fit a GARCH(1,1) model in R and would like to create a plot similar to the one in this question: Is this the correct way to forecast stock price volatility using GARCH
Could someone direct me to ...
- 11
1
vote
1
answer
297
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What are some good models for stock price predictions?
For the fitting and forecasting of time-series data on stock price, the most frequent model I have heard of is ARIMA. ARIMA is actually conducting a regression of stock prices and residuals of stock ...
- 111
1
vote
2
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297
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$n$-day ahead forecast for asymmetric DCC-GARCH model
I am working on forecasting covariances with the use of MGARCH models. I was wondering if anyone knows how to implement a n-day ahead forecast of the aDCC (asymmetric DCC) model in R. The ...
- 11
3
votes
2
answers
365
views
Confidence Intervals for ARMA+GARCH forecasts
I have fitted an ARMA(1,1)+GARCH(1,1) model to my logreturns series. When it comes to my standarized error's distribution however, I have opted for a Skewed Generalized Error Distribution, because of ...
- 175