All Questions
Tagged with volatility time-series
91 questions
3
votes
1
answer
386
views
GARCH(1,1) residuals are not homoskedastic
Given the following simulated GARCH(1, 1) process:
...
CommunityBot
- 1
2
votes
0
answers
33
views
How Are The Initial Value of Conditional Variance Calculated in rugarch Package?
I am trying to verify the calculations of my zero-mean GARCH(1,1) model using the rugarch library. At first I thought the initial first value of the conditional ...
- 82.8k
0
votes
0
answers
13
views
Estimating Variability or Volatility at a Point in Discrete Signal
I have a discrete signal/time series $X_t$ whose values were recorded from a sensor at a semi-regular frequency. I want to create some measure of variability/volatility/noise at each timestamp. I've ...
1
vote
0
answers
14
views
What are the pros and cons of using multivariate Filtered Historical Simulation with univariate GARCH models compared to a GARCH-DCC approach?
I am assessing the market risk of an equity portfolio and have come across an example in the MATLAB documentation that uses a multivariate Filtered Historical Simulation technique:
https://it....
- 69.5k
0
votes
2
answers
473
views
Should I include AR, MA, or ARMA in my DCC(1,1)GARCH(1,1) approach?
I know an AR, MA or generally speaking an ARMA term is included for the mean. I however can not find how to determine this for my specific application. Is there any information that can be derived ...
2
votes
0
answers
48
views
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, ...
- 1,465
2
votes
1
answer
108
views
XGBoost: does manipulating the sample make it "extrapolate"?
Suppose I want to perform time series forecasting with XGBoost. I understand that tree-based models cannot extrapolate. However, the time series I am working with is stationary (no trend or obvious ...
- 131k
0
votes
0
answers
29
views
time series squared forecast evaluation
I have a time series with very weak autocorrelations- mostly unforecastable. However, its squared values have stronger autocorrelations. Something like this:
...
- 633
3
votes
1
answer
1k
views
Expression for the unconditional variance in the EGARCH model
Given the EGARCH specification:
$\log(\sigma_t^2)=\omega + \alpha(|z_{t-1}| + E[|z_{t-1}|]) + \gamma z_{t-1} + \beta \log(\sigma_{t-1}^2)$
Is it possible to find a closed-form solution for the ...
- 10.3k
2
votes
0
answers
12
views
Interpretation of coefficients in HAR model
I'm performing the HAR model by Corsi. However, I don't quite understand what Corsi means by this in the original paper.
He writes:
It is worth noticing that if we accept the interpretation that ...
- 10.3k
0
votes
0
answers
97
views
How can I make a time series less volatile?
How can I compress a time series so that any large % changes are compressed and so that all the values fall within a a specific range?
At the moment, I have built in a rule that caps the change at 0....
- 23
2
votes
1
answer
138
views
Testing if volatility increases during ECB-Monetary Press Releases
I'm currently writing a thesis where I am trying to disect the ECB monetary press releases and their impact on the European stock market. I am using an event study methodology. Computing Daily Excess ...
- 69.5k
2
votes
1
answer
462
views
How to model volatility spillovers between some financial time series?
I am doing research to study volatility spillover effects between several financial time series $\{x_{1,t}\}, \dots, \{x_{k,t}\}$ (in my case, $k=4$). What would be the best model to study the ...
- 69.5k
1
vote
1
answer
94
views
What are some alternative approaches for forecasting time-series data when you have more underlying data available than used in the standard models?
I'm working through time-series forecasting, using models such as ETS, ARIMA, and vector autoregression as described in several texts (for example, Hyndman, R.J., & Athanasopoulos, G. (2021) ...
- 523
0
votes
1
answer
339
views
ARIMA vs GARCH: Why ARIMA can't be used to model volatility/variance like GARCH?
We can take the variance series and apply ARIMA model on it to have forecasting of volatility.
"ARIMA modelling is not the best in this circumstance because it models the mean rather than the ...
- 69.5k
0
votes
1
answer
53
views
Volatility Modelling of Equity , error in code
Dear StackExchange Community,
I am working on the codes by https://rpubs.com/rsayed/573439 to "measure the volatility spillovers and connectedness" using Diebold-Yilmaz Methodology (https://...
- 101
2
votes
1
answer
47
views
I can't find an adequate conditional model for this time series
I have the European TTF GAS spot Price time series from 31/12/1990 to 31/10/2022:
https://docs.google.com/spreadsheets/d/1Iu84-oFtv3-ybmp72IJ_s1DfcTG_TDu7/edit?usp=sharing&ouid=...
- 363
3
votes
0
answers
1k
views
Combining multiple stock time series to one data set for LSTM
I am trying to predict daily stock return volatility using an LSTM network. My data comprises price data of five different stocks, over the same time frame. My question, to which I have not found an ...
- 31
1
vote
1
answer
158
views
How to model a GARCH(1,1) with covariate?
The purpose of my study is to understand if changes in environment policy or changes in people concerns about climate change affects volatility or if they can help in the prediction of volatility. In ...
- 69.5k
4
votes
0
answers
83
views
How to pick the daily volatility component in Multiplicative Components GARCH modelling?
Recently I've been drawn to the rather interesting Multiplicative Components GARCH model for intraday volatility modelling, a draft paper written on it can be found here: Chanda, Engle, Sokalska, 2005 ...
- 282
1
vote
1
answer
661
views
ACF and volatility clustering
Can someone explain me the interpretation of volatility clustering from ACF of the absolute returns?
I got two graphs of ACF of the absolute returns (first one for daily returns, second one for weekly ...
- 1,389
1
vote
0
answers
243
views
How to determine whether to model GARCH effects over ARCH effects?
Based on my understanding, we could determine whether or not to include ARCH effects, by checking the residuals of the mean corrected model (EX: ARMA model). I know the difference between GARCH ...
- 69.5k
6
votes
2
answers
3k
views
Why is GARCH offering no predictive value?
I am playing around with GARCH models for the first time (I have a stats background but basically no experience with GARCH), trying to forecast volatility in a financial time series.
I trained a GARCH(...
- 1,571
1
vote
1
answer
82
views
Standard Deviation shows that a price series is riskier but annualized volatility computed with the log of returns shows the opposite
I apologize if this is not a smart question, but it seems contradictory that the standard deviations of two price series show that series A is riskier, but when I plot the annualized volatilities (...
- 3,897
1
vote
1
answer
376
views
Can the GARCH model predict other things than only volatility?
I was reading that ARIMA models are used to model the mean whereas GARCH models are usually used to model the conditional variance (i.e. volatility). Is it possible that the GARCH model can somehow be ...
- 69.5k
0
votes
1
answer
108
views
Forecasting volatility from serially uncorrelated (squared) returns
I am trying to estimate future volatility based on historical stock price data, using (G)ARCH models. I have computed the ACF and PACF of returns and squared returns, and none of them show signs of ...
- 69.5k
7
votes
7
answers
8k
views
Weak stationarity and ARMA-ARCH/GARCH models?
I am slightly irritated about weak stationarity in connection to ARCH/GARCH models. I do not know the answer and I am not sure about it:
The basic question is:
Do we have to test weak ...
- 69.5k
0
votes
0
answers
46
views
How to calculate 1-step ahead volatility for IGAARCh(1,1)
I need some pointers to solve this question?
Any help is appreciated.
- 11
1
vote
0
answers
414
views
The Nonlinear Asymmetric GARCH Model
I'm reading about the Nonlinear Asymmetric GARCH (NAGARCH) model. If NAGARCH(1, 1) is given by:
$${\displaystyle ~\sigma _{t}^{2}=~\omega +~\alpha (~\epsilon _{t-1}-~\theta ~\sigma _{t-1})^{2}+~\beta ~...
- 750
1
vote
1
answer
210
views
In a GJR model, is there any interpretation attributed to half of the asymmetry parameter?
I'm reading this paper by Abosedra et. al (2006), where they study the volatility of US natural gas prices.
They report the estimation from a AR(1)-GARCH(1,1) model and a AR(1)-GJR-GARCH(1,1) model as ...
- 69.5k
1
vote
1
answer
946
views
Why are ARCH/GARCH discussed like they predict the time series value itself instead of residuals?
I am fairly new to time-series analysis, I am trying to learn ARCH/GARCH models.
My understanding is that ARCH/GARCH models try to predict the residuals (difference between an observed value from DGP ...
- 69.5k
1
vote
1
answer
101
views
ARCH: How is Volatility Formulation rewritten as Residuals Formulation
I am trying to understand the concept of ARCH(1) model from this tutorial video.
From 4:15, it's explained that,
the variance of residuals (1) can be formulated as (2).
( = residual at t, =variance of ...
- 69.5k
1
vote
0
answers
59
views
Estimating stochastic volatility shock for TFP
I am trying to estimate a stochastic volatility shock for Total Factor Productivity (TFP) in a similar way to Fernandez-Villaverde and Rubio-Ramírez (2010) and Fernandez-Villaverde et al. (2011).
$$...
- 1,539
1
vote
0
answers
238
views
Modelling the Conditional Variance in a Panel Setting
I am familiar with ARCH-type models to estimate the conditional volatility of some variable of interest in a univariate setting.
I know that there also exists the concept of multivariate ARCH-type ...
- 69.5k
0
votes
1
answer
528
views
Rolling fixed window scheme for GARCH forecasting
I'm working on my bachelors thesis which mainly revolves around this paper: https://www.mdpi.com/2225-1146/4/1/3/htm
Shortly after describing the dataset in 3.1 the authors mention that they use a ...
- 69.5k
2
votes
1
answer
465
views
Out of sample ARCH forecast
I have estimated a conditional mean model for a time series:
$ x_t = x_{t-1} + \epsilon_t$.
Say I have estimated it using periods 1 to 10. I can do an out of sample conditional mean forecast by ...
- 1,129
1
vote
1
answer
1k
views
Expected Value of an ARMA-GARCH Model
An ARMA(p,q) model is given by
$ \qquad \qquad Y_t = c + \sum\limits_{i=1}^{p}\varphi_iY_{t-i}+\sum\limits_{i=1}^{q}\theta_i\varepsilon_{t-i} + \varepsilon$
with $\varepsilon_t \sim N(0,\sigma^2)$.
...
- 69.5k
1
vote
0
answers
304
views
ARCH coefficient in GARCH models
Is anyone knows to interpret ARCH Coefficient in GARCH Models ? I tried to find what is ARCH Coefficient means. Some says it's for detecting Spillover effect, Some says Volatility Clustering or ...
- 4,049
2
votes
1
answer
309
views
GARCH forecast of series (in R) seems too high
I am wondering why the mean of my model is so high leading to a high forecast of the time series data. I included a linear regression in the external regressors as there is a clear downward trend.
I ...
- 69.5k
2
votes
1
answer
3k
views
conditional volatility plot in R - GARCH
When I build a GARCH(1,1) with a skewed generalised error dist to model the innovations, with a linear trend using the fGarch library I get the following:
...
- 69.5k
1
vote
1
answer
483
views
add linear trend back into time series prediction (in R)
I have the following GARCH(1,1) model
...
- 69.5k
1
vote
0
answers
65
views
Should I standardize forecasted and actual values for Mincer Zarnowitz test?
I have some out-of-sample forecasted values of variance through some GARCH model, and now I am trying to perform a Mincer-Zarnowitz test for validity of my predictions. I first standardized both ...
- 11
1
vote
2
answers
5k
views
DCC GARCH model diagnostics in R
I have fitted a DCC GARCH model to my multivariate financial data. So, now I need to check the fitted model by using the standardized residual and its squared process. A good fitted model should have ...
14
votes
2
answers
28k
views
Measure of volatility for time series data?
I would like to calculate some measure of volatility or noise for stationary time series data. This can be a measure for a single time series or a relative measure comparing multiple time series ...
- 10.9k
5
votes
2
answers
6k
views
On forecasting, the mean squared error and realized volatility
Say one has finished estimating a correctly specified GARCH(1,1) on a daily time series and now wants to evaluate the accuracy of the one step ahead forecasts what steps or tests could one do?
I ...
2
votes
0
answers
249
views
Negative unconditional variance forecast for EGARCH model in R
I'm trying to model several financial time series and to get some forecast on them.
Considering the log-returns, I fitted an EGARCH(1,1) on the data and got the parameters, as known constraint-free ...
- 69.5k
2
votes
1
answer
70
views
How to compare volatilities of cryptocurrencies [closed]
Data: daily spread (highest price - lowest price at a given day) of Bitcoin, Ethereum and Ripple. The spread values are an absolute amount in US$.
Bitcoin is worth much more than the other two and ...
- 57.6k
1
vote
1
answer
66
views
If I have a time series forecast density that is bi-modal, does that mean that my data is heteroscedastic?
The title pretty much explains it already:
If I have enough data points that I can plot my entire forecast density and it ends up looking like this, does it mean that it is heteroscedastic and I ...
- 30k
3
votes
0
answers
193
views
How to measure/predict volatility of a time series?
Here's the problem:
We have an entity, and entity can switch ownership. The data can be seen as a time series of events (i.e. ownership change). Of course, events are labeled with epoch time.
So ...
- 153
3
votes
2
answers
789
views
Conditional Volatility of GARCH squared residuals
Motivation
I want to wrap up my own GARCH implementation
to make sure I have understood the underlying model/assumption.
to leverage forecast::auto.arima to ...
- 69.5k