Questions tagged [volatility]
A statistical measure of the dispersion of a (financial) time series, e.g. its (annualized or regular) standard deviation
19 questions
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Does GARCH($p$,0) make sense at all?
I wonder if a GARCH model with only "autoregressive" terms and no lagged innovations makes sense. I have never seen examples of GARCH($p$,0) in the literature. Should the model be discarded altogether?...
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Evaluate forecasting ability of GARCH models with RMSE and MAE
I am evaluating different forecasting models and their ability to forecast index volatility during period of market turmoil, using two measurements, Root Mean Square Error and Mean Absolute Error. For ...
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The best way to compute the PRESS statistic
I would like to forecast the return volatility in a financial market. I am using symbolic regression/genetic programming to generate models with a good in-sample fit. I would like to compute ...
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Persistence in GJR-GARCH (asymmetric GARCH)
Consider the standard GARCH model:
$$ \sigma^2_t = \omega + \alpha\varepsilon^2_{t-1} + \beta\sigma^2_{t-1}.$$
The so-called persistence parameter is defined as the sum $\alpha+\beta$.
Now consider ...
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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 ...
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Remaining heteroskedasticity even after GARCH estimation
This is according to the Ljung-Box $Q$ statistic of residuals squared and ARCH-LM test. Both suggest there are ARCH effects remaining after lag 1 even after I have estimated my GARCH (1,1) model. I ...
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Has anybody ever found data where ARCH and GARCH models work?
I'm an analyst in financial and insurance fields and whenever I try to fit volatility models I obtain awful results: residuals are often non-stationary (in the unit root sense) and heteroskedastic (so ...
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Bootstrap sample with size greater than the original sample
I want to predict future returns over a 20 days horizon using an ARMA-GARCH model fitted to my data.
The goal is to estimate different risk measures like VaR or CVar.
In particular say I use AR(1) ...
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Interpreting QLIKE and MSE Loss function (Patton 2011)
In Patton (2011) the author finds that both the MSE and the QLIKE loss function are robust when used to compare rivalling volatility forecasting models, which means that using a proxy for volatility ...
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GARCH estimates differ in rugarch (R) vs. EViews
I modelled a stock's volatility using the "rugarch" package in R and Eviews.
The estimated model is GARCH(1,1).
Data is as below:
...
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How do I extract VaR estimation from DCC-GARCH model in R?
I have estimated a DCC-GARCH model in R and I need to extract the Value at Risk for an equally weighted portfolio from the estimated model.
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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 ...
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Forecasting with ARIMA and GARCH: does my plan look alright?
I have a time series containing the daily close price for a stock and I would like to perform a 10 days forecast of the volatility.
I'm trying to follow this tutorial: https://talksonmarkets.files....
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Forecasting using Copula GARCH methods
I need to replicate what Huang et al. (2009)* did without using built-in functions in R.
We have 2 assets to construct an equal-weighted portfolio. We model their volatility according to a GARCH(1, 1),...
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Chances a forecasting model exceeds/deceeds a specified threshold [closed]
I am interested in determining the confidence of a forecasting model with applications to quantitative finance.
I have the following multivariate data $X$:
\begin{align}
X(t) \sim F_{X}(t)
\end{...
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GARCH(1,1) volatility forecast looks biased, it is consistently higher than Parkinson's HL vol
I am trying to create one-step ahead forecasts for the S&P500 using a GARCH(1,1) model. I am using the rugarch package in R.
As you can see, the forecasted points are consistently higher than the ...
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DCC GARCH - specifying ARCH and GARCH parameter matrices in Stata
The command in Stata to estimate the DCC model of two variables is:
mgarch dcc ( x1 x2=, noconstant) , arch(1) garch(1) distribution(t)
$$
\begin{bmatrix}
h_{...
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Using the normal errors formula, find an iterative equation that predicts the variances of a GARCH(1,1) model
As the above states, I need to find an iterative equation that predicts the variances of a GARCH(1,1) model. Here's how I started:
Let's suppose that we have $h$ as our forecast origin. We know that ...
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Comparison of daily fitted volatility and observed absolute daily return
I am trying to estimate daily volatility of stock's return.
I have the below daily stock return data for 400 days:
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