Questions tagged [volatility]
A statistical measure of the dispersion of a (financial) time series, e.g. its (annualized or regular) standard deviation
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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 ...
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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 ...
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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....
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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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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 ...
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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:
...
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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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Verifying the integrability condition of a deterministic volatility function
Suppose there is integrability condition:
\begin{equation}
\mathbb{E}\left[\int_0^T\frac{\sigma^2(t)}{T-t}dt\right]<\infty
\end{equation}
for an arbitrary volatility function. Suppose I nominate ...
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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" (...
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A volatility score not sensitive to the overall scale of the variable
I want to measure volatility in my customer base using the last 5 years of activity. That is, a total of purchases summed by year over a 5 year period.
I plan to use this formula to calculate the ...
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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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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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How to find a consistency index for a binary variable?
I am working on a project where there are 2 variables to monitor, say sales (actual) and projected sales (target).
The sales ...
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Success probability when we have expected return and volatility
I am reading Taleb "Fooled By Randomness", and the author says that a 15% return with 10% volatility translates to 93% success in a year and 50.02% success in any given second.
Could someone ...
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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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Conditional volatility and notation to express it
I'm taking a risk modelling class, and we're discussing conditional vs unconditional volatility.
We have standard volatility $\sigma = \sqrt{\mathbb{E}[r_t - \mathbb{E}(r_t)]^2}$
But what is ...
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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 ...
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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 ...
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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....
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Expectation of the realized volatility
I was reading Zhang and Wang 2023 and I have some doubts regarding it. The realized Stochastic Volatility Model is expressed as follows:
$$\begin{matrix}
y_t = \exp \big( \frac{h_t}{2} \big) \...
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Measuring Portfolio Volatility when Risk-Off
I'm trying to calculate the annualized volatility of a single-asset trading strategy that is either 100% long or 100% cash.
Imagine a risk-free asset with a guaranteed and fixed daily return of 0.1%. ...
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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 ...
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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/...
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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 ...
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GARCH model analysis using python
I have an AR(3)-GJR-GARCH(2,2,2) model. How can I test the presence of ‘leverage effects’ (i.e. asymmetric responses of the conditional variance to the positive and negative shocks) with 5% ...
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VaR from Bayesian GARCH / Quantile Estimation
I have fitted a Bayesian GARCH(1,1) model with Student $t$ innovations to some time series data, $X_1,...,X_n$ and now want to estimate Value-at-Risk (VaR) (i.e., 5% quantiles) at each times $t=1,,...,...
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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) ...
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Forecasting the conditional variance of AR(p)-GARCH(1,1) model
How can I derive forecasting formula for the conditional variance $h_{t+k}$, $k\geq1$ for AR(p)-GARCH(1,1)?
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Approximation for the Volatility of an Interest Rate
I'm a pure math student teaching myself the basics of quantitative finance, and I'm having a hard time understanding some of the approximations/nonrigorous claims that are common in applied statistics....
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Comparing models using different training sets
I try to compare the forecasting performance of several models. I do it for two situations: normal and extreme cases. My dataset set is not big.
One of the models (gradient boosting) requiers a ...
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Prediction intervals in the case of changing variance
I derive a point estimate given value $x_0$ using an estimated linear regression as follows:
$$\hat{y_0} = x_0^T\hat{\beta}.$$
I know that a prediction interval for a given value $x_0$: $$\hat{y}_0\pm ...
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Calculate the daily standard deviation for time series (stock market) in R
I´m modeling with diffrent GARCH-Models the daily standard deviation of a stock market. That includes a rolling forecast model of the daily standard deviation. This works pretty well so far.
To ...
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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 ...
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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://...
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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=...
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Interpreting GARCH (1,1) model with external regressor in variance equation using rugarch
I run a standard GARCH (1,1) model and obtain the following results.
Thereafter, I add an external regressor in the same model and obtain the following results:
The GARCH coefficient (beta1) is zero ...
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Can the GARCH intercept be 0?
Reading the ARCH and GARCH theory I understood that
alpha_0 have to be > 0 , but when I estimate my GARCH-X(1,1) model I obtain a non significant constant, like this:
Is it a problem? How can I ...
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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 ...
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Before/After event stock price volatility regression [closed]
So for my dissertation I need to discuss the impact of presidential campaigns on stock price volatility and I need some advice on which test or methodology to use? (not very sophisticated if possible)....
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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 ...
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Should a covariate be lagged in a GARCH-X model?
I am modelling Dow Jones returns using a GARCH(1,1) model but I also want to estimate a GARCH(1,1) by inserting a covariate to check if this covariate affects the volatility in some ways. The ...
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Calculate 7day realized volatility each week for Dataframe with daily log returns
I have a dataframe consisting of daily log returns for multiple time series. I want to calculate the 7-day realized volatility for each time series column for every week. Is there a fast way to get ...
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Using an ARIMA model to output many different scenarios of future wind generation
I am looking to model potential scenarios of wind generation for next year (specifically August). I have read through the literature and decided on using an ARIMA model. I have 10 different data sets ...
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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 ...
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Aggregating Multiperiod DCC-GARCH Forecast Covariance Matrices
Say I fit a $DCC$-$GARCH(1,1)$ model to a dataset of weekly returns for four assets.
I forecast the covariance matrix for the next month (so four weekly steps ahead). This gives me four $4 \times 4$ ...
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Understanding why volatility in diffusion process $(X_t)_{t \in[0,T]}$ is identifiable/known for continuous observations, but the drift is not?
Why is it that when dealing with continuous time observations of a diffusion process $(X_t)_{t \in[0,T]}$, we say that the volatility $\sigma^2$ is "perfectly identifiable" and just usually ...
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Which raw data to include for heterogenous autoregressive (HAR) model
I constructed the realized variance of bitcoin returns per day from 8-10-2015 to today. The realized variance is calculated by taking the cumulative squared intra-day returns. 5-minute high frequency ...
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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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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 ...
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Error when forecasting volatility with GARCH model in R [closed]
I am trying to forecast volatility on four different time series which is returns of SP500, Nasdaq 100, Dow Jones and Russel 2000. the four time series consists of 3259 observation and is divided into ...
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