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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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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Time Series Modeling Question
I am trying to model the effect of volume traded on implied volatility of weekly options. I have the data for 52 weekly expiries at 5 minute intervals.
However the key insight is that each weekly run ...
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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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transition probabilities of a markov process
I have a stochastic volatility model for commodity price which follows an AR(1) process:
ln(pt ) − m = ρ (ln(pt−1) − m) + exp(σt)ut ut ∼ IID(0, 1)
σt − μ = ρσ(σt−1 − μ) + ηεt εt ∼ IID(0, 1)
...
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Difference-in-differences of standard deviation
I am hypothesizing that a certain event caused prices of commodity A to become more volatile. I obtained monthly price data for commodity A as well as a price index for a larger bucket of products ...
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GARCH fit to the residuals of AR/ARMA mean equation previously fitted
Suppose I have an ARMA (p,q) (let it be ARMA (2,2)) fitted to my original returns series and have the residuals of said ARMA model extracted.
Next, it is my understanding that I need to fit a GARCH ...
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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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Error when using eGARCH but not sGARCH in rugarch
I have implemented the basic sGarch model using the code below:
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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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Estimating Volatility in financial time series
According to Ruey S. Tsay's Analysis of Financial Time Series, the way volatility is estimated is to fit ARMA model to log-return data and then square the residuals from ARMA model. The squared ...
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How to compute loss on GARCH multi-horizon predictions vs realized time series
Suppose I have a daily financial timeseries of zero-mean returns r(t), and I fit a GARCH model.
I'm using the arch_model package which forecasts volatility by ...
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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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How do I interpret a DCC model from EViews?
How would I interpret this DCC model from EViews? I am trying to use this output to find whether bitcoin has safe haven properties in volatile markets. When I read journals it says if δ2 and δ3 are ...
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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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GARCH(1,2) out-of-time model selection (assessment)
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 ...
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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 and al (2009)* did without using built-in functions in R. What I'm struggling with is how to forecast returns for my two data samples. I've found the GARCH specs and ...
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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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egarch using rugarch package in R
Hello.
I have been trying to wrap my head around GARCH (via rugarch package) for the past week and been trying to mimic the numbers as shown at vlab nyc's website.
I have not confirmed where they get ...
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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 ...
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ARSV model estimation with (constrained) generalized method of moments in R
I am trying to perform the estimation of the following Autoregressive Stochastic Volatility model
$$
y_t=\sigma_t u_t = exp(w_t/2)u_t \\
w_t = \omega + \phi w_{t-1} + \eta_t
$$
in R via the function <...
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Can we calculate the standard deviation of a large number of average data?
I am calculating the Value at Risk (VaR Formula=Deposits Initial balance * Volatility of deposits (standard deviation of returns of the deposits) * Critical Value of a probability distribution * ...
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Long-Run Variance LRV for TGARCH and GJR-GARCH
As LRV calculation from GARCH parameters is on annual basis:
$$ LRV = \frac{\omega}{1 - \alpha - \beta} \cdot 252 $$
I wonder if it's not a composition of unconditional variance divided by the model ...
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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(...
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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 (...
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A Markov Regime-Switching GARCH with Time-Varying Transition Matrix Package in R
Does anyone know if there exists any Markov regime-switching GARCH with time-varying transition matrix package or tutorial in R? I know of the "MSGARCH" package by D. Ardia et al. but the ...
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How to measure volatility of a categorial variable?
I have a variable that is a rank of 6 categories though 12 months. The categories are S, A, B, C, D, and E. Where S is best and E is worst. The variable can change overtime, for example one ...
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Contradictory results when estimating GJR-GARCH(1,1) with rugarch package
I am using financial stock data (1588 observations, daily returns) to estimate
a GARCH(1,1) and a
GJR-GARCH(1,1) model.
A GARCH(1,1) takes the form:
$\sigma_t^2 = \omega+\alpha_1 a_{t-1}^2+\beta_1\...
