A measure of the variation in price over time. Also a measure of the risk of a financial instrument.

learn more… | top users | synonyms

4
votes
0answers
198 views

What is the longest number of consecutive days that options implied volatility has stayed “extremely high” for any particular underlying?

Curious as to whether or not there is any sort of all time record. Any index, future, or stock will do. Volatility must be well above the average 1 year volatility for all periods.
4
votes
1answer
527 views

Moving window forecasting in Python

I am looking to create some code that will out-of-sample forecast the HAR-RV model. The model itself is formulated as the following, and the betas are estimated through HAC-OLS or Newey-West. ...
3
votes
2answers
311 views

Black-Scholes and Fundamentals

So basically $dS_t=\mu S_tdt+\sigma S_tdWt$ and $\mu=r-\frac12\sigma^2$ I have just been thinking about this later equation. This is very interesting because it ties together risk-free ...
3
votes
3answers
5k views

relation between asset's and equity volatilities - merton model

In terms of Merton credit risk model need to find the initial value of counterparty's assets and the volatility of the assets. Both value are not directly observable thus we have to approximate them ...
3
votes
2answers
189 views

GARCH models vs VIX

I am examining how investor sentiment affects the probability of stock market crises. I am using methodology similar to this paper https://ideas.repec.org/p/dij/wpfarg/1110304.html. VIX (equivalents) ...
3
votes
3answers
117 views

What is the rationale behind using SV models with 2 distinct volatility processes?

In the Double Heston model, there are 2 distinct volatility processes. The SDEs read \begin{align} & d{{S}_{t}}=r{{S}_{t}}dt+\sqrt{{{v}_{1}}(t)}{{S}_{t}}d{{W}_{1}}(t)+\sqrt{{{v}_{2}}(t)}{{S}_{t}}...
3
votes
2answers
517 views

When gains are made: Overnight or during trading hours? What is the connection to volatility?

Falkenblog reports an interesting finding: All of the stock returns since 1993 are from overnight returns and cross-sectionally, volatility receives a positive overnight risk premium, a negative ...
3
votes
1answer
89 views

Approximation of an option price

The value of an option in the money is 11.50 Euros. The parameters of the market are: -The price of the underlying stock: 81.4 Euros. -The volatility ofthe underlying is : 34.65 % The ...
3
votes
5answers
178 views

economic facts that causes the financial time series to be heavy tailed

When reading a tutorail on extreme value theory, I once meet the following claim ...
3
votes
2answers
104 views

GARCH variance vs standard deviation for volatility

in my series of questions related to GARCH and volatility I finally think I've got a decent grasp on it. You guys have been great help clearing up my questions for me. My next question is just a ...
3
votes
1answer
196 views

What return equation is Engle referring to in his Nobel lecture?

Engle comments in "Risk and Volatility: Econometric models and Financial Practice" that If the price of risk were constant over time, then rising conditional variances would translate linearly ...
3
votes
1answer
116 views

Time-Varying Volatility and Conditional Likelihood

Engle's comment in his seminal paper "Risk and Volatility: Econometric models and Financial Practice" mentions that I had recently worked extensively with the Kalman Filter and knew that a ...
3
votes
2answers
340 views

Transformation to reduce standard deviation without changing median

Consider some negative skew and high kurtosis return time-series $X_t$. I do not know the functional form of the pdf of $X_t$ and have about 150,000 data points. Suppose that I was to create an ...
3
votes
2answers
727 views

Backtesting VaR model violation independence

I am interested in hearing about the practitioner state of the art for testing the time independence of a VaR model (i.e. that VaR violations are independent in time). There are a number of tests in ...
3
votes
1answer
315 views

How is the formula for the VEV (VaR-equivalent volatility) in the PRIIP document derived?

The recent regulation (page 32) on PRIIPs requires to compute a VaR-equivalent volatility defined as $$\mbox{VEV}=\frac{\sqrt{3.842-2\ln \mbox{VaR}}-1.96}{\sqrt{T}}$$ Does anyone have an idea how ...
3
votes
6answers
252 views

Intuitively speaking, why do at the money options have no volga/convexity?

I was wondering if someone could give me an intuitive explanation as to why the vega of at the money options doesn't increase with volatility. I've seen some mathematical explanations showing the ...
3
votes
2answers
1k views

how do we know if the volatility which is quoted in market is Normal (Bachelier model) or log normal (Black 76)?

in market, many instruments are quoted in volatility, but how we can tell what kind of volatility is this? is it normal volatility, or lognormal volatility. because it affect our hedging positions so ...
3
votes
3answers
244 views

Could we estimate a portfolio's volatility using a GARCH on the portfolio returns?

Estimating the volatility of a portfolio is typically done by first estimating the covariance matrix. This, however, can be difficult to do accurately and predictivly. This paper gives a nice summary ...
3
votes
2answers
643 views

How to compare volatility models?

What are the most popular ways to compare volatility models? Suppose I wanted to compare the forecasting accuracy of a GARCH(1,1) model with the historic 30 day volatility. What method should I use?
3
votes
2answers
94 views

How to transform Ornstein-Uhlenbeck parameters from hourly to daily?

I get the parameters (long-term mean, volatility, mean-reversion speed, correlation) of two correlated Ornstein-Uhlenbeck processes via a likelihood estimation from hourly data. If I want to transform ...
3
votes
1answer
220 views

Find call and put volatilities using ATM, Risk reversal and Butterflies volatilities

I have to plot the implied volatility surface for EUR/USD. So, my goal is to produce something like that, from put delta 10 to call delta 10: Searching for informations, I found that I could find ...
3
votes
2answers
198 views

How to get around flat likelihood function when calibrating GBM parameters?

I want to calibrate jointly the drift mu and volatility sigma of a geometric brownian motion, $$\log(S_t) = \log(S_{t-1}) + (\mu - 0.5*\sigma^2) \Delta t + \sigma*\sqrt{\Delta t}*Z_t$$ where $Z_t$ ...
3
votes
1answer
140 views

Volatility updating rule using r

I'm trying to program a volatility updating rule using iteration. I start with the well know Heston-Nandi model where the returns dynamics are : with is iid standard normal randome variable, where ...
3
votes
2answers
149 views

Approximation of different volatilities

Suppose I model the forward swap rate lognormal $$dS_t = \sigma_{ln}S_tdW_t$$ On the other hand we could model it simply by a normal assumption: $$dS_t = \sigma_{n}dW_t$$ I would like to know if ...
3
votes
1answer
182 views

Estimating Beta from unevenly spaced price history

I have a certain non-stock asset that has 1 transaction every 1 to 8 months. I also have a price index of that class of asset compiled by another party on monthly basis. If I regress $price = \alpha' +...
3
votes
2answers
142 views

What impact does arbitrage have on realised volatility estimates?

Doing some research modeling/estimating volatility in the bitcoin market. There is quite a bit of scope for arbitrage within crypto-currency markets. Wonder if this has any impact on my volatility ...
3
votes
1answer
151 views

market completion under stochastic volatility model

Consider a stochastic volatility model. As there are two sources of risk and one asset only, this is an incomplete market. One can complete the market by considering a derivative V1 used to hedge the ...
3
votes
1answer
4k views

How to estimate a multivariate GJR or TARCH model in Eviews?

How do I specify the GARCH/TARCH equation in Eviews 6 in the variance regressors frame, if I want to find out whether there are volatilty spillovers from stock markets A and B to stock market C? P.S. ...
3
votes
2answers
161 views

How to user GARCH(p,q) to identify most volatile sector?

I would like to ask help concerning the utilization of GARCH(p,q) models to identify volatility. Suppose that I have daily closing prices of 6 financial sectors spanning several years, and I am ...
3
votes
2answers
391 views

Is there a way to adjust R PerformanceAnalytics function VaR with EWMA or GARCH method?

Is there a way to upgrade R PerformanceAnalytics function VaR with more risk sensitive approaches like EWMA or GARCH? Or is there another R package which can handle the issue?
3
votes
1answer
1k views

How to Calculate Confidence Intervals for Moving Averages Given Nonindependence?

I've plotted 30-year moving averages across time for a couple of portfolios, and I was wondering how to calculate a 95% CI for the these moving average data (i.e., across all moving average data ...
3
votes
2answers
184 views

Cross-sectional volatility vs temporal volatility

Volatility is usually defined as the standard deviation of returns, but sometimes it is calculated as the standard deviation of cross-sectional return divided by the square root of time, where other ...
3
votes
1answer
235 views

How to interpret negative asset volatility numerical results in Merton model?

I am currently working on my thesis where I discuss the Merton default probability model. I have a huge sample of US firms for the period 1990-2010. I use both numerical and complex iterative approach ...
3
votes
1answer
253 views

How would you correct a GARCH model to deal with non mean reverting volatility?

I am currently attempting to model and forecast volatility of bitcoin but have not been able to find a GARCH model that fits the data appropriately. I've used tick data sampled at 1 hour intervals ...
3
votes
1answer
245 views

Why are there different estimators for stock volatility? (realized variance, RAV, etc)

I am very confused about why different volatility estimators (RV, RAV, BPV, etc) exist. If the goal is to find the best estimator for stock volatility, and volatility is latent, how do I know which ...
3
votes
1answer
255 views

Does the correlation amongst stocks rise when stock values decline?

Is there any research on whether the correlations among stocks rise when stock indices decline? Which model could account and test for that effect ? Maybe GARCH-BEKK, or some models using copulas?
3
votes
1answer
281 views

How to use volatility to assess the accuracy of a stock market model?

Background: For a dissertation I have a multi-agent stock market model that I am using to assess different mechanisms for producing particular dynamic regimes. A key point is assessing how closely it ...
3
votes
0answers
37 views

CBOE Index Minute Data

I am doing a small research and looking for a place to purchase historical minute CBOE Index data. I am interested in: VIX - CBOE Volatility Index VVIX - CBOE VIX VOLATILITY INDEX VXV - CBOE VIX ...
3
votes
1answer
181 views

rugarch: GARCH external regressors

I'm currently playing around with the great rugarch package in R. However, I tried to test the external regressor functionality. I implemented a GARCH(1,1) process and compared it with a GARCH(0,1) ...
3
votes
1answer
101 views

What are some markets that don't have volatility smiles and why don't they?

I have read that volatility smiles didn't show up for equity options until 1987. Can some one give me an example(s) of what markets now still don't have volatility smiles and what an explanation for ...
3
votes
0answers
99 views

How can a beginner trader make use of 'volatility of volatility'

For a beginner option trader in equity options, how can he use this metric that is provided by his broker/data vendor? How can he use this metric to gain an added understanding of the option pricing/...
3
votes
0answers
263 views

Constructing Volatility Smile from American Options

My question is about best practices for reconstructing volatility smiles for a fixed tenor from American option data. For simplicity/liquidity, I am currently considering options on SPY. I am ...
3
votes
2answers
545 views

SABR model inconsistent with Black Swaption Pricing

I am confused on the following: When we price swaption, the market convention is to use Black's Model which assumes forward swap rate is following Black's model under the Q(t) measure. When we tries ...
3
votes
0answers
299 views

Does Bakshi, Kapadia and Madan (2003) VIX building approach underestimate volatility?

From a paper that shortly addresses an alternative approach to VIX-like index building: To test this approach, I've built a fake book of B&S options with constant volatility equal to $\sigma=...
3
votes
0answers
106 views

Derivation of variance of Zhou (1996) volatility estimator

Does anyone know how to derive the Variance of Bin Zhou's volatility estimator (Theorem 1) in 'High-Frequency Data and Volatility in Foreign-Exchange Rates' (1996) Zhou 1996 Any help would be ...
3
votes
0answers
756 views

Markov-Switching E-GARCH with R

I am looking for a R library for modeling a Markov-Switching E-GARCH process. In other questions at StackExchange related to GARCH models, the package rugarch is often mentionned. Do you recommend it ...
3
votes
0answers
310 views

Measuring unbiased estimator for variance with RMSE?

The root mean squared error (RMSE) is considered by some to be the best measure of how good a variance estimate is. You often see it quoted as: $RMSE=\sqrt{\frac{1}{n}\sum_{i=1}^n(\hat{\sigma_i} - \...
3
votes
0answers
495 views

Real time stock volatility

Is there any need for real time weighted volatility on a tick by tick basis for equities? If you had that access to that, what could you do with it?
3
votes
0answers
132 views

What is the relation between return volatility and return rank volatility, and how can I control the latter?

I have no experience in finance, but I've been playing around with a virtual portfolio. I'm trying to control the "rank volatility" distribution - that is, the volatility of a stock's daily rank in ...
3
votes
1answer
343 views

How to adapt a Moving Average period to market conditions?

I would like to know if there is some way to adapt the period of a moving average to market conditions like for instance the stop loss can be adapted to market conditions using the average true range. ...