Questions tagged [volatility]

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

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37 views

Which delta-neutral construction method to pick? [closed]

There seem to be at least two methods that I know of: Classic buy option, sell underlying (or the reverse). Buy call and put (or the reverse). ... (I imagine there are others as well) In the context ...
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GARCH model using high frequency price return

In a GARCH(1,1) model for time intervals of length $k\delta$, $$h(t,t+k\delta) = c+a\,r(t-k\delta,t)^2 +b\,h(t-k\delta,t) \tag1$$ where $h(t-k\delta,t)$ is the estimated variance for the and $r(t-k\...
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32 views

transforming variables

I am would like to create a regression model with different variables however before using these variables in my regression model I would like to transform the variable in order to make it more ...
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1answer
49 views

How to get exposure to realised volatility while being vega neutral?

Let's say I am predicting the realised volatility of a stock index. I am buying or selling straddles based on whether the predicted vol is higher or lower than the implied ATM volatility for the ...
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41 views

garch(1,1) Annualised Volitility with python

I am trying to calculate the annualized Volatility of given returns for a stock with Garch(1,1) on python using a code I found online. The value I should be getting is around 27, but the value I am ...
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Why a model like GARCH is only good for daily volatility and not for intraday volatilities?

I´m currently looking to implement an intraday volatility model and I´m new at the quant world and I learned how superior is GARCH family is for daily volatilities, but in the research stage I found ...
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Behavior of Vega PnL for 6 month ATM S&P500 option

I am interpolating the vol surface for 6 months maturity from price data for S&P500 options. For this vol smile I compute the ATM strike. I then assume I can buy a call option at this strike, ...
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37 views

Trading butterfly a long vol or short vol

Sorry for what could be a naive question. When is the right time to trade a butterfly i.e. (buy 10d call and put vs sell atm all notional flat) is it when implied vols are high or low (relative to ...
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60 views

Hedging predicted volatility

Q. If you predict the volatility of the stock is 10% a year from now and current price is X dollar, how do you hedge the risk? Im not sure why I am finding this so hard. How do we use options (...
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Price volatility short-term (10 seconds) forecast

Dataset: list of all realized trades (BTCUSDT) from a certain cryptoexchange with timestamps (15 days worth of data) Problem: predict the "price volatility" (standard deviation of realized ...
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Black Scholes implied volatility [closed]

I am reading up on implied volatility and I encountered the term Black-Scholes implied volatility which I haven't heard before. What is the meaning of this term? Say I am looking at the Heston model ...
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102 views

Methods of quantifying shifts in return distributions

I am studying and running some experiments on minute-resolution asset returns and visualizing shifts in the return distribution across a moving window. The returns have fatter tails than if one used a ...
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125 views

Valuation of Variance Swap

Let say I have a Variance Swap contract which is based on daily closing prices (not the continuous variance calculation) and will last between the day interval $T_1$...
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Why are FX options vols quoted in 25RR and 25BF terms instead of by strike like credit options?

Credit options follow a quoting convention for the vols based on strike, which fits in neatly with the Black-Scholes framework. So why are FX options vols quoted in terms of 25-delta Risk Reversals ...
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61 views

forecasting hourly variance with higher resolution data available

Assume one has price data $P_{1}, P_{2}, \dots, P_{n}$ with one hour resolution and aims to forecast the variance for one hour ahead return. The first approach to try is ARCH or GARCH models. There ...
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113 views

Calculating implied volatility index

What are common methods to compute implied volatility index? One could use VIX method on other underlying. It is also easy to limit the method to 4 atm strikes. Is this a good idea though? What are ...
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28 views

Volatility forecast on SPX option expiration day

I am looking for methods and papers on forecasting SPX option at-the-money implied volatility or realized volatility within its expiration day. What are some stylized facts and forecasting methods?
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1answer
62 views

Optimal bandwidth for Realized Kernel

If I want to estimate Realized Kernel for 1 min bins, is there a way to compute the optimal bandwidth? In the reference paper: Realised Kernels in Practice: Trades and Quotes (Ole Barndoff-Nielsen et ...
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Interpretation of Volatility of Volatility (VVIX)

Recently I came across the VVIX index (also known as VIX of VIX), which represents the 30 day implied (expected) Volatility of the VIX Index. I studied CBOE's Whitepaper for the VIX, which explains ...
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Black Volatility using SABR model

As per the Wikipedia, the SABR model looks like below - $dF_t = \sigma_t \left(F_t\right)^{\beta} dW_t$ $d \sigma_t = \alpha \sigma_t d Z_t$ I have 3 questions - ...
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What are the components of VXN?

What are the exact components of VXN -- the volatility index for NASDAQ-100? The CBOE page links to the document for VIX, which clarifies the exact set of front-month near-the-money SPX options used ...
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Slippage Regression over volume and volatility

I would like to run a regression of slippage over volume and volatility, but I was thinking they are correlated, and their correlation increases throughout the day (U-shape). Would this corrupt my ...
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1answer
70 views

Modelling VWAP Slippage with HFT data

I heard that VWAP slippage (relative difference between the VWAP and the initial mid-price, $\varepsilon \ . \ \frac{P_{VWAP}-P_{arrival}}{P_{arrival}}$ with $\varepsilon = +1 \ or \ -1 $ the trade ...
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132 views

Easiest possible way to backtest a semi dynamic options strategy

I have a few options strategies Id like to backtest and I have some familiarity with Python. In particular Id like to backtest a "semi-dynamic" long vol. strategy putting on $0$ cost ...
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Why is asset volatility easier to estimate than the asset mean if it contains the mean?

It is well known that the variance of asset returns, $\sigma^2$ (whose square root is volatility), is easier to estimate than the asset mean $\mu$ (also known as expected return) because the mean of ...
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Use of ugarchroll vs ugarchforecast: setting parameters

I would like to generate 21 day ahead forecast volatility with ugarchroll. I know it is similar to ugarchforecast with the exception that ugarchroll is a rolling average which considers initially the ...
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116 views

LIBOR market model with stochastic volatility

I have read that there are 3 types of pricing models: local volatility, stochastic volatility and stochastic-local volatility models (LSV). I am now looking at interest rates exotics pricing models ...
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1answer
105 views

Do the weights of the exponentially weighted moving average (EWMA) have to sum to 1?

I am currently trying to calculate a volatility by using the EWMA model because it is said to yield better results than just using an equal weighted calculation approach. However I am a bit confused ...
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Pricing deep OTM and short expiry options with Monte Carlo methods

Is there any good variance reduction technique to price with MC deep OTM and short tenor options under Local Volatility? Can importance sampling be used? I couldn’t find any reference which does not ...
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Is variance of residuals of Markov switching GARCH model regime specific?

I'm using MSGARCH package in R. By return_data/Volatility(fit.model), I get the residuals. When I calculate the standard deviation of the residuals, it turns out that it's close to 1 for all residuals....
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BEKK Garch for time-varying beta in python

I am currently trying to analyse stocks of the S&P500 for their time-varying beta using BEKK Garch in python(jupyter). Unfortunately, I can't find any good packages and the documentation for bekk ...
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Greeks and splits

Should we adjust greeks on stock splits? Let's just ask about splits instead of reverse splits. I'm also interested how answers change if we change models/assumptions. I have some contradicting ...
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50 views

Calculate annualized returns and annualized volatility from monthly returns?

I have a dataset with monthly returns (In decimals) Jan-2008, Feb-2008 .... Dec-2008, Jan-2009 .... Dec-2017 This is what I have done, ...
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How to implement an “Active Long Volatility” Strategy?

The research paper "The Allegory of the Hawk and Serpent" describes an asset allocation referred to as the "Dragon" Portfolio, which allocates 18% to "active long volatility&...
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Volatility estimation based on a 60 days range

In Hutchinson et al: A Nonparametric Approach to Pricing and Hedging Derivative Securities Via Learning Network (1994) paper (link), to estimate $\sigma$ for the Black-Scholes formula, it says (p. 881)...
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1answer
108 views

What is volatility trading? [closed]

I have heard that there are ways that one can trade volatility with options. What option strategies can be used to do so? Are the other ways to trade volatility besides with options? If so, what ...
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3answers
149 views

Premium Currency and Volatility

Does the volatility of a Currency Pair depend on the currency in which the premium is paid? For example- will the Volatility of USDJPY change if the premium is paid in USD instead of JPY. Is there any ...
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how to interpret the results of a GARCH model fit R/python

I have got the following output from a gjrGARCH model, and I need help to interpret it in order to decide whether it is already a good model and proceed with the forecast. ...
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50 views

What's the difference between ATM Vol vs ATMF Vol?

May I ask what's the difference between At-the-money volatility vs At-the-money foward Vol?
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Price of Call & Put Spreads as Volatility Tends to Infinity in Bachelier Model

In the standard Black Scholes model, as we take volatility to infinity, the price of call spreads goes to zero and the price of put spreads goes to the difference in strikes. I ran a simulation using ...
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84 views

Implied Volatility from Heston Model

When one construct surface for Implied volatilities using Heston model from different Strike prices and Maturities, we get a surface where long dated volatilities ...
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Volatility differences

To discover trading prices of high volatility, I measure the standard deviation of two currency pairs using a simple example: ...
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“ugarch” roll from “rugarch” not working in source()

I have an automatic rolling GARCH forecast using the rugarch package in R. It is stored in a file GARCH.R. When I try to run the code using source('GARCH.R'), I get ...
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50 views

how to model the volatility of the currency exchange rate

I want to estimate/predict the volatility of the currency exchange rate. I have checked in literature a few models from very simple PPP to econometric factor model forecasting, to GARCH (for ...
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1answer
115 views

Modelling Geometric Browian Motion price model with stochastic volatility

I'd like to generate scenarios (simulate several paths of the process) for several stocks using multinomial Geometric Brownian Motion under Stochastic volatility assumption. I'm going to use it in my ...
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58 views

Volatility of multimodal distribution of returns

Take $x_1, x_2, \ldots, x_T$ to be the price of a stock, indexed by $t=1, 2, \ldots, T$. Define rate of return at time $t>W$ for a window size of $W$ to be $$r_t = \frac{x_t - x_{t-W}}{x_{t-W}}$$ ...
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VIX vs S&P: Drift in the hedging residual?

I am looking at the daily returns of the VIX index (dVIX ) and the daily returns of the S&P 500 (dS). I am running a linear regression (using 0 intercept) and get a regression slope of -1.4, i.e. ...
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76 views

Vasicek model - Bond price and volatility

Why does the bond price under the Vasicek model increase as the rate volatility increases? What is the intuition behind this?
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Modelling volatility for higher frequency data

I'm doing some academic work on volatility forecasting. I've got 1-minute bar data. It is not clear to me what model is best suited for forecasting volatility when higher frequency data is available. ...

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