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Volatility most frequently refers to the standard deviation of the change in value of a financial instrument with a specific time horizon. It is often used to quantify the risk of the instrument over that time period. Volatility is typically expressed in annualized terms, and it may either be an absolute number (5$) or a fraction of the initial value (5%). In probability and statistics, the standard deviation of a probability distribution, random variable, or population or multiset of values is a measure of the spread of its values. ...
Financial instruments package financial capital in readily tradeable forms - they do not exist outside the context of the financial markets. ...
For other uses, see Risk (disambiguation). ...
For a financial instrument whose price follows a Gaussian random walk, or Wiener process, the volatility increases by the square-root of time as time increases. Conceptually, this is because there is an increasing probability that the instrument's price will be farther away from the initial price as time increases. Generally, the word gaussian pertains to Carl Friedrich Gauss and his ideas. ...
In mathematics, computer science, and physics, a random walk, sometimes called a drunkards walk, is a formalisation of the intuitive idea of taking successive steps, each in a random direction. ...
In mathematics, the Wiener process, so named in honor of Norbert Wiener, is a continuous-time Gaussian stochastic process with independent increments used in modelling Brownian motion and some random phenomena observed in finance. ...
More broadly, volatility refers to the degree of (typically short-term) unpredictable change over time of a certain variable. It may be measured via the standard deviation of a sample, as mentioned above. However, price changes actually do not follow Gaussian distributions. Better distributions used to describe them actually have "fat tails" although their variance remains finite. Therefore, other metrics may be used to describe the degree of spread of the variable. As such, volatility reflects the degree of risk faced by someone with exposure to that variable. It has been suggested that this article or section be merged with Long-range dependency. ...
For other uses, see Risk (disambiguation). ...
Historical volatility is the volatility of a financial instrument based on historical returns. This phrase is used particularly when it is wished to distinguish between the actual volatility of an instrument in the past, and the current volatility implied by the market. In financial mathematics, the implied volatility of an option contract is the volatility implied by the market price of the option based on an option pricing model. ...
Volatility for market players Volatility is often viewed as a negative in that it represents uncertainty and risk. However, volatility can be good in that if one shorts on the peaks, and buys on the lows one can make money, with greater money coming with greater volatility. The possibility for money to be made via volatile markets is how short term market players like day traders hope to make money, and is in contrast to the long term investment view of buy and hold. For other uses, see Risk (disambiguation). ...
To meet Wikipedias quality standards, this article or section may require cleanup. ...
Day trading most commonly refers to the practice of either buying and then selling or selling and then buying a stock within the same day. ...
Invest redirects here. ...
Buy and hold is a long term investment strategy based on the concept that in the long run equity markets give a good rate of return despite periods of volatility or decline. ...
It is also possible to trade volatility directly, through the use of derivative securities such as options. See Volatility arbitrage. In finance, an option is a contract whereby the contract buyer has a right to exercise a feature of the contract (the option) at future date (the exercise date), and the writer (seller) has the obligation to honour the specified feature of the contract. ...
Volatility arbitrage, a. ...
Volatility versus direction Volatility does not imply direction. (This is due to the fact that all changes are squared.) An instrument that is more volatile is likely to increase or decrease in value more than one that is less volatile.
For example, a savings account has low volatility. It won't lose 50% in a year but neither will it gain 50%.
Volatility over time It's common knowledge that types of assets experience periods of high and low volatility. That is, during some periods prices go up and down quickly, while during other times, they do not seem to move at all, almost, for a long time.
Periods when prices fall quickly (a crash) are often followed by prices going down even more, or going up by an unusual amount. Also, a time when prices rise quickly (a bubble) may often be followed by prices going up even more, or going down by an unusual amount.
The converse is, 'doldrums' can last for a long time as well.
Most typically, extreme movements do not appear 'out of nowhere'; they're presaged by larger movements than usual. This is termed autoregressive conditional heteroskedasticity. Of course, whether such large movements have the same direction, or the opposite, is more difficult to say. And an increase in volatility does not always presage a further increase--the volatility may simply go back down again. In econometrics, an autoregressive conditional heteroskedasticity (ARCH) model considers the variance of the current error term to be a function of the variances of the previous time periods error terms. ...
Mathematical definition The annualized volatility σ is the standard deviation σ of the instrument's logarithmic returns in a year. It has been suggested that Rate of return on investment be merged into this article or section. ...
The generalized volatility σT for time horizon T in years is expressed as:
 .
For example, if the daily logarithmic returns of a stock have a standard deviation of 0.01 and there are 252 trading days in a year, then the time period of returns is 1/252 and annualized volatility is
 .
The monthly volatility (i.e., T = 1 / 12 of a year) would be
 .
Note that the formula used to annualize returns is not deterministic, but is an extrapolation valid for a random walk process whose steps have finite variance. Generally, the relation between volatility in different time scales is more complicated, involving the Lévy stability exponent α: In mathematics, computer science, and physics, a random walk, sometimes called a drunkards walk, is a formalisation of the intuitive idea of taking successive steps, each in a random direction. ...
 .
If α = 2 you get the Wiener process scaling relation, but some people believe α < 2 for financial activities such as stocks, indexes and so on. This was discovered by Benoît Mandelbrot, who looked at cotton prices and found that they followed a Lévy alpha-stable distribution with α = 1.7. (See New Scientist, 19 April, 1997.) Mandelbrot's conclusion is, however, not accepted by mainstream financial econometricians. Dr. Benoît B. Mandelbrot, Ph. ...
In probability theory, a Lévy skew alpha-stable distribution or just stable distribution, developed by Paul Lévy, is a probability distribution where sums of independent identically distributed random variables have the same distribution as the original. ...
See also The Beta coefficient, is a key parameter in the Capital asset pricing model (CAPM). ...
Derivatives traders at the Chicago Board of Trade. ...
Financial economics is the branch of economics concerned with resource allocation over time. ...
In financial mathematics, the implied volatility of an option contract is the volatility implied by the market price of the option based on an option pricing model. ...
For other uses, see Risk (disambiguation). ...
In probability and statistics, the standard deviation of a probability distribution, random variable, or population or multiset of values is a measure of the spread of its values. ...
Stochastic volatility models are used in the field of quantitative finance to evaluate derivative securities, such as options. ...
Volatility arbitrage, a. ...
External links - An Overview of Historical Volatility Equations The Quant Equation Archive at sitmo.com
- A Practical Guide to Forecasting Financial Market Volatility by Ser-Huang Poon
- Implied Volatility Calculator option-price.com
- Options Calculator ivolatility.com
- Graphical Volatility Calculator Options Toolbox
- Volatility Trailing Stop Tracking Automated
- Historical Volatility Spreadsheet
- The concept of volatility in theories of finance
- Asset Price Dynamics, Volatility, and Prediction a textbook by Stephen Taylor
- Analysis of daily stock price volatility
- An introduction to volatility and how it can be calculated in excel, by Dr A. A. Kotzé
- Diebold, Francis X.; Hickman, Andrew; Inoue, Atsushi & Schuermannm, Til (1996) "Converting 1-Day Volatility to h-Day Volatility: Scaling by sqrt(h) is Worse than You Think"
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