Binare Optionen & Volatilitat 2020 Beispiel fur Volatilitatsindex

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Highest Implied Volatility Options

Stocks: 15 20 minute delay (Cboe BZX is real-time), ET. Volume reflects consolidated markets. Futures and Forex: 10 or 15 minute delay, CT.

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This page shows equity options that have the highest implied volatility. Implied volatility is a theoretical value that measures the expected volatility of the underlying stock over the period of the option. It is an important factor to consider when understanding how an option is priced, as it can help traders determine if an option is fairly valued, undervalued, or overvalued. Generally speaking, traders look to buy an option when the implied volatility is low, and look to sell an option (or consider a spread strategy) when implied volatility is high.

Implied volatility is determined mathematically by using current option prices and the Black-Scholes option pricing model. The resulting number helps traders determine whether the premium of an option is „fair“ or not. It is also a measure of investors‘ predictions about future volatility of the underlying stock. Implied volatility rises when the demand for an option increases and when the market’s expectations for the underlying stock is positive. You will see higher-priced option premiums on options with high volatility. On the other hand, implied volatility decreases with a lesser demand and when the underlying stock has a negative outlook. You will see higher-priced option premiums on options with high volatility, and cheaper premiums with low volatility.

It should also be noted that earnings announcements and news releases can have an impact on implied volatility. You may see a rise in implied volatility prior to an announcement, with a sharp drop-off in implied volatility afterwards.

The page is initially sorted in descending Implied Volatility sequence. You can re-sort the page by clicking on any of the column headings.

In order to be included: For U.S. market, an option needs to have volume of greater than 500, open interest greater than 100, a last price greater than 0.10, and implied volatility greater than 60%. For Canadian market, an option needs to have volume of greater than 25, open interest greater than 1, and implied volatility greater than 60%. For both U.S. and Canadian markets. we also show only options with days till expiration greater than 14.

Options information is delayed a minimum of 15 minutes, and is updated at least once every 15-minutes through-out the day.


Available only with a Premier Membership, you can base an Options Screener off the symbols currently on the page. This lets you add additional filters to further narrow down the list of candidates.

  1. Click „Screen“ on the page and the Options Screener opens, pulling in the symbols from the Highest Implied Volatility Options page.
  2. Add additional criteria in the Screener, such as „Moneyness“, or „Delta“.
  3. View the results and if you wish, save the Screener to run again at a later date.
  4. Running a Saved Screener at a later date will always start with a new list of results. Your Saved Screener will always start with the most current set of symbols found on the Highest Implied Volatility Options page before applying your custom filters and displaying new results.
Data Updates

For pages showing Intraday views, we use the current session’s data, with new price data appear on the page as indicated by a „flash“. Stocks: 15 minute delay (Cboe BZX data for U.S. equities is real-time), ET. Volume reflects consolidated markets. Futures and Forex: 10 or 15 minute delay, CT.

The list of symbols included on the page is updated every 10 minutes throughout the trading day. However, new stocks are not automatically added to or re-ranked on the page until the site performs its 10-minute update.

Page Sort

Pages are initially sorted in a specific order (depending on the data presented). You can re-sort the page by clicking on any of the column headings in the table.


Most data tables can be analyzed using „Views.“ A View simply presents the symbols on the page with a different set of columns. Site members can also display the page using Custom Views. (Simply create a free account, log in, then create and save Custom Views to be used on any data table.)

Each View has a „Links“ column on the far right to access a symbol’s Quote Overview, Chart, Options Quotes (when available), Barchart Opinion, and Technical Analysis page. Standard Views found throughout the site include:

    Main View: Symbol, Name, Last Price, Change, Percent Change, High, Low, Volume, and Time of Last Trade.

Technical View: Symbol, Name, Last Price, Today’s Opinion, 20-Day Relative Strength, 20-Day Historic Volatility, 20-Day Average Volume, 52-Week High and 52-Week Low.

Performance View: Symbol, Name, Last Price, Weighted Alpha, YTD Percent Change, 1-Month, 3-Month and 1-Year Percent Change.

  • Fundamental View: Available only on equity pages, shows Symbol, Name, Weighted Alpha, Market Cap, P/E Ratio. Earnings Per Share, Beta, Return on Equity, and Price/Sales
  • Data Table Expand

    Unique to, data tables contain an „expand“ option. Click the „+“ icon in the first column (on the left) to „expand“ the table for the selected symbol. Scroll through widgets of the different content available for the symbol. Click on any of the widgets to go to the full page.

    Horizontal Scroll on Wide Tables

    Especially when using a custom view, you may find that the number of columns chosen exceeds the available space to show all the data. In this case, the table must be horizontally scrolled (left to right) to view all of the information. To do this, you can either scroll to the bottom of the table and use the table’s scrollbar, or you can scroll the table using your browser’s built-in scroll:

    • Left-click with your mouse anywhere on the table.
    • Use your keyboard’s left and right arrows to scroll the table.
    • Repeat this anywhere as you move through the table to enable horizontal scrolling.

    Also unique to Barchart, FlipCharts allow you to scroll through all the symbols on the table in a chart view. While viewing FlipCharts, you can apply a custom Chart Template, further customizing the way you can analyze the symbols. FlipCharts are a free tool available to Site Members.


    Download is a free tool available to Site Members. This tool will download a .csv file for the View being displayed. For dynamically-generated tables (such as a Stock or ETF Screener) where you see more than 1000 rows of data, the download will be limited to only the first 1000 records on the table. For other static pages (such as the Russell 3000 Components list) all rows will be downloaded.

    Free members are limited to 5 downloads per day, while Barchart Premier Members may download up to 100 .csv files per day.

    What is volatility?

    Or why your option prices can be less stable than a one-legged duck

    Some traders mistakenly believe that volatility is based on a directional trend in the stock price. Not so. By definition, volatility is simply the amount the stock price fluctuates, without regard for direction.

    As an individual trader, you really only need to concern yourself with two forms of volatility: historical volatility and implied volatility. (Unless your temper gets particularly volatile when a trade goes against you, in which case you should probably worry about that, too.)

    Historical volatility is defined in textbooks as “the annualized standard deviation of past stock price movements.” But rather than bore you silly, let’s just say it’s how much the stock price fluctuated on a day-to-day basis over a one-year period.

    Even if a $100 stock winds up at exactly $100 one year from now, it still could have a great deal of historical volatility. After all, it’s certainly conceivable that the stock could have traded as high as $175 or as low as $25 at some point. And if there were wide daily price ranges throughout the year, it would indeed be considered a historically volatile stock.

    Figure 1: Historical volatility of two different stocks

    This chart shows the historical pricing of two different stocks over 12 months. They both start at $100 and end at $100. However, the blue line shows a great deal of historical volatility while the black line does not.

    Implied volatility isn’t based on historical pricing data on the stock. Instead, it’s what the marketplace is “implying” the volatility of the stock will be in the future, based on price changes in an option. Like historical volatility, this figure is expressed on an annualized basis. But implied volatility is typically of more interest to retail option traders than historical volatility because it’s forward-looking.

    Where does implied volatility come from? (hint: not the stork)

    Based on truth and rumors in the marketplace, option prices will begin to change. If there’s an earnings announcement or a major court decision coming up, traders will alter trading patterns on certain options. That drives the price of those options up or down, independent of stock price movement. Keep in mind, it’s not the options’ intrinsic value (if any) that is changing. Only the options’ time value is affected.

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    The reason the options’ time value will change is because of changes in the perceived potential range of future price movement on the stock. Implied volatility can then be derived from the cost of the option. In fact, if there were no options traded on a given stock, there would be no way to calculate implied volatility.

    Implied volatility and option prices

    Implied volatility is a dynamic figure that changes based on activity in the options marketplace. Usually, when implied volatility increases, the price of options will increase as well, assuming all other things remain constant. So when implied volatility increases after a trade has been placed, it’s good for the option owner and bad for the option seller.

    Conversely, if implied volatility decreases after your trade is placed, the price of options usually decreases. That’s good if you’re an option seller and bad if you’re an option owner.

    In Meet the Greeks, you’ll learn about “vega”, which can help you calculate how much option prices are expected to change when implied volatility changes.

    How implied volatility can help you estimate potential range of movement on a stock

    Implied volatility is expressed as a percentage of the stock price, indicating a one standard deviation move over the course of a year. For those of you who snoozed through Statistics 101, a stock should end up within one standard deviation of its original price 68% of the time during the upcoming 12 months. It will end up within two standard deviations 95% of the time and within three standard deviations 99% of the time.

    Figure 2: Normal distribution of stock price

    In theory, there’s a 68% probability that a stock trading at $50 with an implied volatility of 20% will cost between $40 and $60 a year later. There’s also a 16% chance it will be above $60 and a 16% chance it will be below $40. But remember, the operative words are “in theory,” since implied volatility isn’t an exact science.

    Let’s focus on the one standard deviation move, which you can think of as a dividing line between “probable” and “not-so-probable.”

    For example, imagine stock XYZ is trading at $50, and the implied volatility of an option contract is 20%. This implies there’s a consensus in the marketplace that a one standard deviation move over the next 12 months will be plus or minus $10 (since 20% of the $50 stock price equals $10).

    So here’s what it all boils down to: the marketplace thinks there’s a 68% chance at the end of one year that XYZ will wind up somewhere between $40 and $60.

    By extension, that also means there’s only a 32% chance the stock will be outside this range. 16% of the time it should be above $60, and 16% of the time it should be below $40.

    Obviously, knowing the probability of the underlying stock finishing within a certain range at expiration is very important when determining what options you want to buy or sell and when figuring out which strategies you want to implement.

    Just remember: implied volatility is based on general consensus in the marketplace — it’s not an infallible predictor of stock movement. After all, it’s not as if Nostradamus works down on the trading floor.

    Which came first: implied volatility or the egg?

    If you were to look at an option-pricing formula, you’d see variables like current stock price, strike price, days until expiration, interest rates, dividends and implied volatility, which are used to determine the option’s price.

    Market makers use implied volatility as an essential factor when determining what option prices should be. However, you can’t calculate implied volatility without knowing the prices of options. So some traders experience a bit of “chicken or the egg” confusion about which comes first: implied volatility or option price.

    In reality, it’s not that difficult to understand. Usually, at-the-money option contracts are the most heavily traded in each expiration month. So market makers can allow supply and demand to set the at-the-money price for at-the-money option contract. Then, once the at-the-money option prices are determined, implied volatility is the only missing variable. So it’s a matter of simple algebra to solve for it.

    Once the implied volatility is determined for the at-the-money contracts in any given expiration month, market makers then use pricing models and advanced volatility skews to determine implied volatility at other strike prices that are less heavily traded. So you’ll generally see variances in implied volatility at different strike prices and expiration months.

    Figure 3: Option pricing components

    Here is all the information you need to calculate an option’s price. You can solve for any single component (like implied volatility) as long as you have all of the other data, including the price.

    But for now, let’s stay focused on the implied volatility of the at-the-money option contract for the expiration month you’re planning to trade. Because it’s typically the most heavily traded contract, the at-the-money option will be the primary reflection of what the marketplace expects the underlying stock to do in the future.

    However, watch out for odd events like mergers, acquisitions or rumors of bankruptcy. If any of these occur it can throw a wrench into the monkeyworks and seriously mess with the numbers.

    Using implied volatility to determine nearer-term potential stock movements

    As mentioned above, implied volatility can help you gauge the probability that a stock will wind up at any given price at the end of a 12-month period. But now you might be thinking, “That’s all fine and dandy, but I don’t usually trade 12-month options. How can implied volatility help my shorter-term trades?”

    That’s a great question. The most commonly traded options are in fact near-term, between 30 and 90 calendar days until expiration. So here’s a quick and dirty formula you can use to calculate a one standard deviation move over the lifespan of your option contract — no matter the time frame.

    Figure 4: Quick and dirty formula for calculating a one standard deviation move over the life of an option

    Remember: these quick and dirty calculations aren’t 100% accurate, mainly because they assume a normal distribution instead of a log normal distribution (see “A Brief Aside” below). They’re merely handy in grasping the concept of implied volatility and in getting a rough idea of the potential range of stock prices at expiration. For a more accurate calculation of what implied volatility is saying a stock might do, use Ally Invest’s Probability Calculator. This tool will do the math for you using a log normal distribution assumption.

    The theoretical world and the real world

    In order to be a successful option trader, you don’t just need to be good at picking the direction a stock will move (or won’t move), you also need to be good at predicting the timing of the move. Then, once you have made your forecasts, understanding implied volatility can help take the guesswork out of the potential price range on the stock.

    It can’t be emphasized enough, however, that implied volatility is what the marketplace expects the stock to do in theory. And as you probably know, the real world doesn’t always operate in accordance with the theoretical world.

    In the stock market crash of 1987, the market made a 20 standard deviation move. In theory, the odds of such a move are positively astronomical: about 1 in a gazillion. But in reality, it did happen. And not many traders saw it coming.

    Although it’s not always 100% accurate, implied volatility can be a useful tool. Because option trading is fairly difficult, we have to try to take advantage of every piece of information the market gives us.

    A Brief Aside: Normal Distribution vs. Log Normal Distribution

    All option pricing models assume “log normal distribution” whereas this section uses “normal distribution” for simplicity’s sake.

    As you know, a stock can only go down to zero, whereas it can theoretically go up to infinity. For example, it’s conceivable a $20 stock can go up $30, but it can’t go down $30. Downward movement has to stop when the stock reaches zero. Normal distribution does not account for this discrepancy; it assumes that the stock can move equally in either direction.

    In a log normal distribution, on the other hand, a one standard deviation move to the upside may be larger than a one standard deviation move to the downside, especially as you move further out in time. That’s because of the greater potential range on the upside than the downside.

    Unless you’re a real statistics geek, you probably wouldn’t notice the difference. But as a result, the examples in this section aren’t 100% accurate, so it’s necessary to point it out.

    Option Implied Volatility Rankings Report

    Displays equities with elevated, moderate, and subdued implied volatility for the current trading day, organized by IV percentile Rank.

    Options serve as market based predictors of future stock volatility and stock price outcomes. The level of the implied volatility of an option signals how traders may be anticipating future stock movements. By comparing implied volatility to historical averages, investors find insights into which equities may be facing higher or lower future volatility in the future. Options with elevated implied volatility are an indication that investors are anticipating the underlying equity to experience higher than normal price swings relative to its historical range. This is often due to an upcoming or impending event such as an earnings announcement, analyst conference presentation or SEC filing.

    Options with subdued implied volatility are an indication that investors may be anticipating the underlying stock to have smaller price fluctuation relative to its historical average. Since traders are pricing in lower future volatility, option premiums will be lower and the cost to hedge risk is less expensive.

    Sort the tables by clicking on specific column headings. For example, click on the IV Percentile Rank column to rank symbols from low to high (click again for high to low), and evaluate possible relationships to Important Dates such as Earnings or Events, or to underlying price changes. Search for specific equities by keyword or symbol in the search box. Click on the icons in the Symbols column to view more information on the specific stock.

    Binare Optionen & Volatilitat 2020 Beispiel fur Volatilitatsindex

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    A complete set of volatility estimators based on Euan Sinclair’s Volatility Trading.

    The original version incorporated network data acquisition from Yahoo!Finance from pandas_datareader . Yahoo! changed their API and broke pandas_datareader .

    The changes allow you to specify your own data so you’re not tied into equity data from Yahoo! finance. If you’re still using equity data, just download a CSV from and use the data.yahoo_data_helper method to form the data properly.

    Volatility estimators include:

    • Garman Klass
    • Hodges Tompkins
    • Parkinson
    • Rogers Satchell
    • Yang Zhang
    • Standard Deviation

    For each of the estimators, plot:

    • Probability cones
    • Rolling quantiles
    • Rolling extremes
    • Rolling descriptive statistics
    • Histogram
    • Comparison against arbirary comparable
    • Correlation against arbirary comparable
    • Regression against arbirary comparable

    Create a term sheet with all the metrics printed to a PDF.

    Page 1 – Volatility cones

    Page 2 – Volatility rolling percentiles

    Page 3 – Volatility rolling min and max

    Page 4 – Volatility rolling mean, standard deviation and zscore

    Page 5 – Volatility distribution

    Page 6 – Volatility, benchmark volatility and ratio###

    Page 7 – Volatility rolling correlation with benchmark

    Page 3 – Volatility OLS results

    Hit me on twitter with comments, questions, issues @jasonstrimpel

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