How accurate is Implied Volatility in predicting future moves?
Historical volatility of a stock is going to be based on past performance, basically its current trend.  That can be useful, but really is no indication of how it will perform in the future.  Especially with a big swing in the market. Now if you're talking about implied volatility (IV) of an options contract, that's a little different.  IV is derived from an option’s price and shows what the market “implies” about the stock’s volatility in the future. Thus it is based on the actions of active traders and market makers.  So, it gives you a bit more insight into what's going on, but at times has less to do with fundamentals. I guess a good way to think of IV based on options contracts is as an educated opinion, of the market as a whole, with regards to how much that stock could likely move over a period of time (options expiration). Also note that IV represents the potential for a stock to move, but it does not forecast direction. I don't know of any studies off the top of my head, but I'm sure there have been plenty. A change in implied volatility tells us something about what investors are thinking (or fearing) about the volatility going forward for the life of the associated option contracts (which may be short or long-lived).  IV does a good job of summarizing the information available to investors, which includes information about the past and the present. However, whether these investor views actually translate into what happens in the future is a topic of debate in the finance literature--investors do not generally know the future--there are conflicting results available.  There have been papers that show that implied volatility has predictive power in some situations, time periods, and horizons (though it is also biased) and other papers that show that it does not have statistically significant predictive power at all. The consensus last time I checked was that implied volatility is no worse than historical volatility (including methods that use trends in historical volatility to forecast where it is going) at predicting future volatility.  Whether it is significantly better and whether either reliably predicts the future is something that is not agreed on.  I take this lack of consensus as evidence that if it does predict future volatility, it does so poorly. Somewhat dated FAJ survey on the subject "How accurate is Implied Volatility in predicting future moves? How would you measure this?  If the implied volatility says that there's a 1% chance that a stock will double, and it doubles, was it ""right""?  You could also say that it says there's a 99% change that it doesn't double, so was it ""wrong""?   What you could measure is the variance of daily returns over a time period, and see how well that compares to implied volatility, but there's no way to compare IV with the absolute price movement.  If a stock goes up 0.01 each day, then the variance is 0 (the daily returns are the same each day), but over 250 the stock would go up $2.50."
The options market seems to disagree...  While the implied volatility is greater than the historical volatility.. At 23% the implied isn't much higher than the past implied-vol. I'll trust the market over the stock-twits chairman.  http://www.cboe.com/framed/IVolframed.aspx?content=http%3a%2f%2fcboe.ivolatility.com%2foptions.j%3fcontract%3dC0F1D96A-D9C7-49D2-8941-45DC1B0E0B0F&amp;sectionName=SEC_TRADING_TOOLS&amp;title=CBOE%20-%20IVolatility%20Services  ... that being said -- I (like everyone and their sister) think we break 100 and move hard to 104-105. "I'm sorry.  But no.  It is not.  Some simple microeconomic theories can be predictive *in the current system*.  But macroeconomic theories are almost never predictive and always more reminiscent of a religion.  Science must be predictive by definition.  But predictions about complex systems are notoriously dicey.  This is why your meteorologist can't predict more than a few days out.    It's because it's impossible.  The system is too complex.  It is sensitive to initial conditions which are unknown and unknowable.  And the inputs are too numerous and varied to account for everything.  But they can be accurate to within a given confidence interval, even if it does not achieve formal statistical significance.  And they can run something akin to what economists would call Monte Carlo simulations given their models.  But so far as macroeconomics go, there is no admission by many practitioners in many schools about the predictive limitations on the whole endeavor based on the complex nature of the system.  There are simply constructed theoretical frameworks, which are not predictive, but which seem to have fit certain patterns in the past that are cherry-picked to confirm a hypothesis.  If that is science, it is bad science.  This does not mean one cannot have an untested hypothesis.  Economists generally cannot set up their own experiments, after all.  And they deal in complexity and human decision, just like the other social scientists.  But economists, perhaps more so than other social scientists due to the increased mathematical skill set in the standard tool-box of the field, tend to overstate their case.  This is particularly true for those larger-named economists in the field who inevitably get hired by major media companies.  If Friedman and Galbraith were both scientists, how did they come to such widely different conclusions?    How does the University of Chicago predict and prescribe the polar opposite of U. MO St. Louis?   Basing any theory on splitting one half of Weber's theory of rationality from the other and assigning the behavioral patterns to actors already makes several cognitive leaps.  And yes, in the last few years we have had the school of behavioral economics and bounded rationality models to try to cope with this.  But it's still far from predictive.  The Austrians are certainly on some of the shakiest ground in my view.  At least Keynes' work was rigorous.  So was Marx's for that matter.  That stands in stark contrasts to the Austrians and their ilk.  But regardless, when dealing with essentially contested concepts, consensus through induction becomes the only path forward.  Empirical deduction falls off the menu.  The schools of biology and chemistry at U MO and U Chic. will not come to diametrically opposite conclusions given identical data.  The schools of economics do.  That, in and of itself, is anecdotal evidence of a severe flaw in the ""science in a very litteral sense.""  And so I stand by my statement." "I strongly suggest you read up the Option Greeks. You can be right about a stocks price movement and still not make money b/c other factors come into play from time or volatility. For a ""free"" option hedge you can look at collars. Buying puts and selling calls to offset the debit you pay for the transaction. Ex: AAPL is 115, You buy the 110 puts and sell the 120 calls. This gives you a collar around he current price. Your hedged below 110 and can still participate in upside move to 120. Also look into time value. Time decays exponentially in the last 30 days. If you are long this hurts you, if you are short(selling) this is good. Be sure to take this into account. Delta: relation of the option to the underlying stock move on a .01-1 scale, .50 is ""normal."" Deep in the money options have higher deltas. It is possible other factors can offset this delta move. This is why people will lose money on earnings plays even though they are right.  EX: Say you buy an AAPL call at 120, earnings comes out and the stock goes to 121. Even though you are ""in the money"" your contract may still have less value than what you paid because of VOLATILITY collapse. The market place knows earnings move a stock and that is factored into the price of the options expected volatility. As mentioned watch out for dividend dates. Always be aware of dividend dates and earnings dates and if your contract is going to cover one of these events. Interest rates have an effect as well but since the Fed has near 0 rates there is little impact at the present. Though this could certainly change if the fed starts raising rates. Research the Black Scholes Pricing model. Whenever you trade always think about what the other guys is thinking. Sometimes we forget their is someone else on the other side of my trade that thinks essentially the exact opposite of me. Its a zero sum game. As far as choosing strikes you can look at calculating the At THe money straddle to see if the options are ""cheap"" [stock Price * Implied Volatility (for 30, 60, 90 days Depending on your holding period)* Sq root of days to expiration] / 19 (which is sq root of days/yr) Add and subtract this number to the current stock price to give you an approximate 1 standard deviation of expected price movement. Keeping with our example. AAPL at 115, lets say your formula spits out a 6; therefore price range is expected to be 109 to 121 for the time period. Helpful for selling options, I would sell the 122  call or the 108 puts. Hope this helps. Start small and get a feel for things." If upper and Bollinger bands either converge ... or diverge ..., does that mean the market is TRENDING? No - Bollinger bands measure volatility, which is an measure of how much variation there is in the price of the instrument. It does not indicate a trend which means that the instrument tends to move in a consistent direction.  When Bollinger bands are close together, that means volatility is relatively low, and vice-versa. They can  be interpreted as signals that a stock might move in one direction or the other, but they are not a measure of directional movement. "I am strongly skeptical of this.  In fact, after reading your question, I did the following: I wrote a little program in python that ""simulates"" a stock by flipping a coin. Each time the coin comes up heads, the stock's value grows by 1. Each time the coin comes up tails, the stock's value drops by 1.  I then group, say, 50 of these steps into a ""day"", and for each day I look at opening, closing, maximum and minimum. This is then graphed in a candlestick chart.  Funny enough, those things look exactly like the charts analysts look at. Here are a few examples:    If you want to be a troll, show these to a technical analyst and ask them which of these stocks you should sell short and which of them you should buy. You can try this at home, I posted the code here and it only needs Python with a few extra packages (Numpy and Pylab, should both be in the SciPy package). In reply to a comment from JoeTaxpayer, let me add some more theory to this. My code actually performs a one-dimensional random walk. Now Joe in the comments says that an infinite number of flips should approach the zero line, but that is not exactly correct. In fact, there is a high chance to end up far from the zero line, because the expected distance from the start for a random walk with N steps is sqrt(N).  What does indeed approach the zero line is if you took a bunch of these random walks and then performed the average over those. There is, however, one important aspect in which this random walk differs from the stock market: The random walk can go down as far as it likes, whereas a stock has a bottom below which it cannot fall. Reaching this bottom means the company is bankrupt and gets removed from the market. This means that the total stock market, which we might interpret as a sum of random walks, does indeed have a bias towards upwards movement, since I'm only averaging over those random walks that don't go below a certain threshold. But you can really only benefit from this effect by being broadly diversified." In my experiences most hedge funds won't have a benchmark in their mandate and are evaluated based upon absolute returns.  Their benchmarks are generally cash + x basis points.  So, no attribution and no IR.  No experience at all with CTA's though, so not sure how things are there. This is exactly how I started, starting a simulation account on the CBOE website just to see what situation was profitable because it was all greek to me. Actually after learning the greeks, I realize that site was worse and eventually read some books and got better tools. The screenshot you have is telling you the strikes, but unfortunately they are showing you the technical name of the contract on the exchanges. For example, just like you type in AAPL to buy shares of AAPL stock, you can type in VIX1616K16E to get that one particular contract, expiration and strike. So lets break it down just by inferring, because this is what I just did with that picture: You know the current price of VIX, $17.06 Calls expiring November 16th, 2016:  What is changing? SYMBOL / YEAR / EXPIRATION DAY / STRIKE / OPTION-STYLE (?) So knowing that in the money options will be more expensive, and near the money options will be slightly cheaper, and out the money will be even cheaper, you can see what is going on, per expiration. "You are probably going to hate my answer, but... If there was an easy way to ID stocks like FB that were going to do what FB did, then those stocks wouldn't exist and do that because they would be priced higher at the IPO. The fact is there is always some doubt, no one knows the future, and sometimes value only becomes clear with time. Everyone wants to buy a stock before it rises right? It will only be worth a rise if it makes more profit though, and once it is established as making more profit the price will be already up, because why wouldn't it be? That means to buy a real winner you have to buy before it is completely obvious to everyone that it is going to make more profit in the future, and that means stock prices trade at speculative prices, based on expected future performance, not current or past performance. Now I'm not saying past and future performance has nothing in common, but there is a reason that a thousand financially oriented websites quote a disclaimer like ""past performance is not necessarily a guide to future performance"". Now maybe this is sort of obvious, but looking at your image, excluding things like market capital that you've not restricted, the PE ratio is based on CURRENT price and PAST earnings, the dividend yield is based on PAST publications of what the dividend will be and CURRENT price, the price to book is based on PAST publication of the company balance sheet and CURRENT price, the EPS is based on PAST earnings and the published number of shares, and the ROI and net profit margin in based on published PAST profits and earnings and costs and number of shares. So it must be understood that every criteria chosen is PAST data that analysts have been looking at for a lot longer than you have with a lot more additional information and experience with it. The only information that is even CURRENT is the price. Thus, my ultimate conclusive point is, you can't based your stock picks on criteria like this because it's based on past information and current stock price, and the current stock price is based on the markets opinion of relative future performance. The only way to make a good stock pick is understand the business, understand its market, and possibly understand world economics as it pertains to that market and business. You can use various criteria as an initial filter to find companies and investigate them, but which criteria you use is entirely your preference. You might invest only in profitable companies (ones that make money and probably pay regular dividends), thus excluding something like an oil exploration company, which will just lose money, and lose it, and lose some more, forever... unless it hits the jackpot, in which case you might suddenly find yourself sitting on a huge profit. It's a question of risk and preference. Regarding your concern for false data. Google defines the Return on investment (TTM) (%) as: Trailing twelve month Income after taxes divided by the average (Total Long-Term Debt + Long-Term Liabilities + Shareholders Equity), expressed as a percentage. If you really think they have it wrong you could contact them, but it's probably correct for whatever past data or last annual financial results it's based on."