How is the price of VXX determined?
"Generally, ETFs work on the basis that there exists a pair of values that can be taken at any moment in time: A Net Asset Value of each share in the fund and a trading market price of each share in the fund.  It may help to picture these in baskets of about 50,000 shares for the creation/redemption process. If the NAV is greater than the market price, then arbitrageurs will buy up shares at the market price and do an ""in-kind"" transaction that will be worth the NAV value that the arbitrageurs could turn around and sell for an immediate profit. If the market price is greater than the NAV, then the arbitrageurs will buy up the underlying securities that can be exchanged ""in-kind"" for shares in the fund that can then be sold on the market for an immediate profit. What is the ETF Creation/Redemption Mechanism? would be a source on this though I imagine there are others. Now, in the case of VXX, there is something to be said for how much trading is being done and what impact this can have. From a July 8, 2013 Yahoo Finance article: At big option trade in the iPath S&P 500 VIX Short-Term Futures Note   is looking for another jump in volatility.  More than 250,000 VXX options have already traded, twice its daily   average over the last month. optionMONSTER systems show that a trader   bought 13,298 August 26 calls for the ask price of $0.24 in volume   that was 6 times the strike's previous open interest, clearly   indicating new activity. Now the total returns of the ETF are a combination of changes in share price plus what happens with the distributions which could be held as cash or reinvested to purchase more shares."
It's done by Opening Auction (http://www.advfn.com/Help/the-opening-auction-68.html): The Opening Auction Between 07.50 and   a random time between 08.00 and   08.00.30, there will be called an auction period during which time,   limit and market orders are entered   and deleted on the order book. No   order execution takes place during   this period so it is possible that the   order book will become crossed. This   means that some buy and sell orders   may be at the same price and some buy   orders may be at higher prices than   some sell orders. At the end of the random start period,   the order book is frozen temporarily   and an order matching algorithm is   run. This calculates the price at   which the maximum volume of shares in   each security can be traded. All   orders that can be executed at this   price will be filled automatically,   subject to price and priorities. No   additional orders can be added or   deleted until the auction matching   process has been completed. The opening price for each stock will   be either a 'UT' price or, in the   event that there are no transactions   resulting form the auction, then the   first 'AT' trade will be used. *Volatility and the VIX can be very tricky to trade.  In particular, going out longer than a month can result in highly surprising outcomes because the VIX is basically always a one month snapshot, even when the month is out in the future. Thanks for the reply.  These are good points. I didn't think about the fact that they essentially control the price at that point. Especially with a contract agreement.   I decided to not go with an exclusive selling rights deal. Too much market potential to restrict myself. You're correct. The VIX price is calculated based on the price of all of SPX options which are expiring (IIRC 2) weeks after the expiration of that VIX contract. It's an index measuring implied vol not realized vol.  VIX futures/options are calculated slightly differently than the VIX index. VXX VZX XVIZ and there are plenty others correlated to market volatility if you want the wildest hedge, use VXX, it is also the most liquid According to Active Equity Management by Zhou and Jain: When a stock pays dividend, the adjusted price in Yahoo makes the following adjustment: Let T be the ex-dividend date (the first date that the buyers of a stock will not receive the dividend) and T-1 be the last trading day before T. All prices before T are adjusted by a multiplier (C_{T-1} - d_T)/C_{T-1}, where C_{T-1} is the close price at T-1 and d_T is the dividend per share. This, of course means that the price before T decreases. Buy some pits for xiv in October if you want to piggy back. Options pretty cheap right now.  Not sure if xiv has options, but if vix spikes, xiv will tank almost 1 for 1 negative relationship. Chart both of them over time to see the relationship. "Assuming you are executing your order on a registered exchange by a registered broker, your order will be filled at the best bid price available.  This is because brokers are legally obliged to get the best price available. For example, if the market is showing a bid of 49.99 and an offer of 50.01 and you submit an order to offer 1000 shares at 5.00, your order will be filled at 49.99.  This is assuming the existing bids are for enough shares to fill all of the 1000 shares being offered.  If the share you are offering lacks the necessary liquidity to fill the order - i.e., the 49.99 bid is for less than 1000 shares and the ""level two"" bids are not enough to fill the remaining shares, then the order would be posted in the market as an offer to sell the balance (1000 - shares filled at 49.99 and those filled at level two bids) at 5.00.   I'm pretty sure that the scenario you are describing would be described as market manipulation and it would be against the law." You're realizing the perils of using a DCF analysis.  At best, you can use them to get a range of possible values and use them as a heuristic, but you'll probably find it difficult to generate a realistic estimate that is significantly different than where the price is already. Why would you regress prices?  Correlation should alway be based on returns. Daily return correlation is around 0.8 last I checked. Of course this is backward looking. Correlation of VIX to next month returns is pretty low. I haven't checked shorter timeframes though. In most circumstances prices do not change on a daily basis on most goods and services, and just because inflation is high does not mean all prices of every good and service has to increase over the short term.  Prices are determined by costs of doing business, manufacturing costs and wage growth, and by competition.  For example, if one product has very little competition and costs to produce it have gone up, then the seller might increase prices by 10% to cover their cost of buying the goods off the manufacturer, whilst another product may have plenty of competition, the seller has sourced a new manufacturer from overseas with lower manufacturing costs, they might lower their selling costs by 5% to better compete and increase their sales. Inflation figures are calculated from a set basket of goods and services, and if inflation increases it does not mean that all prices in that basket have gone up, only that the aggregate for the whole basket of goods and services has gone up since the last inflation figures were calculated. As the commenters have already indicated, money market mutual funds are not guaranteed to maintain principal during all market conditions, and investments in mutual funds are not insured against loss due to market changes. That said, you can run a price search on Vanguard's website and see these results: So, despite all the economic problems since 1975, VMMXX has never traded at a price other than $1.00. Assuming cell A1 contains the number of trades: will price up to A1=100 at 17 each, and the rest at 14 each. The key is the MAX and MIN. They keep an item from being counted twice. If X would end up negative, MAX(0,x) clamps it to 0. By extension, if X-100 would be negative, MAX(0, X-100) would be 0 -- ie: that number doesn't increase til X>100. When A1=99, MIN(a1,100) == 99, and MAX(0,a1-100) == 0. When A1=100, MIN(a1,100) == 100, and MAX(0,a1-100) == 0. When A1=101, MIN(a1,100) == 100, and MAX(0,a1-100) == 1. Of course, if the 100th item should be $14, then change the 100s to 99s. "As I understand it, Implied Volatility represents the expected gyrations of an options contract over it's lifetime.  No, it represents that expected movement of the underlying stock, not the option itself.  Yes, the value of the option will move roughly in the same direction the value of the stock, but that's not what IV is measuring. I even tried staring at the math behind the Options pricing model to see if that could make more sense for me but that didn't help. That formula is correct for the Black-Scholes model - and it is not possible (or at least no one has done it yet) to solve for s to create a closed-form equation for implied volatility.  What most systems do to calculate implied volatility is plug in different values of s (standard deviation) until a value for the option is found that matches the quoted market value ($12.00 in this example).  That's why it's called ""implied"" volatility - the value is implied from market prices, not calculated directly. The thing that sticks out to me is that the ""last"" quoted price of $12 is outside of the bid-ask spread of $9.20 to $10.40, which tells me that the underlying stock has dropped significantly since the last actual trade.   If the Implied Vol is calculated based on the last executed trade, then whatever algorithm they used to solve for a volatility that match that price couldn't find a solution, which then choose to show as a 0% volatility.   In reality, the volatility is somewhere between the two neighbors of 56% and 97%, but with such a short time until expiry, there should be very little chance of the stock dropping below $27.50, and the value of the option should be somewhere around its intrinsic value (strike - stock price) of $9.18." Former software developer at an insurance company here (not State Farm though). All of the above answers are accurate and address how the business analysts come up with factors on which to rate your quote. I wanted to chime in on the software side here; specifically, what goes into actually crunching those numbers to produce an end result. In my experience, business analysts provide the site developers with a spreadsheet of base rates and factors, which get imported into a database. When you calculate a quote, the site starts by taking your data, and finding the appropriate base rate to start with (usually based on vehicle type, quote type (personal/commercial/etc.) and garaging zip code for the US). The appropriate factors are then also pulled, and are typically either multiplicative or additive relative to the base rate. The most 'creative' operation I've seen other than add/multiply was a linear interpolation to get some kind of gradient value, usually based on the amount of coverage you selected. At this point, you could have upwards of twenty rating factors affecting your base rate: marriage status, MVR reports, SR-22; basically, anything you might've filled into your application. In the case of MVR reports specifically, we'd usually verify your input against an MVR providing service to check that you didn't omit any violations, but we wouldn't penalize for lying about it...we didn't get that creative :) Then we'd apply any fees and discounts before spitting out the final number. With all that said, these algorithms that companies apply to calculate quotes are confidential as far as I'm aware, insofar as they don't publish those steps anywhere for the public to access. The type of algorithm used could even vary based on the state you live in, or really just when the site code is arbitrarily updated to use a new rating system. Underwriters and agents might have access to company-specific rating tables, so they might have more insight at the company level.  In short, if there's an equation out there being used to calculate your rate, it's probably a huge string of multiplications with some base rate additions and linear interpolations peppered in, based on factors (and base rates) that aren't readily publicized. Your best bet is to not go through the site at all and talk to a State Farm agent about agency-specific practices if you're really curious about the numbers.