Why does Yahoo! Finance report different prices for the same index?
"Are you sure you're using the same date range? If you're using Max, then you're not, as ^FTMC goes back to 12/1/1985 while ^GDAXI only goes back to 11/1/1990. If I enter a custom date range of 11/1/1990 through 10/24/2015, I get:  and:  which, other than the dates it chose to use as labels on the x-axes, look identical. (I tried to add the URLs of the charts, but it looks like the Yahoo! URLs don't include the comparison symbol, which makes them useless for this answer. They're easy enough to construct though, just add the secondary symbol using the Comparison button and set the date range using the calendar button.) On your PS, I don't know, as you can see by my charts it even chose different labels when the date ranges were identical (although at least it didn't scale different dates differently), so maybe it's trying to be ""smart"" and choose dates based on the total amount of data available for the primary symbol, which is different in the two cases."
"The CBOE states, in an investor's guide to Interest Rate Options: The Options’ Underlying Values   Underlying values for the option contracts are   10 times the underlying Treasury yields (rates)—   13-week T-bill yield (for IRX), 5-year T-note   yield (for FVX), 10-year T-note yield (for TNX)   and 30-year T-bond yield (for TYX). The Yahoo! rate listed is the actual Treasury yield; the Google Finance and CBOE rates reflect the 10 times value.  I don't think there's a specific advantage to ""being contrary"", more likely it's a mistake, or just different." If you're interested in slower scale changes, one option is to use indexes that value a common commodity in different currencies such as the Big Mac Index.  If a Big Mac costs more in AUD but stays the same in USD, then AUD have gone up. "Note that an index fund may not be able to precisely mirror the index it's tracking. If enough many people invest enough money into funds based on that index, there may not always be sufficient shares available of every stock included in the index for the fund to both accept additional investment and track the index precisely.  This is one of the places where the details of one index fund may differ from another even when they're following the same index. IDEALLY they ought to deliver the same returns, but in practical terms they're going to diverge a bit. (Personally, as long as I'm getting ""market rate of return"" or better on average across all my funds, at a risk I'm comfortable with, I honestly don't care enough to try to optimize it further. Pick a distribution based on some stochastic modelling tools, rebalance periodically to maintain that distribution, and otherwise ignore it. That's very much to the taste of someone like me who wants the savings to work for him rather than vice versa.)" The biggest issue with Yahoo Finance is the recent change to the API in May. The data is good quality, includes both dividend/split adjusted and raw prices, but it's much more difficult to pull the data with packages like R quantmod than before.  Google is fine as well, but there are some missing data points and you can't unadjust the prices (or is it that they're all unadjusted and you can't get adjusted? I can't recall). I use Google at home, when I can't pull from Bloomberg directly and when I'm not too concerned with accuracy.  Quandl seems quite good but I haven't tried them. There's also a newer website called www.alphavantage.co, I haven't tried them yet either but their data seems to be pretty good quality from what I've heard. The companies which define the major indexes do not derive profit directly from the indexes. They are typically brokerages, which use the indexes as a tool for discussing investment options with their clients and as a publicity tool to remind the public that they are long-standing, respected firms whom we might want to consider working with. Can't mention the Dow without being reminded of Dow Jones, for example. Likewise the Standard & Poor's 500 reminds us that S&P is still going strong. There may also be some slight market manipulation opportunities in choosing which specific stocks are included in each index, but since investors rarely follow an index exactly as originally defined I'm not convinced that's significant. And the mix included in each index changes relatively rarely and has to be justified by what the index claims to be representing. So basically they are trying to see two things.  One is whether prices are correlated to each other for long periods of time as a preliminary study suggested (which would go against efficient markets hypothesis, since you could use that info to game the market) or if that result is illusory and the long term returns are close to a standard normal distribution which would follow the effiecient markets hypo.  The second thing I don't follow as well, but they're trying to solve the first thing so that they can then look at why, when they look at returns at different time scales, (1minute, one hour, one week), the model which had been proposed for these returns is not supported by the data  (the first thing). They say that the old model (Levy) says that the variability should not be the same at the different time scales, but the data suggests that it is.  So they then propose a modification of the old Levy model, and say that it would also explain the strange first result they looked at. (that prices are correlated for longer periods).  That probably doesn't make any sense, but you might have more luck by posting in /r/statistics. On NASDAQ the ^ is used to denote other securities and / to denote warrents for the underlying company. Yahoo maybe using some other designators for same. "I expect that data may be copyright. Data that's published (e.g. on a newsfeed or web site) is subject to terms of use. Standard & Poor's web site says, about the Shiller indexes, Who do I contact at S&P to license my   use of these indices?   Questions   regarding licensing the   S&P/Case-Shiller Home Price Indices   can be addressed to:  Bo Chung    Managing Director    bo_chung@standardandpoors.com,   +1.212.438.3519 As for 'recording' the information yourself, that may depend on how and where (e.g. from what source) you're recording it. If for example you tried to record prices from the Canadian MLS (Realtor's) network, they too have their own terms of use on the data they publish. Copyright laws vary from country to country (and terms of use certainly vary): for example see http://en.wikipedia.org/wiki/Feist_v._Rural which is case law about copyrighting a phone directory in the USA, and contrast that with http://en.wikipedia.org/wiki/Database_right which is European legislation. So who owns data if it is determined by free market? I guess that ""determined by free market"" means that buyers and sellers are publishing their offers-to-buy and their offers-to-sell, and I guess that the publisher (e.g. the stock exchange) has 'terms of use' about the data (the offers) that they're publishing." "For the S&P and many other indices (but not the DJIA) the index ""price"" is just a unitless number that is the result of a complicated formula.  It's not a dollar value.  So when you divide said number by the earnings/share of the sector, you're again getting just a unitless number that is incomparable to standard P-E ratios. In fact, now that I think about, it kinda makes sense that each sector would have a similar value for the number that you're computing, since each sector's index formula is presumably written to make all the index ""price""s look similar to consumers." That is true. You will not be able to reconstruct the value of the index from the data returned with this script.  I initially wrote this script because I wanted data for a lot of stocks and I wanted to perform PCA on the stocks currently included in the index. "I may be underestimating your knowledge of how exchanges work; if so, I apologize.  If not, then I believe the answer is relatively straightforward. Lets say price of a stock at time t1 is 15$ .  There are many types of price that an exchange reports to the public (as discussed below); let's say that you're referring to the most recent trade price.  That is, the last time a trade executed between a willing buyer and a willing seller was at $15.00. Lets say a significant buy order of 1M shares came in to the market. Here I believe might be a misunderstanding on your part.  I think you're assuming that the buy order must necessarily be requesting a price of $15.00 because that was the last published price at time t1.  In fact, orders can request any price they want.  It's totally okay for someone to request to buy at $10.00.  Presumably nobody will want to sell to him, but it's still a perfectly valid buy order. But let's continue under the assumptions that at t1: This makes the bid $14.99 and the ask $15.00.  (NYSE also publishes these prices.) There aren't enough people selling that stock. It's quite rare (in major US equities) for anyone to place a buy order that exceeds the total available shares listed for sale at all prices.  What I think you mean is that 1M is larger than the amount of currently-listed sell requests at the ask of $15.00. So say of the 1M only 100,000 had a matching sell order and others are waiting. So this means that there were exactly 100,000 shares waiting to be sold at the ask of $15.00, and that all other sellers currently in the market told NYSE they were only willing to sell for a price of $15.01 or higher.  If there had been more shares available at $15.00, then NYSE would have matched them. This would be a trigger to the automated system to start increasing the price. Here is another point of misunderstanding, I think.  NYSE's automated system does not invent a new, higher price to publish at this point.  Instead it simply reports the last trade price (still $15.00), and now that all of the willing sellers at $15.00 have been matched, NYSE also publishes the new ask price of $15.01.  It's not that NYSE has decided $15.01 is the new price for the stock; it's that $15.01 is now the lowest price at which anyone (known to NYSE) is willing to sell.  If nobody happened to be interested in selling at $15.01 at t1, but there were people interested in selling at $15.02, then the new published ask would be $15.02 instead of $15.01 -- not because NYSE decided it, but just because those happened to be the facts at the time. Similarly, the new bid is most likely now $15.00, assuming the person who placed the order for 1M shares did not cancel the remaining unmatched 900,000 shares of his/her order.  That is, $15.00 is now the highest price at which anyone (known to NYSE) is willing to buy. How much time does the automated system wait to increment the price, the frequency of the price change and by what percentage to increment etc. So I think the answer to all these questions is that the automated system does none of these things.  It merely publishes information about (a) the last trade price, (b) the price that is currently the lowest price at which anyone has expressed a willingness to sell, and (c) the price that is currently the highest price at which anyone has expressed a willingness to buy. ::edit:: Oh, I forgot to answer your primary question. Can we estimate the impact of a large buy order on the share price? Not only can we estimate the impact, but we can know it explicitly.  Because the exchange publishes information on all the orders it knows about, anyone tracking that information can deduce that (in this example) there were exactly 100,000 shares waiting to be purchased at $15.00.  So if a ""large buy order"" of 1M shares comes in at $15.00, then we know that all of the people waiting to sell at $15.00 will be matched, and the new lowest ask price will be $15.01 (or whatever was the next lowest sell price that the exchange had previously published)." For stock splits, let's say stock XYZ closed at 100 on February 5.  Then on February 6, it undergoes a 2-for-1 split and closes the day at 51.  In Yahoo's historical prices for XYZ, you will see that it closed at 51 on Feb 6, but all of the closing prices for the previous days will be divided by 2.  So for Feb 5, it will say the closing price was 50 instead of 100. For dividends, let's say stock ABC closed at 200 on December 18.  Then on December 19, the stock increases in price by $2 but it pays out a $1 dividend.  In Yahoo's historical prices for XYZ, you will see that it closed at 200 on Dec 18 and 201 on Dec 19.  Yahoo adjusts the closing price for Dec 19 to factor in the dividend. Why don't you look at the actual funds and etfs in question rather than seeking a general conclusion about all pairs of funds and etfs?  For example, Vanguard's total stock market index fund (VTSAX) and ETF (VTI).  Comparing the two on yahoo finance I find no difference over the last 5 years visually.  For a different pair of funds you may find something very slightly different.   In many cases the index fund and ETF will not have the same benchmark and fees so comparisons get a little more cloudy.  I recall a while ago there was an article that was pointing out that at the time emerging market ETF's had higher fees than corresponding index funds.  For this reason I think you should examine your question on a case-by-case basis.  Index fund and ETF returns are all publicly available so you don't have to guess. Should be noted that pacoverflow's answer is wrong. Yahoo back-adjusts all the previous (not current or future) values based on a cumulative adjustment factor. So if there's a dividend ex-date on December 19, Yahoo adjusts all the PREVIOUS (December 18 and prior) prices with a factor which is: 1 - dividend / Dec18Close that's just it, though - they are splitting up the 1%! and in most cases, especially vanguard, they are splitting up far less.  ETFs don't have 12b-1 fees. explaining why you're experiencing different returns for ETFs will almost certainly involve something other than their expense. again, this is especially true for vanguard. they have the cheapest ETFs around (though i think schwab beats them on a few now).  i can only guess at the full compensation structure. betterment likely earns money on cash reserves and  securities hypothecation (i guess?). they also charge a small fee from what i understand. finance is very slim these days.  i guess i'm wondering what your ultimate question is. if it's the inter corporate compensation structure, above is my best guess. if it's about performance, then we need to compare the ETFs you are looking at. if it's about the fees on funds, i think we covered that!  as an advisor, it's my experience that very specific inquiries about fees have a deeper concern. people hear a lot about being overcharged so cost is a very standard place for clients to initially look when trying to compare performance of portfolios or securities.