Uni-Select (UNS.TO) Market Cap Incorrect?
Note that your link shows the shares as of March 31, 2016 while http://uniselect.com/content/files/Press-release/Press-Release-Q1-2016-Final.pdf notes a 2-for-1 stock split so thus you have to double the shares to get the proper number is what you are missing. The stock split occurred in May and thus is after the deadline that you quoted.
Many of the Bitcoin exchanges mimic stock exchanges, though they're much more rudimentary offering only simple buy/sell/cancel orders.  It's fairly normal for retail stock brokerage accounts to allow other sorts of more complex orders, where once a certain criteria is met, (the price falls below some $ threshold, or has a movement greater than some %) then your order is executed.  The space between the current buy order and the current sell order is the bid/ask spread, it's not really about timing.  Person X will buy at $100, person Y will sell at $102.  If both had a price set at $101, they would just transact.  Both parties think they can do a little bit better than the current offer.  The width of the bid/ask spread is not universal by any means.  The current highest buy order and the current lowest sell order, are both the current price.  The current quoted market price is generally the price of the last transaction, whether it's buy or sell. You, like DailyFail, don't understand why mentioning market cap and then comparing nothing more than current share prices is nonsense.   That's without getting into the many ways the person you quoted and the foundation of his economic opinions are ridiculous. On Monday, the 27th of June 2011, the XIV ETF underwent a 10:1 share split. The Yahoo Finance data correctly shows the historic price data adjusted for this split.  The Google Finance data does not make the adjustment to the historical data, so it looks like the prices on Google Finance prior to 27 June 2011 are being quoted at 10 times what they should be.   Coincidentally, the underlying VIX index saw a sudden surge on the Friday (24 June) and continued on the Monday (27 June), the date that the split took effect.  This would have magnified the bearish moves seen in the historic price data on the XIV ETF. Here is a link to an article detailing the confusion this particular share split caused amongst investors.  It appears that Google Finance was not the only one to bugger it up.  Some brokers failed to adjust their data causing a lots of confusion amongst clients with XIV holdings at the time. This is a recurring problem on Google Finance, where the historic price data often (though not always) fails to account for share splits. Basic arbitrage is the (near-)simultaneous purchasing and selling of things that are convertible.   The classic example is the international trading of equities. If someone in London wants to purchase a hundred shares of Shell for 40 GBP ea. and someone in New York wants to sell you a hundred shares of Shell for 61 USD ea., you can buy the shares from the guy in New York, sell them to the guy in London and convert your GBP back in to USD for a profit of $41.60 minus fees.  Now, if after you buy the shares in New York, the price in London goes down, you'll be left holding 100 shares of Shell that you don't want. So instead you should borrow 100 shares in London and sell them at the exact same time that you buy the shares in New York, thus keeping your net position at 0. In fact, you should also borrow 4000GBP and convert them to USD at the same time, so that exchange rate changes don't get you. I should have been clearer but my point was that the NYSE seems to be blaming third party vendors for reporting invalid test data but their own website reported the same data so it seems like there might be another issue.   Edit: Found the full comment. It seems that NASDAQ distributed the test data and other parties including the NYSE incorrectly displayed it. I can (barely) understand some third parties incorrectly reporting this data but it seems really bizarre that NYSE wouldn't know how to handle this. In order to see whether you can buy or sell some given quantity of a stock at the current bid price, you need a counterparty (a buyer) who is willing to buy the number of stocks you are wishing to offload. To see whether such a counterparty exists, you can look at the stock's order book, or level two feed. The order book shows all the people who have placed buy or sell orders, the price they are willing to pay, and the quantity they demand at that price. Here is the order book from earlier this morning for the British pharmaceutical company, GlaxoSmithKline PLC.  Let's start by looking at the left-hand blue part of the book, beneath the yellow strip. This is called the Buy side. The book is sorted with the highest price at the top, because this is the best price that a seller can presently obtain. If several buyers bid at the same price, then the oldest entry on the book takes precedence. You can see we have five buyers each willing to pay 1543.0 p (that's 1543 British pence, or £15.43) per share. Therefore the current bid price for this instrument is 1543.0. The first buyer wants 175 shares, the next, 300, and so on. The total volume that is demanded at 1543.0p is 2435 shares. This information is summarized on the yellow strip: 5 buyers, total volume of 2435, at 1543.0. These are all buyers who want to buy right now and the exchange will make the trade happen immediately if you put in a sell order for 1543.0 p or less. If you want to sell 2435 shares or fewer, you are good to go. The important thing to note is that once you sell these bidders a total of 2435 shares, then their orders are fulfilled and they will be removed from the order book. At this point, the next bidder is promoted up the book; but his price is 1542.5, 0.5 p lower than before. Absent any further changes to the order book, the bid price will decrease to 1542.5 p. This makes sense because you are selling a lot of shares so you'd expect the market price to be depressed. This information will be disseminated to the level one feed and the level one graph of the stock price will be updated. Thus if you have more than 2435 shares to sell, you cannot expect to execute your order at the bid price in one go. Of course, the more shares you are trying to get rid of, the further down the buy side you will have to go. In reality for a highly liquid stock as this, the order book receives many amendments per second and it is unlikely that your trade would make much difference. On the right hand side of the display you can see the recent trades: these are the times the trades were done (or notified to the exchange), the price of the trade, the volume and the trade type (AT means automatic trade).  GlaxoSmithKline is a highly liquid stock with many willing buyers and sellers. But some stocks are less liquid. In order to enable traders to find a counterparty at short notice, exchanges often require less liquid stocks to have market makers. A market maker places buy and sell orders simultaneously, with a spread between the two prices so that they can profit from each transaction. For instance Diurnal Group PLC has had no trades today and no quotes. It has a more complicated order book, enabling both ordinary buyers and sellers to list if they wish, but market makers are separated out at the top. Here you can see that three market makers are providing liquidity on this stock, Peel Hunt (PEEL), Numis (NUMS) and Winterflood (WINS). They have a very unpalatable spread of over 5% between their bid and offer prices. Further in each case the sum total that they are willing to trade is 3000 shares. If you have more than three thousand Dirunal Group shares to sell, you would have to wait for the market makers to come back with a new quote after you'd sold the first 3000. Quick and dirty paper but pretty interesting.. I'm not in Portfolio Management but I probably would have ended up at the modal number as well.   I don't know the subject deeply enough to answer my own question, but is the bias always toward underestimation of variance? Or is that a complex of the way the problem was set up?   Another question I have for those in investment management; Would this impact asset allocation? No, it's not even remotely accurate in the current sense. Both markets have counterparties directly executing against one another, and both have auctions. The auction mechanics are different (with NYSE's Specialist/DMM model) but during normal market hours there isn't much difference. This question is impossible answer for all markets but there are 2 more possibilities in my experience: USB is the ticker for US Bancorp. The numbers to me look like their prediction of the return for the day, I could be wrong but I think that's what it is. You can D/K a trade if it is not confirmed in a timely manner.  Also, UBS chose not to sell on the first day they waited hoping and got burned.  So that first day loss argument doesn't stand here, it can't due to a technical error.  My post states that it had to be  a large holding for some time. What really matters is of course how it compares to future prices. Are we making the assumption that the future prices will be more like the average over the last 100 years (which, by looking at your diagram, we seem to be one standard deviation or so above)? "As an exercise, I want to give this a shot.  I'm not involved in a firm that cares about liquidity so all this stuff is outside my purview.  As I understand it, it goes something like this: buy side fund puts an order to the market as a whole (all or most possibly exchanges).  HFTs see that order hit the first exchange but have connectivity to exchanges further down the pipe that is faster than the buy side fund.  They immediately send their own order in, which reaches exchanges and executes before the buy side fund's order can.  They immediately put up an ask, and buy side fund's order hits that ask and is filled (I guess I'm assuming the order was a market order from the beginning).  This is in effect the HFT front running the buy side fund.    Is this accurate?  Even if true, whether I have a genuine issue with this... I'm not sure.  Has anyone on the ""pro-HFT"" side written a solid rebuttal to Lewis and Katsuyama that has solid research behind it?" Market cap probably isn't as big of an issue as the bid/ask spread and the liquidity, although they tend to be related. The spread is likely to be wider on lesser traded ETF funds we are talking about pennies, likely not an issue unless you are trading in and out frequently. The expense ratios will also tend to be slightly higher again not a huge issue but it might be a consideration. You are unlikely to make up the cost of paying the commission to buy into a larger ETF any time soon though. Why is it OK for companies to lose all of our personal information with absolutely no penalties?  If the government fined these companies a dollar per SS number lost you bet your ass they'd start actually paying attention to security for a change.