Historical data files for NYSE/NASDAQ daily open/close price data?
I think Infochimps has what you are looking for: NYSE and NASDAQ. Another possibly more flexible option is Yahoo finance here is an example for the dow.. http://finance.yahoo.com/q/hp?s=%5EDJI&a=9&b=1&c=1928&d=3&e=10&f=2012&g=d&z=66&y=0 Some of the individual stocks you can dl directly to a spreadsheet (not sure why this isn't offer for indexs but copy and paste should work). http://finance.yahoo.com/q/hp?s=ACTC.OB+Historical+Prices
"You cannot determine this solely by the ticker length. However, there are some conventions that may help steer you there. Nasdaq has 2-4 base letters BATS has 4 base letters NYSE equity securities have 1-4 base letters. NYSE Mkt (formerly Amex) have 1-4 base letters. NYSE Arca has 4 base letters OTC has 4 base letters. Security types other than equities may have additional letters added, and each exchange (and data vendors) have different conventions for how this is handled. So if you see ""T"" for a US-listed security it would be only be either NASDAQ, NYSE or NYSE Mkt. If you see ""ANET"" then you cannot tell which exchange it is listed on.  (In this case, ANET Arista Networks is actually a NYSE stock). For some non-equity security types, such as hybrids, and debt instruments, some exchanges add ""P"" to the end for ""preferreds"" (Nasdaq and OTC) and NYSE/NYSE Mkt have a variety of methods (including not adding anything) to the ticker.  Examples include NYSE:TFG, NYSEMkt:IPB, Nasdaaq: AGNCP, Nasdaq:OXLCN.  It all becomes rather confusing given the changes in conventions over the years. Essentially, you require data that provides you with ticker, listing location and security type. The exchanges allocate security tickers in conjunction with the SEC so there are no overlaps.  eg. The same ticker cannot represent two different securities. However, tickers can be re-used.  For example, the ticker AB has been used by the following companies:" .INX (the S&P 500 index itself) does not include reinvested dividens.  You can figure total return by going to Yahoo finance, historical data. Choose the start year, and end year. You should find that data for SPY (going back to 1993) will show an adjusted close, and takes dividends into account. This isn't perfect as SPY has a .09% expense ratio, but it's better than just the S&P index. One of the more popular Dow ETF is DIA, this will let you similarly track the Dow while accounting for dividends. Google Finance and Yahoo Finance have been transitioning their API (data interface) over the last 3 months. They are currently unreliable. If you're just interested in historical price data, I would recommend either Quandl or Tiingo (I am not affiliated with either, but I use them as data sources). Both have the same historical data (open, close, high, low, dividends, etc.) on a daily closing for thousands of Ticker symbols. Each service requires you to register and get a unique token. For basic historical data, there is no charge. I've been using both for many months and the data quality has been excellent and API (at least for python) is very easy! If you have an inclination for python software development, you can read about the drama with Google and Yahoo finance at the pandas-datareader group at https://github.com/pydata/pandas-datareader. Listing on NYSE has more associated overhead costs than listing on NASDAQ.  In the case of young technology companies, this makes NASDAQ a more attractive option. Perhaps the most important factor is that NYSE requires that a company has an independent compensation committee and an independent nominating committee while NASDAQ requires only that executive compensation and nominating decisions are made by a majority of independent directors.  No self-respecting, would-be-instant-billionare tech entreprenuer is going to want some independent committee lording it over their pay packet.  Additionally, listing on NYSE requires a company have stated guidance for corporate governance while NASDAQ imposes no such requirement.  Similarly, NYSE requires a company have an internal audit team while NASDAQ imposes no such requirement.   Fees on NYSE are also a bit higher than NASDAQ, but the difference is not significant. A good rundown of the pros/cons: http://www.investopedia.com/ask/answers/062215/what-are-advantages-and-disadvantages-listing-nasdaq-versus-other-stock-exchanges.asp nice work! really enjoyed looking through your website. do you see any possible application of Machine Learning (specifically tensorflow) to this? I was thinking about building a trading bot that uses data from various APIs as a strategy just as an experiment but I'm wondering what your insights are. "Try the general stock exchange web page. http://www.aex.nl I did a quick trial myself and was able to download historical data for the AEX index for the last few years.  To get to the data, I went to the menu point ""Koersen"" on the main page and chose ""Indices"". I then entered into the sub page for the AEX index. There is a price chart window in which you have to choose the tab ""view data"". Now you can choose the date range you need and then download in a table format such as excel or csv. This should be easy to import into any software.  This is the direct link to the sub page: http://www.aex.nl/nl/products/indices/NL0000000107-XAMS/quotes" Hi guys,  This is an app I've been working on over the summer. It's my belief that a lot of people want to learn about the stock market but in the end can't because they're turned off by long walls of text you get when you Google about them/read a textbook.   I know there are other simplified solutions out there but they're not widely adopted yet and I don't think there are any (?) that were made app first.  Anyway, check it out if you can. Appreciate all feedback/comments. Everything would depend on whether the calculation is being done using the company's all-time high intraday trading price or all-time high closing price. Further, I've seen calculations using non-public pricing data, such as bid-offer numbers from market makers, although this wouldn't be kosher. The likelihood is that you're seeing numbers that were calculated using different points in time. For the record, I think Apple has overtaken Microsoft's all-time highest market cap with a figure somewhere north of $700 billion (nominal).  Here's an interesting article link on the subject of highest-ever valuations: comparison of highest market caps ever