Using Marine Traffic (AIS) to make stock picks?
Since you seem determined to consider this, I'd like to break down for you why I believe it is an incredibly risky proposition: 1) In general, picking individual stocks is risky. Individual stocks are by their nature not diversified assets, and a single company-wide calamity (a la Volkswagen emissions, etc.) can create huge distress to your investments. The way to mitigate this risk is of course to diversify (invest in other types of assets, such as other stocks, index funds, bonds, etc.). However, you must accept that this first step does have risks.  2) Picking stocks on the basis of financial information (called 'fundamental analysis') requires a very large amount of research and time dedication. It is one of the two main schools of thought in equity investing (as opposed to 'technical analysis', which pulls information directly from stock markets, such as price volatility). This is something that professional investors do for a living - and that means that they have an edge you do not have, unless you dedicate similar resources to this task. That information imbalance between you and professional traders creates additional risk where you make determinations 'against the grain'.  3) Any specific piece of public information (and this is public information, regardless of how esoteric it is) may be considered to be already 'factored into' public stock prices. I am a believer in market efficiency first and foremost. That means I believe that anything publically known related to a corporation ['OPEC just lowered their oil production! Exxon will be able to increase their prices!'] has already been considered by the professional traders currently buying and selling in the market. For your 'new' information to be valuable, it would need to have the ability to forecast earnings in a way not already considered by others. 4) I doubt you will be able to find the true nature of the commercial impact of a particular event, simply by knowing ship locations. So what if you know Alcoa is shipping Aluminium to Cuba - is this one of 5 shipments already known to the public? Is this replacement supplies that are covering a loss due to damaged goods previously sent? Is the boat only 1/3 full? Where this information gets valuable, is when it gets to the level of corporate espionage. Yes, if you had ship manifests showing tons of aluminum being sold, and if this was a massive 'secret' shipment about to be announced at the next shareholders' meeting, you could (illegally) profit from that information. 5) The more massive the company, the less important any single transaction is. That means the super freighters you may see transporting raw commodities could have dozens of such ships out at any given time, not to mention news of new mine openings and closures, price changes, volume reports, etc. etc. So the most valuable information would be smaller companies, where a single shipment might cover a month of revenue - but such a small company is (a) less likely to be public [meaning you couldn't buy shares in the company and profit off of the information]; and (b) less likely to be found by you in the giant sea of ship information. In summary, while you may have found some information that provides insight into a company's operations, you have not shown that this information is significant and also unknown to the market. Not to mention the risks associated with picking individual stocks in the first place. In this case, it is my opinion that you are taking on additional risk not adequately compensated by additional reward. You can. Speculating on marine traffic is more closely tied to oil trades and ocean shipping container rates, than trades on any particular companies. But companies heavily tied to ocean shipping can be ripe for speculation. The baltic dry index is created for this analytical purpose, and that information can be used as an indicator to hedge or speculate in container freight swap agreements.  The Guggenheim Shipping Exchange Traded Fund also serves as a proxy for maritime shipping profitability, but it is just a bundle of several publicly traded marine shipping companies shares.
We have custom software written in mostly C# for the long term strategies. Day trading is done on multiple platforms. Currently using ToS scripts for some futures and equities strategies to great success, and sierra charts for a few futures exclusively. I just moved into a position to work with day trading so I'm still learning more about the systems he uses That metric is not very useful for anything other than very extremely long trading periods. Most strategies or concerned with price movement over much shorter time frames, 15 mins, 1 hr, 4 hr, daily, weekly, monthly. The MA or moving average is a trend following lagging indicator used to smooth out price fluctuations and more accurately reflect the price of trading instrument such as a stock (AAPL), commodity, or currency pair. Traders are generally concerned with current market trends and price action of the instrument they are trading. As such, an extremely long MA (average daily price, over a period of 365 days) are generally not that important. "Trading on specific ECNs is the easy part - you simply specify the order routing in advance.  You are not buying or selling the *exact* same shares.  Shares are fungible - so if I simultaneously buy one share and sell another share, my net share position is zero - even if those trades don't settle until T+3.  PS ""The Nasdaq"" isn't really an exchange in the way that the CME, or other order-driven markets are.  It's really just a venue to bring market makers together.  It's almost like ""the internet,"" as in, when you buy something from Amazon, you're not buying it from ""the internet,"" but it was the internet that made your transaction with Amazon possible." This would be a nice Raspberry Pi project for Mathematica, which comes bundled free on the Raspbian OS. You can program it up and leave it running.  It's not expensive and doesn't use much power. A program to monitor stock prices or volume could be written as simply as :-  This checks the volume of trades of Oct 2014 US crude oil futures every 30 seconds and sends an email if the volume jumps by more than 100. The financial data in this example is curated from Yahoo.  If specific data is not available or not updated frequently enough, if you can find an alternative online data source it's usually possible read the data in.  For example, this is apparently real-time data :- {Crude Oil, 92.79, -0.67, -0.71%} After leaving the above program running while writing this the volume of trades has risen like so :-  Edit I just set this running on a Raspberry Pi.  I had to use gmail for the email setup as described in this post: Configuring Mathematica to send email from a notebook.  Anyway, it's working.  Hope I don't get inundated with emails. ;-) "In addition to what @George Marian said, a very large portion of trades are from computer programs trained to make trades when certain apparent patterns are observed.  Since these programs are not all designed in the same way, much of the supply and demand is a result of different algorithms with different ""opinions"" on what the stock is doing." About 10 years ago, I used to use MetaStock Trader which was a very sound tool, with a large number of indicators, but it has been a number of years since I have used it, so my comments on it will be out of date. At the time it relied upon me purchasing trading data myself, which is why I switched to Incredible Charts. I currently use Incredible Charts which I have done for a number of years, initially on the free adware service, now on the $10/year for EOD data access. There are quicker levels of data access, which might suit you, but I can't comment on these. It is web-based which is key for me. The data quality is very good and the number of inbuilt indicators is excellent. You can build search routines on the basis of specific indicators which is very effective. I'm looking at VectorVest, as a replacement for (or in addition to) Incredible Charts, as it has very powerful backtesting routines and the ability to run test portfolios with specific buy/sell criteria that can simulate and backtest a number of trading scenarios at the same time. The advantage of all of these is they are not tied to a particular broker. I'll just add this: In the best hedge funds and proprietary trading funds, stock selection is approached very scientifically in order to minimize losses/maximize gains. Researchers think of a trading idea and carefully test it to see which methods of stock selection work and how well, and finally they combine them. Every day researchers update their models based on the past performance of each indicator.  All this is just too much work to be done manually. Firms use machine learning methods to understand markets. They try to figure out what is normal, what did not happen correctly at a specific time, what will happen in future. For instance, they use deep learning networks to look at unlabeled data, and figure out what is normal and what is not. These networks can analyze an unstructured haystack of noise, and separate out the signal. This is very relevant to finance and markets because finding the patterns and anomalies in market data has been the bread and butter of traders for decades. Deep learning networks give us applications like feature learning. By 'features,' I'm referring to certain attributes in data that indicate an event. By anticipating them, we can help predict future price movements. New technology is allowing us to break new ground in managing risk, to be a-typical and manage risk in ever-improving ways. It's the responsibility of every trader, whether working for themselves or others, to take advantage of this technology to improve the collective investing experience. I care very deeply about this. I have many close friends, in the finance world and without, who have lost large amounts of money to poor trade tools and lack of transparency. I just finished a high frequency trading project. Individuals can do it, but you need a lot of capital. You can get a managed server in Times Square for $1500/month, giving you access to 90% of the US exchanges that matter, their data farms are within 3 milliseconds of distance (latency). You can also get more servers in the same building as the exchanges, if you know where to look ;) thats all I can divulge good luck As far as i understand the big companies on the stock markets have automated processes that sit VERY close to the stock feeds and continually processes these with the intention of identifying an opportunity to take multiple small lots and buy/sell them as a big lot or vice/versa and do this before a buy or sell completes, thus enabling them to intercept the trade and make a small profit on the delta. With enough of these small gains on enough shares they make big profits and with near zero chance of losing. Edit3: Regarding the usefulness of the bare number itself, it is not useful unless, for example, an employer uses that average in the computation of how many options the employer grants to the employee as part of the compensation paid. One of my employers used just such an average. What is far more common is to use two or more moving averages, of different periods, plotted on a chart.  My original response continues below... Assuming there are 252 trading days a year, the following chart does what you have done but with a moving average: AAPL on Stockcharts.com  Edit: BTW, I looked up the number of Federal holidays, there are 9. The average year has 365.2422 days. 365.2422 × 5/7 = 260.8873. Subtract 9 and you get 251.8873 trading days in the average year. So 252 is a better number for the SMA than 250 if you want to average a year.  Edit2: Here is the same chart with more than one average included: AAPL chart w/indicators "You can have a look at betabrokers. It's an simulated stock trading platform which is entirely email-based. You start with 10 000$ and you make transactions with commands in the subject line of the email (e.g. ""buy 250$ AAPL"" or ""cover 20 shares of AAPL""). It should be straightforward to add an email interface to your python script." 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Since the year of 2007, our organization has been established as an authorized channel partner for SAP Business One. SOFTCORE SOLUTIONS has a successful track record for delivering on time, within budget, state-of-the-art IT solutions to a broad range of global clientele. From single problem applications to complete turnkey operations, SoftCORE Solutions delivers solutions to your doorstep. The Company's infrastructure allows it to implement projects on multiple platforms in India or abroad. The Company is involved in evolving software solutions in the latest technology areas. Company has excellent practical hands-on experience in database related business applications. It customizes software for specific application, environment &amp; roles. SOFTCORE SOLUTIONS builds &amp; delivers solutions with high quality of commitment and expertise Yes, http://shares.telegraph.co.uk/stockscreener/ has what you're looking for. That makes sense.  So it's sort of a thoughtless process on a short time scale, but if you add up all that noise over time you could (potentially) end up with a more meaningful position than if you had valued and bet on each stock individually.  And I could see how these things could spread along a chain to unrelated stocks as well... Bloomberg is very popular, especially for researching individual companies. Market QA and Factset are popular for analyzing data. Microsoft Excel and Matlab are very common for analyzing the data.  Lots of time traders will take data from Bloomberg, Market QA, Factset or where ever, and then actually preform their analytics in Excel or Matlab. A lot of the brokers provide their own software to traders using their platform, and that software can also contain different tools to help the traders as well.