How to continuously plot futures data
"Note that the series you are showing is the historical spot index (what you would pay to be long the index today), not the history of the futures quotes. It's like looking at the current price of a stock or commodity (like oil) versus the futures price.  The prompt futures quote will be different that the spot quote. If you graphed the history of the prompt future you might notice the discontinuity more. How do you determine when to roll from one contract to the other? Many data providers will give you a time series for the ""prompt"" contract history, which will automatically roll to the next expiring contract for you.  Some even provide 2nd prompt, etc. time series.  If that is not available, you'd have to query multiple futures contracts and interleave them based on the expiry rules, which should be publicly available. Also is there not a price difference from the contract which is expiring and the one that is being rolled forward to? Yes, since the time to delivery is extended by ~30 days when you roll to the next contract. but yet there are no sudden price discontinuities in the charts. Well, there are, but it could be indistinguishable from the normal volatility of the time series."
The car has software that will automatically plot a route using chargers, manage charging times and notify you via a phone app when the car has charged enough to continue your route.  Also, most superchargers are located next to a restaurant or thing to do while the car charges. Most of the US is already covered by the by network this year, but next year the network will triple in charging stations.   It's really much better than it seems, unless you are constantly driving very long distances. In my five years of Tesla ownership I have never had a problem driving between California and Texas. I'm just starting my career (I'm 21) in competitive intelligence/market and market data analysis and was wondering what kind of opportunities it holds for the future. I guess this isn't directly applicable but it does give me some insight. How have you enjoyed your career? "You are probably going to hate my answer, but... If there was an easy way to ID stocks like FB that were going to do what FB did, then those stocks wouldn't exist and do that because they would be priced higher at the IPO. The fact is there is always some doubt, no one knows the future, and sometimes value only becomes clear with time. Everyone wants to buy a stock before it rises right? It will only be worth a rise if it makes more profit though, and once it is established as making more profit the price will be already up, because why wouldn't it be? That means to buy a real winner you have to buy before it is completely obvious to everyone that it is going to make more profit in the future, and that means stock prices trade at speculative prices, based on expected future performance, not current or past performance. Now I'm not saying past and future performance has nothing in common, but there is a reason that a thousand financially oriented websites quote a disclaimer like ""past performance is not necessarily a guide to future performance"". Now maybe this is sort of obvious, but looking at your image, excluding things like market capital that you've not restricted, the PE ratio is based on CURRENT price and PAST earnings, the dividend yield is based on PAST publications of what the dividend will be and CURRENT price, the price to book is based on PAST publication of the company balance sheet and CURRENT price, the EPS is based on PAST earnings and the published number of shares, and the ROI and net profit margin in based on published PAST profits and earnings and costs and number of shares. So it must be understood that every criteria chosen is PAST data that analysts have been looking at for a lot longer than you have with a lot more additional information and experience with it. The only information that is even CURRENT is the price. Thus, my ultimate conclusive point is, you can't based your stock picks on criteria like this because it's based on past information and current stock price, and the current stock price is based on the markets opinion of relative future performance. The only way to make a good stock pick is understand the business, understand its market, and possibly understand world economics as it pertains to that market and business. You can use various criteria as an initial filter to find companies and investigate them, but which criteria you use is entirely your preference. You might invest only in profitable companies (ones that make money and probably pay regular dividends), thus excluding something like an oil exploration company, which will just lose money, and lose it, and lose some more, forever... unless it hits the jackpot, in which case you might suddenly find yourself sitting on a huge profit. It's a question of risk and preference. Regarding your concern for false data. Google defines the Return on investment (TTM) (%) as: Trailing twelve month Income after taxes divided by the average (Total Long-Term Debt + Long-Term Liabilities + Shareholders Equity), expressed as a percentage. If you really think they have it wrong you could contact them, but it's probably correct for whatever past data or last annual financial results it's based on." 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 well there are many papers on power spot price prediction, for example. It depends on what level of methodology you would like to use. Linear regression is one of the basic steps, then you can continue with more advanced options. I'm a phd student studying modelling the energy price (electricity, gas, oil) as stochastic process. Regarding to your questions: 1. mildly speaking, it's really hard, due to its random nature! (http://www.dataversity.net/is-there-such-a-thing-as-predictive-analytics/)  2. well, i would ask what kind of measure of success you mean? what level of predicted interval one could find successful enough? 3. would you like me to send you some of the math-based papers on? 4. as i know, the method is to fully capture all main characteristics of the price. If it's daily power price, then these are mean-reversion effect, high volatility, spike, seasonality (weekly, monthly, yearly).  Would you tell me what kind of method you're using? Maybe we can discuss some shared ideas? Anna Okay, I think I managed to find the precise answer to this problem! It involves solving a non-linear exponential equation, but I also found a good approximate solution using the truncated Taylor series. See below for a spreadsheet you can use. Let's start by defining the growth factors per period, for money in the bank and money invested:   Now, let S be the amount ready to be invested after n+1 periods; so the first of that money has earned interest for n periods. That is,  The key step to solve the problem was to fix the total number of periods considered. So let's introduce a new variable: t = the total number of time periods elapsed So if money is ready to invest every n+1 periods, there will be t/(n+1) separate investments, and the future value of the investments will be:  This formula is exact in the case of integer t and n, and a good approximation when t and n are not integers. Substituting S, we get the version of the formula which explicitly depends on n:  Fortunately, only a couple of terms in FV depend on n, so we can find the derivative after some effort:  Equating the derivative to zero, we can remove the denominator, and assuming t is greater than zero, we can divide by the constant ( 1-G t ):  To simplify the equation, we can define some extra constants:    Then, we can define a function f(n) and write the equation as:  Note that α, β, γ, G, and R are all constant. From here there are two options: Use Newton's method or another numerical method for finding the positive root of f(n). This can be done in a number of software packages like MATLAB, Octave, etc, or by using a graphics calculator. Solve approximately using a truncated Taylor series polynomial. I will use this method here. The Taylor series of f(n), centred around n=0, is:  Truncating the series to the first three terms, we get a quadratic polynomial (with constant coefficients):  Using R, G, α, β and γ defined above, let c0, c1 and c2 be the coefficients of the truncated Taylor series for f(n):    Then,  n should be rounded to the nearest whole number. To be certain, check the values above and below n using the formula for FV. Using the example from the question: For example, I might put aside $100 every week to invest into a stock   with an expected growth of 9% p.a., but brokerage fees are $10/trade.   For how many weeks should I accumulate the $100 before investing, if I   can put it in my high-interest bank account at 4% p.a. until then? Using Newton's method to find roots of f(n) above, we get n = 14.004. Using the closed-form approximate solution, we get n = 14.082. Checking this against the FV with t = 1680 (evenly divisible by each n + 1 tested): Therefore, you should wait for n = 14 periods, keeping that money in the bank, investing it together with the money in the next period (so you will make an investment every 14 + 1 = 15 weeks.) Here's one way to implement the above solution with a spreadsheet. StackExchange doesn't allow tables in their syntax at this time, so I'll show a screenshot of the formulae and columns you can copy and paste: Formulae:  Copy and paste column A: Copy and paste column B: Results:  Remember, n is the number of periods to accumulate money in the bank. So you will want to invest every n+1 weeks; in this case, every 15 weeks. ES1 is the Bloomberg symbol for the CME E-mini S&P 500 front-month continuous contract.  ES2, ES3, etc. will likewise yield the 2nd and 3rd months.  Which exact futures contract this symbol refers to will change about once a month. There is a great 3rd party application out there that I use (I am a broker) along with my internal analysts and other 3rd party sources.  VectorVest has a LOT of technical information, but is very easy to use.  It will run any kind of screen you like, including low 52 week numbers.  (No, I don't get anything for recommending them.)