Google Finance: Input Parameters For Simple Moving Averages
The difference is that for the one year time frame the data is represented based on daily data and the SMA is 20 days, whilst for the 5 year timeframe the data is automatically represented as weekly data with the SMA represented by 20 weeks not 20 days anymore. This happens due to daily data on this chart being too much data to represent over a 5 year period so the data defaults to weekly data over such a long period. If the chart is represented as weekly data then any indicators will also have to be represented in weekly data. If you use a more sophisticated charting program you can actually select to see daily or weekly data over longer periods such as 5 years or more. I looked at this a little more closely but the answer Victor provided is essentially correct.  The key to look at in the google finance graph is the red labled SMA(###d) would indicate the period units are d=days.  If you change the time axis of the graph it will shift to SMA(###m) for period in minutes or SMA(###w) for period in weeks.  Hope this clears things up!
There are lots of good answers on here already.  There are actually lots of answers for this question.  Lots.  I have years of experience on the exchange feed side and there are hundreds and thousands of variables.   All of these variables are funneled into systems owned by large financial institutions (I used to manage these - and only a few companies in the world do this so not hard to guess who I work for).  Their computers then make trades based on all of these variables and equations.  There are variables as whacky as how many times was a company mentioned in an aggregate news feed down to your basic company financials.  But if there is a way to measure a company (or to just guess) there is an equation for it plugged into a super computer at a big bank. Now there are two important factors on why you see this mad dash in the morning: Now most of the rest of the day is also automated trades but by the time you are an hour into market open the computers for the most part have fulfilled their calendar buys.  Everyone else's answer is right too.  There is futures contracts that change, global exchange info changes, options expiring, basic news, whatever but all of these are amplified by the calendar day changing. I was typing up a long response and lost it to a backspace.. so, I apologize but I don't intend on rewriting it all.  You'll have to use a method called bootstrapping to get the forward rates.  Essentially you're looking at the spot rate today, and the forward rates, then filling in what must be the rate to make them equal out in the end.  Sorry I'm not more help! James Roth provides a partial solution good for stock picking but let's speed up process a bit, already calculated historical standard deviations: Ibbotson, very good collection of research papers here, examples below Books "I could not figure out a good way to make XIRR work since it does not support arrays.  However, I think the following should work for you: Insert a column at D and call it ""ratio"" (to be used to calculate your answer in column E).  Use the following equation for D3: =1+(C3-B3-C2)/C2 Drag that down to fill in the column. Set E3 to: =(PRODUCT(D$3:D3)-1)*365/(A3-A$2) Drag that down to fill in the column. Column E is now your annual rate of return." This is from Google Finance right now. You bought 1 share of Google at $67.05 while it has a current trading price of $1204.11. Now, if you bought a widget for under $70 and it currently sells for over $1200 that is quite the increase, no? Be careful of what prices you enter into a portfolio tool as some people may be able to use options to have a strike price different than the current trading price by a sizable difference. Take the gain of $1122.06 on an initial cost of $82.05 for seeing where the 1367% is coming. User error on the portfolio will lead to misleading statistics I think as you meant to put in something else, right? "I am trying to set up a formula that will find interest-rate behind first pencil sheets at car dealerships. I am not a car finance expert so I need someone who is intimate with how these loans really work.   The points of data I get at first pencil are: 1) Amount Financed 2) Period 3) Monthly Payment  The data I need to extrapolate: 1) Rate in percentile so that I can compare to my bank's offer.  I have tried this and many other stock ""find rate"" formulas with no accurate results: R=(A/P^(1/n)-1)n" As you point out, the moving average is just MA(k)t = (Pt-1 + … + Pt-k )/k and is applied in technical analysis (TA) to smooth out volatile (noise) price action. If it has any logic to it, you might want to think in terms of return series (Pt - Pt-1 / Pt-1) and you could hypothesize that prices are in fact predictable and will oscillate below and above a running moving average.  Below is a link to a study on MA trading rules, published in the Journal of Finance, with the conclusion of predictive power and abnormal returns from such strategies. As with any decision made upon historical arguments, one should be aware of structural changes and or data mining.  Simple  technical trading rules and the stochastic properties of stock  returns Brock, W., J. Lakonishok and B. Le Baron, 1992, Simple technical trading rules and the stochastic properties of stock returns, Journal of Finance, 47, 1731-64. MA rules betterthan chance in US stock market, 1897-1986 I don't know whether you are new to TA or not, but a great commercial site, with plenty of computer-generated signals is FinViz. "P/E is Price divided by Earnings Per Share (EPS). P/E TTM is Price divided by the actual EPS earned over the previous 12 months - hence ""Trailing Twelve Month"". In Forward P/E is the ""E"" is the average of analyst expectations for the next year in EPS. Now, as to what's being displayed. Yahoo shows EPS to be 1.34. 493.90/1.34 = P/E of 368.58 Google shows EPS to be 0.85. 493.40/0.85 = P/E of 580.47 (Prices as displayed, respectively) So, by the info that they are themselves displaying, it's Google, not Yahoo, that's displaying the wrong P/E. Note that the P/E it is showing is 5.80 -- a decimal misplacement from 580 Note that CNBC shows the Earnings as 0.85 as well, and correctly show the P/E as 580 http://data.cnbc.com/quotes/BP.L A quick use of a currency calculator reveals a possible reason why EPS is listed differently at yahoo. 0.85 pounds is 1.3318 dollars, currently. So, I think the Yahoo EPS listing is in dollars. A look at the last 4 quarters on CNBC makes that seem reasonable: http://data.cnbc.com/quotes/BP.L/tab/5 those add up to $1.40." "My answer is Microsoft Excel.  Google ""VBA for dummies"" (seriously) and find out if your brokerage offers an 'API'.  With a brief understanding of coding you can get a spreadsheet that is live connected to your brokers data stream.  Say you have a spreadsheet with the 1990 value of each in the first two columns (cells a1 and b1).  Maybe this formula could be the third column, it'll tell you how much to buy or sell to rebalance them.   then to iterate the rebalance, set both a2 and b2 to =C1 and drag the formula through row 25, one row for each year.  It'll probably be a little more work than that, but you get the idea." As @littleadv and @DumbCoder point out in their comments above, Bloomberg Terminal is expensive for individual investors.  If you are looking for a free solution I would recommend Yahoo and Google Finance. On the other side, if you need more financial metrics regarding historic statements and consensus estimates, you should look at the iPad solution from Worldcap, which is not free, but significantly cheaper then Bloomberg and Reuters. Disclosure: I am affiliated with WorldCap. 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. "Google Finance certainly has data for Tokyo Stock Exchange (called TYO on Google) listings.  You could create a ""portfolio"" consisting of the stocks you care about and then visit it once per day (or write a script to do so)." You may refer to project http://jstock.sourceforge.net. It is open source and released under GPL. It is fetching data from Yahoo! Finance, include delayed current price and historical price. "All of these frameworks, Markowitz, Mean/CVaR, CARA, etc  sit inside a more general framework which is that ""returns are good"" and ""risk/lack of certainty in the returns is bad"", and there's a tradeoff between the two encoded as some kind of risk aversion number.  You can measure ""lack of certainty in returns"" by vol, CVaR, weighted sum of higher moments, but even sector/region concentration.  Similarly do I want more ""returns"" or ""log returns"" or ""sqrt returns"" in the context of this tradeoff?  You don't need any formal notion of utility at that point - and I don't know what formal ideas of utility beyond ""I want more returns and less risk"" really buys you. The Sharpe ratio only really gets its meaning because you've got some formal asset-pricing notion of utility.   In my view the moment that you're putting constraints on the portfolio (e.g. long only, max weights, don't deviate too much from the benchmark ...) - really you're operating in this more general framework anyway and you're not in ""utility-land"" anymore."