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!
Fundamental Analysis can be used to help you determine what to buy, but they won't give you an entry signal for when to buy. Technical Analysis can be used to help you determine when to buy, and can give you entry signals for when to buy. There are many Technical Indicator which can be used as an entry signal, from as simple as the price crossing above a moving average line and then selling when the price crosses back below the moving average line, to as complicated as using a combination of indicators to all line up for an entry signal to be valid. You need to find the entry signals that would suit your investing or trading and incorporate them as part of your trading plan. If you want to learn more about entry signals you are better off learning more about Technical Analysis. Hey a project I'm working on is collecting data on people like you.  If you have a great idea that's been bouncing around in your head for ages, this is the time to make it a reality. 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This information will be emailed to you.  Thank you for your input, we hope to be in contact soon. 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. Part A solution:  Assume no turnover in A.:      Average Balance * Annual Interest - Average Balance * Annual Cost of funds + Annual Fee = Profit from A        Profit From A = Average Balance * Interest Rate - Cost of Funds * Average Balance + Annual Fee     So for B here is the sneaky thing, the Average Balance is 1/12 of the Volume... That makes it really simple...       Volume * InterChange - Average Balance * Cost of Funds + Annual Fee = Profit From A       Volume = 12 x Average Balance So:       12 x Average Balance * Interchange (0.015) - Average Balance * Cost of Funds (0.04) + Annual Fee (Say 50)= Profit From A (260)       0.18* Average Balance - 0.04 * Average Balance = 210  Average Balance = 210/.14  Annual turnover = 12* Average Balance   Come @ me bro :p 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. This is going to be a bit of a shameless plug, but I've build a portfolio tracking website to track your portfolio and be able to share it (in read-only mode) as  well. It is at http://frano.carelessmusings.com and currently in beta. Most portfolio trackers are behind a login wall and thus will lack the sharing function you are looking for. Examples of these are: Yahoo Finance, Google Finance, Reuters Portfolios, MorningStart Portfolios, and many others. Another very quick and easy solution (if you are not trading too often) is a shared google docs spreadsheet. Gdocs has integration with google finance and can retrieve prices for stocks by symbol. A spreadsheet can contain the following: Symbol, Quantity, Avg. Buy Price, Price, P/L, P/L% and so on. The current price and P/L data can be functions that use the google finance API. Hope this helps, and if you check out my site please let me know what you think and what I could change. 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. "At the bottom of Yahoo! Finance's S & P 500 quote Quotes are real-time for NASDAQ, NYSE, and NYSE MKT. See also delay   times for other exchanges. All information provided ""as is"" for   informational purposes only, not intended for trading purposes or   advice. Neither Yahoo! nor any of independent providers is liable for   any informational errors, incompleteness, or delays, or for any   actions taken in reliance on information contained herein. By   accessing the Yahoo! site, you agree not to redistribute the   information found therein. Fundamental company data provided by Capital IQ. 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