Price graphs: why not percent change?
The actual price is represented on charts and not the change in price as a percentage, because it is the actual price which is used in all other parts of analysis (both technical and fundamental), and it is the actual figure the security is bought and sold at. A change in price has to be relative to a previous price at a previous time, and we can easily work out the change in price over any given time period. I think what you are concerned about is how to compare a certain actual price change in low priced securities to the same actual price change in a higher priced securities.  For example: $1.00 rise in a $2.00 stock representing a 50% increase in price; $1.00 rise in a $10.00 stock representing a 10% increase in price. On a standard chart both of these look the same, as they both show a $1.00 increase in price. So what can we do to show the true representation of the percentage increase in price? It is actually quite simple. You view the chart using a log scale instead of a standard scale (most charting packages should have this option). What may look like a bubble on a standard scale chart, looks like a healthy uptrend on a log scale chart and represents a true picture of the percentage change in price. Example of Standard Price Scale VS LOG Price Scale on a Chart Standard Price Scale  On the standard scale the price seems to have very little movement from Mar09 to Jan12 and then the price seems to zoom up after Jan12 to Mar13. This is because a 4% increase (for example) of $0.50 is only $0.02, whilst a 4% increase of $7.00 $0.28, so the increases seem much bigger at the end of the chart. LOG Price Scale  On the LOG chart however, these price changes seem to be more evenly displayed no matter at what price level the price change has occurred at. This thus give a better representation of how fast or slow the price is rising or falling, or the size of the change in price. Actually, total return is the most important which isn't necessarily just price change as this doesn't account for dividends that may be re-invested.  Thus, the price change isn't necessarily that useful in terms of knowing what you end up with as an ending balance for an investment. Secondly, the price change itself may be deceptively large as if the stock initial price was low, e.g. a few dollars or less adjusting for stock splits as most big companies will split the stock once the price is high enough, then the percentages can be quite large years later. Something else to consider is the percentage change would be based on what as the initial base.  The price at the start of the chart or something else?  Carefully consider what you want the initial starting point to be in determining price shifts here as one could take either end and claim a rationale for using it. Most people want to look at the price to get an idea of what would X shares cost to purchase rather than look at the percentage change from day to day. I am in complete agreement with you.  The place i have found with the sort of charts you are looking for is stockcharts.com.   To compare the percentage increase of several stocks over a period of 2 market-open days or more, which is quite useful to follow the changes in various stocks… etc., an example:  Here the tickers are AA to EEEEE (OTC) and $GOLD / $SILVER for the spot gold / silver price (that isn't really a ticker).  It is set to show the last 6 market days (one week+)...the '6' in '6&O'.  You can change it in the URL above or change it on the site for the stocks you want... up to 25 in one chart but it gets really hard to tell them apart!  By moving the slider just left of the ‘6’ at the bottom right corner of the chart, you can look at 2 days or more.  For a specific time period in days, highlight the ‘6’ and type any number of market-open days you want (21 days = about one month, etc.).  By setting a time period in days, and moving the entire slider, you can see how your stocks did in the last bull/bear run, as an example. The site has a full how-to, for this and the other types of charts they offer. The only problem is that many OTC stocks are not charted. Save the comparison charts you use regularly in a folder in your browser bookmarks.  Blessings.  I see the entire needed link isn't in blue... but you need it all.
Degree of Operating Leverage (DOL) measures the percent change in EBIT given a 1% change in Revenue. In other words, if DOL is 1.5, then increasing Revenue by 1% will increase EBIT by 1.5%.  Degree of Financial Leverage (DFL) measures the percent change in NI given a 1% change in EBIT.  Degree of Total Leverage (DTL) cuts EBIT out and measures the percent change in NI given a 1% change in Revenue.   What all three of these numbers measure is “elasticity.” The elasticity between two variables is always the percentage change effect on one due to a 1% change in the other.   Before we talk about why you would multiply elasticities, let’s first just look at absolute changes between a change of three variables, X Y and Z. Lets say X impacts Y (X-&gt;Y) and Y impacts Z (Y-&gt;Z). To make it even more concrete, let’s imagine a classroom where every student is required to have 2 books and every book has 100 pages. So X = # students, Y = # of books, and Z = # of pages. If we add one student to the class, we need to add 2 books. If we add 1 book to the class, we have added 100 pages. With absolute changes like this it is obvious that we don’t add, we multiply. In other words, to directly see the impact of a new student on the number of pages (X -&gt; Z), we would say 1 student -&gt; 2 books -&gt; 200 pages. To say 102 pages would obviously be silly.   For percent changes, this looks pretty similar. To make it easy say the class has 100 students. So adding 1 student is a 1% change. Then we go from 200 books to 202 books, a 1% change. So the degree of Student to Book Leverage is 1 (which make sense there are no “fixed pages”). We go from 20,000 pages to 20,200 pages, also a 1% change so the degree of Book to Page leverage is also 1. Thus, the Student to Page leverage is also just a flat 1.   Let’s add fixed amounts. The teacher has a single 2,000 page book on how to teach. We’ll assume the class has 20 students. So we start with 20*2 + 1 = 41 books and 40*100 + 2,000 = 6,000 pages. Let’s add a student. We have a 21/20 -1 = 4% increase in students. 43/41 -1 = 4.89% increase in books. 6,200/6,000 – 1 = 3.33% increase in pages. So the Degree of Student to Book Leverage is 4.00/4.89 = 0.818 and the Degree of Book to Page Leverage is 4.89/3.33 = 1.47. And the direct Student to Page Leverage is 4.00/3.33 = 1.20. Again, note that here it would be silly to add the degrees of leverage, and when we do multiply them we get 0.82*1.47 = 1.2, the right answer.   From here the application to EBIT [= Sales - Fixed Cost - Variable Cost = (Gross Margin * Sales) - Fixed Cost] and the application to EPS [= EBIT - Interest – Taxes = (1 – tax rate)*(EBIT – Interest)] should be obvious. I can supply the full proof mathematically, however, if you would like. Premise: For me, if wal-mart is doing well, consumers are doing well, and it isn't doing well, then we're probably screwed! Look at this scary graph!  This is what pisses me off about economists (extreme reaction to extremism... get over it). One metric will be chosen to indicate a factor, then when there is a change in that metric, all kinds of loosely supported inferences are made about the general economic welfare of the country. Maybe more people are just shopping at trader joe's and Aldi?? Wouldn't it be more useful to look at an index of all grocery stores and make a judgement off of that? In a strictly mathematical sense, no. Or rather, it depends what 'long run' means.  Say today the home average is $200K, and payment is $900/mo. The $900 today happens to be about 20% of the median US monthly income (which is approximately $54,000/yr). Housing rises 4%/yr, income 3%/yr. In 100 years (long enough?) the house costs $10M but incomes are 'only' $1.03M/yr, and the mortgage, even at the same rate is $45K/month, or, to be clear, it rose to 52% of monthly income.  My observation is that, long term, the median home costs what 25% of median income will support, in terms of the mortgage after downpayment. Long term. That means that if you graph this, you'll see trends above and below the long term line. You'll see a 25 year bubble form starting in the late 80's as rates dropped from near 18% to the Sub-4% in the early 00s. But once you normalize it to percent of income to pay the loan, much of the bubble is flattened out. At 18%, $1500/mo bought you a $100K mortgage, but at 3.5%, it bought $335K. This is in absolute dollars, wages also rose during that time. I am just clarifying how rates distort the long term trends and create the short term anomalies. I'd take a look at some graphs and chart the price of bitcoins and its value. You'll be surprised that it follows basically any other vehicle for money. There were several times where the price of bitcoin dropped drastically and ontop of that, there is a wide margin of error that could cost you your entire wallet with no equivalent to a FDIC insurance or possibility of government/federal intervention in the event of theft. "I think that pattern is impossible, since the attempt to apply the second half would seem to prevent executing the first. Could you rewrite that as ""After the stock rises to $X, start watching for a drop of $Y from peak price; if/when that happens, sell."" Or does that not do what you want? (I'm not going to comment on whether the proposed programmed trading makes sense. Trying to manage things at this level of detail has always struck me as glorified guesswork.)" The history of the last 100 years has demonstrated that inflation need not be a straight-line advance in price across the board. New technology has delivered productivity gains which have in many cases compensated for inflation. Keep in mind that price changes may be inflationary, but may not attributable to inflation. For example, the massive swing upward in gasoline prices had more to do with the market, specifically Chinese demand for gas than inflation. But increased fuel costs trickle into the prices of other commodities that we need to buy as well! Is there an indicator about what percentage must be paid when?  Where does economics end and finance start?  I feel quite geeky, but I have been studying a bit of finance, and listening to bloomberg while I work (I am software dev) and want to understand everything :D  edit: just found about this [https://www.google.com/publicdata](https://www.google.co.uk/publicdata/explore?ds=ds22a34krhq5p_&amp;met_y=gd_pc_gdp&amp;idim=country:pt:es:el&amp;hl=en&amp;dl=en#!ctype=l&amp;strail=false&amp;bcs=d&amp;nselm=h&amp;met_y=gd_mio_eur&amp;scale_y=lin&amp;ind_y=false&amp;rdim=country_group&amp;idim=country:pt:es:el:de:fr:uk&amp;idim=country_group:eu&amp;ifdim=country_group&amp;hl=en_US&amp;dl=en&amp;ind=false) The Shiller data is inflation adjusted. In effect, a flat line means that long term, housing rises with inflation, no more no less. There's no argument, just the underlying data to support his charts. This, among them.   As much as I respect Nobel Prize winning Robert Shiller, his approach and analysis of the boom ignored interest rates. Say we look at a $50K earning couple. This is just below median income. At 9%, they qualify to borrow $145K. As rates fell to 4%, they qualify for $244K. Same fixed 30 term. Ignoring all other factors, the swing in rates will generate an oscillation around the long term trend. And my own data crunching suggests the equilibrium median home price will tend toward the price supported by the median income.  A similar, but not identical question - Why can't house prices be out of tune with salaries? In response to Chan-Ho's comment - I'd imagine Shiller understood the interest impact. To clarify, the chart, as presented, ignores it.