looking for research tool to plug in and evaluate theoretical historical returns
"The professional financial advisors do have tools which will take a general description of a portfolio and run monte-carlo simulations based on the stock market's historical behavior. After about 100 simulation passes they can give a statistical statement about the probable returns, the risk involved in that strategy, and their confidence in these numbers.  Note that they do not just use the historical data or individual stocks. There's no way to guarantee that the same historical accidents would have occurred that made one company more successful than another, or that they will again. ""Past performance is no guarantee of future results""... but general trends and patterns can be roughly modelled. Which makes that a good fit for those of us buying index funds, less good for those who want to play at a greater level of detail in the hope of doing better. But that's sorta the point; to beat market rate of return with the same kind of statistical confidence takes a lot more work."
"I keep spreadsheets that verify each $ distribution versus the rate times number of shares owned. For mutual funds, I would use Yahoo's historical data, but sometimes shows up late (a few days, a week?) and it isn't always quite accurate enough. A while back I discovered that MSN had excellent data when using their market price chart with dividends ""turned on,"" HOWEVER very recently they have revamped their site and the trusty URLs I have previously used no longer work AND after considerable browsing, I can no longer find this level of detail anywhere on their site !=( Happily, the note above led me to the Google business site, and it looks like I am ""back in business""... THANKS!" "The graphing tools within Yahoo offer a decent level of adjustment. You can easily choose start and end years, and 2 or more symbols to compare.  I caution you. From Jan 1980 through Dec 2011, the S&P would have grown $1 to $29.02, (See Moneychimp) but, the index went up from 107.94 to 1257.60, growing a dollar to only $11.65. The index, and therefore the charts, do not include dividends. So long term analysis will yield false results if this isn't accounted for.  EDIT  - From the type of question this is, I'd suggest you might be interested in a book titled ""Stock Market Logic."" If memory serves me, it offered up patterns like you suggest, seasonal, relations to Presidential cycle, etc. I don't judge these approaches, I just recall this book exists from seeing it about 20 years back." "Usually you gotta build those tools for yourself :P, you can usually build em in excel  as its fairly easy and sort to see what is the most profitable, you can code most of the heavy lifting in excel, monte carlo/""complex"" methods you probably won't even need...   I'm a strong proponent of R however what you're doing is not that complex....  edit: I accidently a word." "Check out Professor Damodaran's website: http://pages.stern.nyu.edu/~adamodar/ . Tons of good stuff there to get you started. If you want more depth, he's written what is widely considered the bible on the subject of valuation: ""Investment Valuation"". DCF is very well suited to stock analysis. One doesn't need to know, or forecast the future stock price to use it. In fact, it's the opposite. Business fundamentals are forecasted to estimate the sum total of future cash flows from the company, discounted back to the present. Divide that by shares outstanding, and you have the value of the stock. The key is to remember that DCF calculations are very sensitive to inputs. Be conservative in your estimates of future revenue growth, earnings margins, and capital investment. I usually develop three forecasts: pessimistic, neutral, optimistic. This delivers a range of value instead of a false-precision single number. This may seem odd: I find the DCF invaluable, but for the process, not so much the result. The input sensitivity requires careful work, and while a range of value is useful, the real benefit comes from being required to answer the questions to build the forecast. It provides a framework to analyze a business. You're just trying to properly fill in the boxes, estimate the unguessable. To do so, you pore through the financials. Skimming, reading with a purpose. In the end you come away with a fairly deep understanding of the business, how they make money, why they'll continue to make money, etc." I  found that  an application already exists which does virtually everything I want to do with a reasonable interface.  Its called My Personal Index.  It has allowed me  to look at my asset allocation all in one place. I'll have to enter: The features which solve my problems above include:  Note - This is related to an earlier post I made regarding dollar cost averaging and determining rate of returns.   (I finally got off my duff and did something about it) Here are a few things I've already done, and others reading this for their own use may want to try.  It is very easy to find a pattern in any set of data. It is difficult to find a pattern that holds true in different data pulled from the same population.  Using similar logic, don't look for a pattern in the data from the entire population. If you do, you won't have anything to test it against. If you don't have anything to test it against, it is difficult to tell the difference between a pattern that has a cause (and will likely continue) and a pattern that comes from random noise (which has no reason to continue). If you lose money in bad years, that's okay. Just make sure that the gains in good years are collectively greater than the losses in bad years. If you put $10 in and lose 50%, you then need a 100% gain just to get back up to $10.  A Black Swan event (popularized by Nassim Taleb, if memory serves) is something that is unpredictable but will almost certainly happen at some point. For example, a significant natural disaster will almost certainly impact the United States (or any other large country) in the next year or two. However, at the moment we have very little idea what that disaster will be or where it will hit.  By the same token, there will be Black Swan events in the financial market. I do not know what they will be or when they will happen, but I do know that they will happen. When building a system, make sure that it can survive those Black Swan events (stay above the death line, for any fellow Jim Collins fans). Recreate your work from scratch. Going through your work again will make you reevaluate your initial assumptions in the context of the final system. If you can recreate it with a different medium (i.e. paper and pen instead of a computer), this will also help you catch mistakes. http://www.euroinvestor.com/exchanges/nasdaq/macromedia-inc/41408/history will work as DumbCoder states, but didn't contain LEHMQ (Lehman Brother's holding company). You can use Yahoo for companies that have declared bankruptcy, such as Lehman Brothers: http://finance.yahoo.com/q/hp?s=LEHMQ&a=08&b=01&c=2008&d=08&e=30&f=2008&g=d but you have to know the symbol of the holding company. I've looked into Thinkorswim; my father uses it. Although better than eTrade, it wasn't quite what I was looking for. Interactive Brokers is a name I had heard a long time ago but forgotten. Thank you for that, it seems to be just what I need. Another possibly more flexible option is Yahoo finance here is an example for the dow.. http://finance.yahoo.com/q/hp?s=%5EDJI&a=9&b=1&c=1928&d=3&e=10&f=2012&g=d&z=66&y=0 Some of the individual stocks you can dl directly to a spreadsheet (not sure why this isn't offer for indexs but copy and paste should work). http://finance.yahoo.com/q/hp?s=ACTC.OB+Historical+Prices Personally, I think this one is best. RAROC (risk-adjusted return on capital) puts things in perspective for excess returns when considering risk-contribution. It does have its flaws, e.g. the quality of the VaR can be manipulated or simply incorrectly measured. But as in any model, it's GIGO (garbage-in garbage-out). "This falls under value investing, and value investing has only recently picked up study by academia, say, at the turn of the millennium; therefore, there isn't much rigorous on value investing in academia, but it has started. However, we can describe valuations: In short, valuations are randomly distributed in a log-Variance Gamma fashion with some reason & nonsense mixed in. You can check for yourself on finviz.  You can basically download the entire US market and then some, with many financial and technical characteristics all in one spreadsheet. Re Fisher: He was tied for the best monetary economist of the 20th century and created the best price index, but as for stocks, he said this famous quote 12 days before the 1929 crash: ""Stock prices have reached what looks like a permanently high plateau. I do not feel there will be soon if ever a 50 or 60 point break from present levels, such as (bears) have predicted. I expect to see the stock market a good deal higher within a few months.""   - Irving Fisher, Ph.D. in economics, Oct. 17, 1929 EDIT Value investing has almost always been ignored by academia.  Irving Fisher and other proponents of it before it was codified by Graham in the mid 20th century certainly didn't help with comments like the above.  It was almost always believed that it was a sucker's game, ""the bigger sucker"" game to be more precise because value investors get destroyed during recession/collapses.  So even though a recessionless economy would allow value investors and everyone never to suffer spontaneous collapses, value investors are looked down upon by academia because of the inevitable yet nearly always transitory collapse.  This expresses that sentiment perfectly. It didn't help that Benjamin Graham didn't care about money so never reached the heights of Buffett who frequently alternates with Bill Gates as the richest person on the planet.  Buffett has given much credibility, and academia finally caught on around in 2000 or so after he was proven right about a pending tech collapse that nearly no one believed would happen; at least, that's where I begin seeing papers being published delving into value concepts.  If one looks harder, academia's even taken the torch and discovered some very useful tools. Yes, investment firms and fellow value investors kept up the information publishing, but they are not academics. The days of professors throwing darts at the stock listings and beating active managers despite most active managers losing to the market anyways really held back this side of academia until Buffett entered the fray and embarrassed them all with his club's performance, culminating in the Superinvestors article which is still relatively ignored.  Before that, it was the obsession with beta, the ratio of a security's variance to its covariance to the market, a now abandoned theory because it has been utterly discredited; the popularizers of beta have humorously embraced the P/B, not giving the satisfaction to Buffet by spurning the P/E.   Tiny technology firms receive ridiculous valuations because a long-surviving tiny tech firm usually doesn't stay small for long thus will grow at huge rates.  This is why any solvent and many insolvent tech firms receive large valuations: risk-adjusted, they should pay out huge on average.  Still, most fall by the wayside dead, and those 100 P/S valuations quickly crumble. Valuations are influenced by growth.  One can see this expressed more easily with a growing perpetuity: Where P is price, i is income, r is the rate of return, and g is the growth rate of i.  Rearranging, r looks like: Here, one can see that a higher P relative to i will dull the expected rate of return while a higher g will boost it. It's fun for us value investor/traders to say that the market is totally inefficient.  That's a stretch.  It's not perfectly inefficient, but it's efficient.  Valuations are clustered very tightly around the median, but there are mistakes that even us little guys can exploit and teach the smart money a lesson or two. If one were to look at a distribution of rs, one'd see that they're even more tightly packed.  So while it looks like P/Es are all over the place industry to industry, rs are much more well clustered. Tech, finance, and discretionaries frequently have higher growth rates so higher P/Es yet average rs.  Utilities and non-discretionaries have lower growth rates so lower P/Es yet average rs." "I'd start with a Google search for ""best backtesting tools."" Does your online brokerage offer anything? You already understand that the data is the important part.  The good stuff isn't free. But yeah, if you have some money to spend you can get more than enough data to completely overwhelm you. :)" I am mostly interested in day to day records, and would like the data to contain information such as dividend payouts, and other parameters commonly available, such as on : http://finviz.com/screener.ashx ... but the kind of queries you can do is limited. For instance you can only go back two years. Check the answers to this Stackoverflow question https://stackoverflow.com/questions/754593/source-of-historical-stock-data a number of potential sources are listed "Long-term capital gains, which is often the main element of investment income for investors who are not high-frequency day traders, are taxed at a single rate that is often substantially below the marginal rate they would otherwise be taxed at, particularly for wealthy individuals. There are a few rationales behind this treatment; the two most common are that the government wants to encourage long-term investments (as opposed to short-term speculation), and that capital gains are a kind of double taxation (from one point of view) as they are coming from income that has already been taxed once before (as wage or ordinary income).  The latter in particular is highly controversial, but this is one of the more divisive political issues in the taxation front - one party would eliminate the tax entirely, the other would eliminate the difference. For most individuals, the majority of their long-term capital gains are taxed at 15% up to almost half of a million dollars total AGI, which is a fairly low rate - it's equivalent to the rate a taxpayer would pay on up to $37,000 in wage income (after deductions/exemptions/etc.).  You can see from this table in Wikipedia that it is much preferred to pay long-term capital gains rates when possible - at every point it's at least 10% lower than the tax rate for ordinary income. Ordinary income includes wages and many other sources of income - basically, anything that is not long term capital gains. Wage income is taxed at this rate, and also subject to some non-income-tax taxes (FICA and Medicare in particular); other sources of ordinary income are not subject to those taxes (including IRA income).  Short term capital gains are generally included in this bucket. Qualified Dividends are treated similarly to long-term capital gains (as they are of a similar nature), and taxed accordingly. The ""Net Investment Tax"" is basically applying the Medicare tax to investment income for higher-income taxpayers ($125k single, $250k joint).  It's on top of capital gains rates for them.  It came about through the Affordable Care Act, and is one of the first provisions likely to be repealed by the new Congress (as it can be repealed through the budgeting provision).  It seems likely that 2017 taxes will not contain this provision."