Evidence for Technical Analysis [duplicate]
To answer your original question: There is proof out there. Here is a paper from the Federal Reserve Bank of St. Louis that might be worth a read.  It has a lot of references to other publications that might help answer your question(s) about TA.  You can probably read the whole article then research some of the other ones listed there to come up with a conclusion.  Below are some excerpts:  Abstract: This article introduces the subject of technical analysis in the foreign exchange market, with emphasis on its importance for questions of market efficiency.  “Technicians” view their craft, the study of price patterns, as exploiting traders’ psychological regularities.  The literature on technical analysis has established that simple technical trading rules on dollar exchange rates provided 15 years of positive, risk-adjusted returns during the 1970s and 80s before those returns were extinguished.  More recently, more complex and less studied rules have produced    more modest returns for a similar length of time.  Conventional explanations that rely on risk adjustment and/or central bank intervention do not plausibly justify the observed excess returns from following simple technical trading rules.  Psychological biases, however, could contribute to the profitability of these rules. We view the observed pattern of excess returns to technical trading rules as being consistent with an adaptive markets view of the world.    and  The widespread use of technical analysis in foreign exchange (and   other) markets is puzzling because it implies  that either traders are   irrationally making decisions on useless information or that past   prices contain useful  information for trading.  The latter   possibility would contradict the “efficient markets hypothesis,”   which holds that  no trading strategy should be able to generate   unusual profits on publicly available information—such as past    prices—except by bearing unusual risk. And the observed  level of   risk-adjusted profitability measures market  (in)efficiency. Therefore   much research effort has been directed toward determining whether   technical analysis is  indeed profitable or not. One of the earliest   studies, by Fama and Blume (1966), found no evidence that a particular   class of TTRs could earn abnormal profits in the stock market.   However, more recent research by Brock,  Lakonishok and LeBaron (1992)   and Sullivan, Timmermann an d White (1999) has provided contrary   evidence. And  many studies of the foreign exchange market have found   evidence that TTRs can generate persistent profits (Poole  6  (1967),   Dooley and Shafer (1984), Sweeney (1986), Levich and Thomas (1993),   Neely, Weller and Dittmar (1997),  Gençay (1999), Lee, Gleason and   Mathur (2001) and Martin (2001)).
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. In fact markets are not efficient and participants are not rational. That is why we have booms and busts in markets. Emotions and psychology play a role when investors and/or traders make decisions, sometimes causing them to behave in unpredictable or irrational ways. That is why stocks can be undervalued or overvalued compared to their true value.  Also, different market participants may put a different true value on a stock (depending on their methods of analysis and the information they use to base their analysis on). This is why there are always many opportunities to profit (or lose your money) in liquid markets. Doing your research, homework, or analysis can be related to fundamental analysis, technical analysis, or a combination of the two. For example, you could use fundamental analysis to determine what to buy and then use technical analysis to determine when to buy. To me, doing your homework means to get yourself educated, to have a plan, to do your analysis (both FA and TA), to invest or trade according to your plan and to have a risk management strategy in place. Most people are too lazy to do their homework so will pay someone else to do it for them or they will just speculate (on the latest hot tip) and lose most of their money. They are almost always behind paywalls. The analysts that write these reports need to get paid somehow.  I'd search for reports on google by specific topic and see what you find, but no where is there a treasure trove of free information id like to start by saying youre still doing this yourself, and i dont actually have all the info required anyway, dont send it but  &gt;[3] Descriptive Statistical Measures: Provide a thorough discussion of the meaning and interpretation of the four descriptive &gt;statistical measures required in your analysis: (1) Arithmetic Mean, (2) Variance, (3) Standard Deviation and (4) Coefficient of &gt;Variation. For example, how are these measures related to each other? In order to develop this discussion, you may want to &gt;consult chapters 2 and 3 of your textbook. This topic is an important part of your report. can be easily interpreted, im guessing the mean is simply just the observed (and then projected stock price for future models) the standard deviation determines the interval in which the stock price fluctuates. so you have like a curve, and then on this curve theirs a bunch of normal distributions modeling the variance of the price plotted against the month  also the coefficient of variation is just r^2 so just read up on that and relate it to the meaning of it to the numbers you have  actually my stats are pretty rusty so make sure you really check into these things  but otherwise the formulas for part 4 is simple too. you can compare means of a certain month using certain equations, but there are different ones for certain situations  you can test for significance by comparing the differences of the means and if its outside of your alpha level then it probably means your company is significantly different from the SP index. (take mu of SP - mu of callaway)  you can also find more info on interpreting the two different coefficients your given if you look up comparing means of linear regression models or something "There seems to be a common sentiment that no investor can consistently beat the market on returns. What evidence exists for or against this? First off, even if the markets were entirely random there would be individual investors that would consistently beat the market throughout their lifetime entirely by luck.  There are just so many people this is a statistical certainty.  So let's talk about evidence of beating the market due to persistent skill. I should hedge by saying there isn't a lot of good data here as most understandably most individual investors don't give out their investment information but there are some ok datasets.  There is weak evidence, for instance, that the best individual investors keep outperforming and interestingly that the trading of individual investors can predict future market movements.  Though the evidence is more clear that individual investors make a lot of mistakes and that these winning portfolios are not from commonly available strategies and involve portfolios that are much riskier than most  would recommend. Is there really no investment strategy that would make it likely for this investor to consistently outperform her benchmark? There are so, many, papers (many reasonable even) out there about how to outperform benchmarks (especially risk-adjusted basis).  Not too mention some advisers with great track records and a sea of questionable websites.  You can even copy most of what Buffet does if you want. Remember though that the average investor by definition makes the average ""market"" return and then pays fees on top of that.  If there is a strategy out there that is obviously better than the market and a bunch of people start doing it, it quickly becomes expensive to do and becomes part the market.  If there was a proven, easy to implement way to beat the market everyone would do it and it would be the market. So why is it that on this site or elsewhere, whenever an active trading strategy is discussed that potentially beats the market, there is always a claim that it probably won't work? To start with there are a large number of clearly bad ideas posed here and elsewhere.  Sometimes though the ideas might be good and may even have a good chance to beat the market.  Like so many of the portfolios that beat the market though and they add a lot of uncertainty and in particular, for this personal finance site, risk that the person will not be able to live comfortably in retirement. There is so much uncertainty in the market and that is why there will always be people that consistently outperform the market but at the same time why there will be few, if any, strategies that will outperform consistently with any certainty." Factset also provides a host of tools for analysis. Not many people know as they aren't as prevalent as Bloomberg. CapitalQ and Thomson Reuters also provide analysis tools. Most of the market data providers also provide analysis tools to analyze the data they and others provide. Log in to your Scottrade account, and goto Markets --> Analyst Views --> Click the PDF link for the company.  Also, there is also the 'Views and News' part of the web page which has additional information beyond what exist in the reports. Regardless of your thoughts on what was happening in late 2012, financial prices should not be used as the sole barometer of a recovery...this is why the Fed uses tons of macroeconomic data, not just that BAC has been up 20% in the last 6 months.   My point is if you are going to tout what seems to be a market timing model, where the authors are proud of the fact that the entire thing is data mined,  you need strong out of sample evidence (over a few business cycles) that it works.  Nothing here comes close "Back-testing itself is flawed. ""Past performance is no guarantee of future results"" is an important lesson to understand. Market strategies of one kind or another work until they don't.  Edited in -- AssetPlay.net provides a tool that's halfway to what you are looking for. It only goes back to 1972, however. Just to try it, I compared 100% S&P to a 60/40 blend of S&P with 5 yr t-bills (a misnamed asset, 5 yr treasuries are 'notes' not 'bills') I found the mix actually had a better return with lower volatility.  Now, can I count on that to work moving forward? Rates fell during most of this entire period so bonds/notes both looked pretty good. This is my point regarding the backtest concept.  GeniusTrader appears more sophisticated, but command line work on PCs is beyond me. It may be worth a look for you, JP. ETF Replay appears to be another backtest tool. It has its drawbacks, however, (ETFs only)" That is called a 'volume chart'. There are many interactive charts available for the purpose. Here is clear example.  (just for demonstration but this is for India only) 1) Yahoo Finance 2) Google Finance 3) And many more Usually, the stock volume density is presented together (below it) with normal price vs time chart. Note: There is a friendly site about topics like this. Quant.stackexchange.com. Think of checking it out. Interesting stuff, but I'd want to know how it occurred to them to check for a Citigroup Bear Run.  It sounds like they simply datamined for one case which fit their hypothesis.  I'd also like to see (1) how other finance companies fared in the same period and (2) how many upticks were available to sell on. About 10 years ago, I used to use MetaStock Trader which was a very sound tool, with a large number of indicators, but it has been a number of years since I have used it, so my comments on it will be out of date. At the time it relied upon me purchasing trading data myself, which is why I switched to Incredible Charts. I currently use Incredible Charts which I have done for a number of years, initially on the free adware service, now on the $10/year for EOD data access. There are quicker levels of data access, which might suit you, but I can't comment on these. It is web-based which is key for me. The data quality is very good and the number of inbuilt indicators is excellent. You can build search routines on the basis of specific indicators which is very effective. I'm looking at VectorVest, as a replacement for (or in addition to) Incredible Charts, as it has very powerful backtesting routines and the ability to run test portfolios with specific buy/sell criteria that can simulate and backtest a number of trading scenarios at the same time. The advantage of all of these is they are not tied to a particular broker. "&gt; Forecasting prices to the level of accuracy they purport is a fool's errand. Sell side analysts are there to get you to buy something, not to make you money. &gt; If they truly believed their analysis was significantly better than anyone else's in the market, they would trade on their own analysis. &gt; No one ever got rich by following analyst recommendations. &gt; Don't believe me? Track the buy/sell recommendations in a spreadsheet for 50+ stocks. I would be shocked if you significantly outperformed the market.  Only partly right.  Sell side price targets are bullshit.  Literally everyone knows this.  The reason there is value isn't because of their predictions but because of everything else.  [Here's another professional's opinion as well:](http://www.reddit.com/r/investing/comments/27dokr/aapl_proves_wall_street_is_nuts/chzy78s?context=3)  &gt; If we're talking about sell-side institutional analysts, then this is not necessarily correct. It's just that the retail sector seems to only give a shit about the forecasts/conclusions (""ohhh DB says buy xyz with target of xx.xx!""). This goes to show how ignorant retail is when it comes to what the actual value of sell-side research reports are.  &gt; Sell-side research isn't valuable for buy-side because of the recommendations.. those are in fact the most ignored aspect of published research. It's valuable for buy-side because of the content. Sell-side analysts do the bullshit grind in investigating underlying information (such as visits to operational endeavors and clawing together bulk data). Buy side uses this underlying accrued data to formulate their own conclusions." "I think the author is really on point here. Just read r/investing or seekingalpha or some other forum with low barriers to entry and you see the same phenomena. People like drama, and there's a convergence towards dramatic opinions and extremes. The scariest part is that while stock valuations are fairly subjective, it is very common to see top reddit comments that are verifiably false, on financial subjects or otherwise.  At some point, I'd really like to take a web scraper to r/investing and see what the relationship between comments on certain companies and their stock performance is. Similarly, it'd be interesting to see if people who are right tend to stick around/people who stick around are more often correct. It'd also be interesting to compare the ""reddit consensus"" with actual analyst consensus and to see where it differs. It might make a good master's thesis.   On the other hand, I'm not convinced that the traditional punditry is necessarily better. Professionals are generally more articulate and ought to be able to highlight the relevant details in a company or sector. However, the 2 minute segments they have with these professionals on CNBC are basically just noise when compared with hour long analyst calls, and I've never found them particularly useful for extracting more than a very 1000-kilometer high view on a topic that I know nothing about.  I think longer form publications like actual interviews, where the guests are on for a longer period of time, or print articles from WSJ/FT/etc. are still good quality, but even financial media has really been catering to the lowest common denominator with free or televised content.  In any case, I think this really reduces down to an issue of critical thinking. Random internet comments can actually be really insightful, or garbage, but most people can't discern the two. I think the same applies to punditry too, however." "Strategy would be my top factor.  While this may be implied, I do think it helps to have an idea of what is causing the buy and sell signals in speculating as I'd rather follow a strategy than try to figure things out completely from scratch that doesn't quite make sense to me. There are generally a couple of different schools of analysis that may be worth passing along: Fundamental Analysis:Fundamental analysis of a business involves analyzing its financial statements and health, its management and competitive advantages, and its competitors and markets. When applied to futures and forex, it focuses on the overall state of the economy, interest rates, production, earnings, and management. When analyzing a stock, futures contract, or currency using fundamental analysis there are two basic approaches one can use; bottom up analysis and top down analysis. The term is used to distinguish such analysis from other types of investment analysis, such as quantitative analysis and technical analysis. Technical Analysis:In finance, technical analysis is a security analysis methodology for forecasting the direction of prices through the study of past market data, primarily price and volume. Behavioral economics and quantitative analysis use many of the same tools of technical analysis, which, being an aspect of active management, stands in contradiction to much of modern portfolio theory. The efficacy of both technical and fundamental analysis is disputed by the efficient-market hypothesis which states that stock market prices are essentially unpredictable. There are tools like ""Stock Screeners"" that will let you filter based on various criteria to use each analysis in a mix.  There are various strategies one could use.  Wikipedia under Stock Speculator lists: ""Several different types of stock trading strategies or approaches exist including day trading, trend following, market making, scalping (trading), momentum trading, trading the news, and arbitrage.""  Thus, I'd advise research what approach are you wanting to use as the ""Make it up as we go along losing real money all the way"" wouldn't be my suggested approach. There is something to be said for there being numerous columnists and newsletter peddlers if you want other ideas but I would suggest having a strategy before putting one's toe in the water."