Evidence for timing market in the short run?
"The time horizon for your IRA is years or decades, therefore there is little evidence that there is a benefit to waiting for the ""perfect time"" to invest.  Unless you plan on making only one or 2 years of investments now and then waiting till retirement; the other deposits you will make over the decades will have a greater influence on returns.  If you are going to search for the perfect time to invest in your index fund, pick a deadline. ""I will take the first sign better than X but will not wait beyond Y""." The study of technical analysis is generally used (sometimes successfully) to time the markets. There are many aspects to technical analysis, but the simplest form is to look for uptrends and downtrends in the charts. Generally higher highs and higher lows is considered an uptrend.  And lower lows and lower highs is considered a downtrend.  A trend follower would go with the trend, for example see a dip to the trend-line and buy on the rebound. Whilst a bottom fisher would wait until a break in the downtrend line and buy after confirmation of a higher high (as this could be the start of a new uptrend). There are many more strategies dealing with the study of technical analysis, and if you are interested you would need to find and learn about ones that suit your investment styles and your appetite for risk. This is the S&P a bit over 20 years. If you've discovered a way to sell at 1400 in 2000, buy at 800 or so in 2003, sell again, well, you get the idea.  There's strong evidence the typical investor hears the S&P is making new highs and rushes in. It's this influx that may send stocks higher from here, until the smart money senses 'overbought' and bails.  I am not the smart money, but my ability to ignore emotion, and use asset allocation naturally had me selling a bit into each run up, and of course buying during downturns. Not all or none, and not with any perfect timing, just at year end when I'm rebalancing.  I am not a fan of short term timing, although I do respect Victor's observations and excellent example of when it's been shown to work. Timing the market and by extension the efficient market hypothesis is one of the most hotly debated subjects in finance academia. If you are to believe the majority of finance professors and PHD's out there chances of timing a market like the NYSE, NASDAQ or LSE is not possible. If you are to take into account the huge amount of hedge funds and money managers who make it their job to prove the efficient market hypothesis wrong then you may have a chance. My opinion is that the EMH is true and that timing a highly efficient market like the NYSE is very difficult or impossible even for those who spend their whole lives trying to beat it. For someone whose primary job isn’t in investments I would put the idea of timing the markets out of your head.
"I interned for about six months at a firm that employed a few technical analysts, so I'll try to provide what little information I can. Since the bulk of the intra-day trading was decided algorithmically, technical analysts had two main functions: This basically boils down to my answer to your question. There are still enough people, trading firms, etc. who believe in candlestick charting and other visually subjective patterns that if you notice a trend, pattern, etc. before the majority of traders observing, you may be able to time the market successfully and profit. This is becoming increasingly dangerous, however, because of the steps I outlined above. Over time, the charting patterns that have been proven effective (often in many firms individually since the algorithms are all proprietary) are incorporated into computer algorithms, so the ""traders"" you're competing with to see the pattern are increasingly low-latency computer clusters less than a few blocks from the exchange. Summary: Candlestick charting, along with other forms of subjective technical analysis, has its believers, and assuming enough of these believers trade the standard strategies based on the standard patterns, one could conceivably time the market with enough skill to anticipate these traders acting on the pattern and therefore profit. However, the marginal benefits of doing so are decreasing rapidly as computers take over more trading responsibility.  Caveats:  I know you're in Australia, where the market penetration of HF/algo traders isn't as high as in the US, so it might be a few more years before the marginal benefits cease to be profitable; that being said, if various forms of technical analysis proved wildly profitable in Australia, above and beyond profits available in other markets, rest assured that large American or British trading firms would already have moved in.  My experience is limited to one trading firm, so I certainly can't speak for the industry as a whole. I know I didn't address candlestick charts specifically, but since they're only one piece of visual technical analysis, I tried to address the issue as a whole.  This somewhat ties into the debate between fundamental or technical analysis, which I won't get into. Investopedia has a short article on the subject. As I said, I won't get into this because while it's a nice debate for small traders, at large trading firms, they don't care; they want to make profit, and any strategy that can be vetted, whether it's fundamental, technical, or astrological, will be vetted.  I want to add more information to my answer to clear up some of the misconceptions in the comments, including those talking about biased studies and a lack of evidence for or against technical analysis (and candlestick charts; I'll explore this relationship further down).  It's important to keep in mind that charting methods, including candlestick charts, are visually subjective ways of representing data, and that any interpretations drawn from such charts should, ideally, represent objective technical indicators. A charting method is only as good as the indicators it's used to represent. Therefore, an analysis of the underlying indicators provides a suitable analysis for the visual medium in which they're presented.  One important study that evaluates several of these indicators is Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation by Lo, Mamaysky, and Wang. Lest anyone accuse its authors of bias, I should point out that not only is it published by the National Bureau of Economic Research (a highly reputable organization within economics and finance), but also that the majority of its authors come from MIT's Sloan school, which holds a reputation second to none. This study finds that several technical indicators, e.g. head-and-shoulder, double-bottom, and various rectangle techniques, do provide marginal value. They also find that although  human judgment is still superior to most computational algorithms in the area of visual pattern recognition, ... technical analysis can be improved by using automated algorithms Since this paper was published in 2000, computing power and statistical analysis have gained significant ground against human ability to identify and exploit for visual pattern detection like candlestick charts.  Second, I suggest you look into David Aaronson's book, Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals. He finds similar results to the Lo, et. al. paper, in that some technical indicators do add value to the investment process, but those that do are those that can be represented mathematically and thus programmed directly into trading algorithms (thus bypassing visual tools like candlestick charts).  He describes how studies, including Lo, et al., have found that head and shoulders patterns are worse than random, i.e. you would earn higher returns if you simply traded at random. That point is worth than repeating. If a day-trader is using a candlestick chart and using head-and-shoulders patterns as part of their toolkit, he's rolling the dice when he uses that pattern and returns that come from its application come from chance. This reminds me of that old story about a company that sends out pamphlets predicting the results of sports games, complete with ""strategies"" and ""data"" to back up the predictions. The company sends out several versions of the pamphlet every game, each predicting a different winner. Given a large enough sample size, by the end of the season, there are a few people who have received a pamphlet that accurately predicted the winner for every game and they're convinced the system is perfect. The others weren't so lucky, however. Relying on candlestick charts and TA patterns that are relics from the pre-computerized era is reassuring to some traders and gives them a sense of control and ""beating the market,"" but how long will chance remain on your side? This is why I maintain that visual tools like candlestick charts are a slowly dying medium. They certainly still add value to some trading firms, which is why Bloomberg terminals still ship with this functionality built in, but as more and more research shows, automated algorithms and statistical indicators can provide more value. It's also important to think about whether the majority of the value added by visual tools like candlestick charts comes in the form of profit or a sense of security to traders who learned the field using them over the past few decades.  Finally, it's extremely important to realize that the actions of retail investors in the equities market cannot begin to represent the behaviors of the market as a whole. In the equities markets alone, trading firms and institutional investors dwarf retail investors, and the difference in scale is even more vastly pronounced in derivatives and currency markets. The fact that some retail investors use candlestick charts and the technical indicators they (hope) underlie them provides nothing but minor anecdotal evidence as to their effectiveness." R/stockmarket is probably the best.  When I have some free time I can test that strategy back as long as you would like in quantstrat, although the only problem with testing futures is joining the consolidated contracts, however I can test it with SPY as SPY returns and ES_F track very closely. In the short term the market is a popularity contest In the short run which in value investing time can extend even to many years, an equity is subject to the vicissitudes of the whims by every scale of panic and elation. This can be seen by examining the daily chart of any large cap equity in the US.  Even such large holdings can be affected by any set of fear and greed in the market and in the subset of traders trading the equity. Quantitatively, this statement means that equities experience high variance in the short rurn. in the long term [the stock market] is a weighing machine In the long run which in value investing time can extend to even multiple decades, an equity is more or less subject only to the variance of the underlying value. This can be seen by examining the annual chart of even the smallest cap equities over decades.  An equity over such time periods is almost exclusively affected by its changes in value. Quantitatively, this statement means that equities experience low variance in the long run. Mostly some custom work i've done myself, bayesian and time series models, but there is some pattern matching. Most TA functions such as MA's, MACD's, BollingerBands, are simple ways of doing time series analysis.  MA's are basic filters.  MACD is essentially a way of viewing acceleration, as its the informational difference between filters.  BB's are mean reverters based on standard deviation/  RSI is a ratio of filtered up to down moves basically generating an indicator based on how strong the market has moved. Buy low, sell high - the problem, of course, finding a crystal ball that will tell you when the highs and lows are going to happen :-) You could, for instance, save your money in cash and wait for the occasional sharp drop, but then you've lost profits & dividends from having that cash under the mattress all those years you were waiting. About the closest I've ever gotten to market timing, and I think the closest anyone can get in real life, is that I cut personal spending to the bone from 2008 to 2011, and invested every spare cent.  But such opportunities only come along a few times in a lifetime. The other thing is to avoid what a lot of people do, which you might call anti-timing.  When the market is high, they jump on the bandwagon, then when it drops they panic-sell, and lose money. "The second drop was part of the same event. The short-term resurgence is often called a ""dead cat bounce"". Mongus Pong's answer is a great answer, I'm going to approach from a more anecdotal POV. Think about the fear that was in the air in Fall 2008. From my recollection, that short-term stabilization came from the Fed, President, Congress, etc standing up and saying that the government would do everything in its power to maintain liquidity in the marketplace. So the fear of a broader collapse of investment banks (beyond Lehman Brothers, Merrill Lynch, etc) due to the Fed behaving as it did in 1929 was abated. By the time you got to Q1 of 2009, it became clear that business vaporized -- nothing was happening. No cars were selling, Christmas was dismal, vacations were cancelled. (example: I went on vacation to a fancy resort in December 2008 and paid $60/night for a $450/night room! The place was half empty.)" A couple ways, but its not a guarantee.  You have to have special charts. Instead of each tick being 1 min, 5 min, or whatever, it is a set number of trades. Say 2000. Since retail investors only buy and sell in small amounts, there will be small volume per tick. An institutional investor, however, would have a much much higher trade lot size, even if using an algo. Thus, large volume spikes in such a chart would signal institutional activity over retail. Similarly, daily charts showing average trade size can help you pick out when institutional activity is highest, as they have much larger trade sizes. You could also learn how the algos work and look for evidence one is being used. ie every time price hits VWAP a large sell order goes through would indicate an institutional investor is selling, especially if it happens multiple times in a row. "The question ""do they?"" is a fair one, but the answer, ""we can only observe the past, and that's what they did,"" may not be so satisfying to you.  It's safe to say that any longer term view of any market will show far less volatility than a short one. It only takes a glance at the return of the 2000's  2009 27.11   2008 -37.22  2007      5.46  2006  15.74 2005  4.79   2004 10.82   2003  28.72  2002    -22.27  2001 -11.98 2000     -9.11 (for the S&P) to see that in an awful decade containing -37% and -22% that the full decade was ""only"" down 9% in total or just less than 1% per year compounded. I'm not predicting any particular returns forward, just noting this is how the math works.  DCA performs well through such a decade, better than in a rising one. You are offered the opportunity to buy into a market selling below the long term trend.  Added note in response to Enno's answer below - On rereading the linked article, I see where the author cites Zvi Bodie who clearly made a logical error. He concludes that since a 20 month S&P put costs triple what a 2.3 mo put costs, that there's more risk the market falls over the longer period, not less. American options can be sold or exercised at any time. If a 2 year option were cheaper than a 2 month option, no one would buy the shorter term. It's pretty simple that the Options Pricing Models take time into account and their value, put or call, increases along with the time till expiration.  On a lighter note, when I take the S&P data for 1871-2012 (I know, no S&P back then, but it's Schiller's data) I get average 40 year returns of 44X, similar to the author's conclusion, $1K growing to $44K. But, the Standard deviation is 28. So the high end of +1 STDEV is $72K, not the author's $166K. Although, the low end 44-28=16 comes close to his $14K figure. $16K is a 7.18% long term return which today doesn't look bad. When the article was written, the author was looking at a 6% short term risk free rate." Thanks for your reply. I’m not familiar with the term “Held-For-Trading Security”. My securities are generally held as collateral against my shorts. To clarify, I am just trying to track the “money in” and “money out” entries in my account for the shorts I write. The transaction is relatively straight forward, except there is a ton of information attached! In simple terms, for the ticker CSR and short contract CSRUQ8, the relevant entries look something like this: There are no entries for expiries. I need to ensure that funds are available for future margin calls and assignments. The sale side using covered calls is as involved. Daily &gt; Weekly &gt; Monthly. This statement says that if you use daily returns you will get more noise than if you used weekly or monthly returns. Much of the research performed uses monthly returns, although weekly returns have been used as well. For HFT you would need to detrend the data in order to spot true turning points. The main source is a direct feed from the stock market itself. The faster the feed, the more expensive. 15-minute delay is essentially free... and for those of us who do long-term investment is more than adequate.  If you want data sooner, sign up with a brokerage that provides that service as part of what you're paying them for... and remember that every bit you spend on services is that much more profit you have to make just to break even, so there's a real tradeoff. "Your questions In the world of technical analysis, is candlestick charting an effective trading tool in timing the markets? It depends on how you define effective. But as a standalone and systematic strategy, it tends not to be profitable. See for example Market Timing with Candlestick Technical Analysis: Using robust statistical techniques, we find that candlestick trading rules are not profitable when applied to DJIA component stocks over 1/1/1992 – 31/12/2002 period. Neither bullish or bearish candlestick single lines or patterns provide market timing signals that are any better than what would be expected by chance. Basing ones trading decisions solely on these techniques does not seem sensible but we cannot rule out the possibility that they compliment some other market timing techniques. There are many other papers that come to the same conclusion. If used correctly, how accurate can they be in picking turning points in the market? Technical analysts generally fall into two camps: (i) those that argue that TA can't be fully automated and that interpretation is part of the game; (ii) those that use TA as part of a systematic investment model (automatically executed by a machine) but generally use a combination of indicators to build a working model. Both groups would argue (for different reasons) that the conclusions of the paper I quoted above should be disregarded and that TA can be applied profitably with the proper framework. Psychological biases It is very easy to get impressed by technical analysis because we all suffer from ""confirmation bias"" whereby we tend to acknowledge things that confirm our beliefs more than those that contradict them. When looking at a chart, it is very easy to see all the occurences when a certain pattern worked and ""miss"" the occurences when it did not work (and not missing those is much harder than it sounds). Conclusions" I interned at a wealth management firm that used very active momentum trading, 99% technicals. Strictly ETFs (indexes, currencies, commodities, etc), no individual equities. They'd hold anywhere from 1-4 weeks, then dump it as soon as the chart starts turning over.  As soon as I get enough capital I'm adopting their same exact strategy, it's painfully easy the strategy is tested all the way to 97. how is the continuous series backadjusted? the emini is rolledover and Ratio back adjusted to the 2nd nearest contract, 9 days prior to expiration. since it is an intraday trade, the discrepancy to the real thing should be next to irrelevant. but comparing it to the spx could make it interesting.  what would be a good format to present the results ? jpeg? pdf ? &gt; One is whether prices are correlated to each other for long periods of time as a preliminary study suggested (which would go against efficient markets hypothesis, since you could use that info to game the market) or if that result is illusory and the long term returns are close to a standard normal distribution which would follow the effiecient markets hypo.  The fascinating thing about this is that the returns themselves show no correlation at all (at any time scale), but the *absolute* returns do.  i.e. following a sharp rise/drop in price, you can predict that a sharp rise/drop is likely to follow, you just can't say in which direction.  And this effect carries over for long periods.  Given that by the central limit theorem the sum of identically distributed random variables converges to a gaussian, leads one to think that short term returns *ought* to be gaussian also.  However, they're not.  Evidently there is something very subtle going on.