Editing Technical analysis (section)

===Efficient-market hypothesis===
The [[efficient-market hypothesis]] (EMH) contradicts the basic tenets of technical analysis by stating that past prices cannot be used to profitably predict future prices. Thus it holds that technical analysis cannot be effective. Economist [[Eugene Fama]] published the seminal paper on the EMH in the ''Journal of Finance'' in 1970, and said "In short, the evidence in support of the efficient markets model is extensive, and (somewhat uniquely in economics) contradictory evidence is sparse."<ref>Eugene Fama, [http://www.e-m-h.org/Fama70.pdf  "Efficient Capital Markets: A Review of Theory and Empirical Work,"] ''The Journal of Finance'', volume 25, issue 2 (May 1970), pp. 383–417.</ref>

However, because future stock prices can be strongly influenced by investor expectations, technicians claim it only follows that past prices influence future prices.<ref name=Aronson>Aronson, David R. (2006). [http://www.wiley.com/WileyCDA/WileyTitle/productCd-0470008741,descCd-authorInfo.html ''Evidence-Based Technical Analysis''], Hoboken, New Jersey: John Wiley and Sons, pages 357, 355–356, 342. {{ISBN|978-0-470-00874-4}}.</ref> They also point to research in the field of [[behavioral finance]], specifically that people are not the rational participants EMH makes them out to be. Technicians have long said that irrational human behavior influences stock prices, and that this behavior leads to predictable outcomes.<ref name=Dichotomy>{{cite journal |author=[[Robert Prechter|Prechter, Robert R Jr]]; Parker, Wayne D |year=2007 |title=The Financial/Economic Dichotomy in Social Behavioral Dynamics: The Socionomic Perspective |journal=Journal of Behavioral Finance |volume=8 |issue=2 |pages=84–108 |doi=10.1080/15427560701381028|citeseerx=10.1.1.615.763 |s2cid=55114691 }}</ref> Author David Aronson says that the theory of behavioral finance blends with the practice of technical analysis:

<blockquote>By considering the impact of emotions, cognitive errors, irrational preferences, and the dynamics of group behavior, behavioral finance offers succinct explanations of excess market volatility as well as the excess returns earned by stale information strategies.... cognitive errors may also explain the existence of market inefficiencies that spawn the systematic price movements that allow objective TA [technical analysis] methods to work.<ref name=Aronson/></blockquote>

EMH advocates reply that while individual market participants do not always act rationally (or have complete information), their aggregate decisions balance each other, resulting in a rational outcome (optimists who buy stock and bid the price higher are countered by pessimists who sell their stock, which keeps the price in equilibrium).<ref name=Clark>Clarke, J., T. Jandik, and Gershon Mandelker (2001). "The efficient markets hypothesis," ''Expert Financial Planning: Advice from Industry Leaders'', ed. R. Arffa, 126–141. New York: Wiley & Sons.</ref> Likewise, complete information is reflected in the price because all market participants bring their own individual, but incomplete, knowledge together in the market.<ref name=Clark/>

====Random walk hypothesis====
The [[random walk hypothesis]] may be derived from the weak-form efficient markets hypothesis, which is based on the assumption that market participants take full account of any information contained in past price movements (but not necessarily other public information). In his book ''A Random Walk Down Wall Street'', Princeton economist [[Burton Malkiel]] said that technical forecasting tools such as pattern analysis must ultimately be self-defeating: "The problem is that once such a regularity is known to market participants, people will act in such a way that prevents it from happening in the future."<ref>Burton Malkiel, A Random Walk Down Wall Street, W. W. Norton & Company (April 2003) p. 168.</ref>  Malkiel has stated that while momentum may explain some stock price movements, there is not enough momentum to make excess profits. Malkiel has compared technical analysis to "[[astrology]]".<ref name=huebscher>Robert Huebscher. [http://www.advisorperspectives.com/newsletters09/pdfs/Burton_Malkiel_Talks_the_Random_Walk.pdf Burton Malkiel Talks the Random Walk]. 7 July 2009.</ref>

In the late 1980s, professors Andrew Lo and Craig McKinlay published a paper which cast doubt on the random walk hypothesis. In a 1999 response to Malkiel, Lo and McKinlay collected empirical papers that questioned the hypothesis' applicability<ref>Lo, Andrew; MacKinlay, Craig. ''A Non-Random Walk Down Wall Street'', Princeton University Press, 1999. {{ISBN|978-0-691-05774-3}}</ref> that suggested a non-random and possibly predictive component to stock price movement, though they were careful to point out that rejecting random walk does not necessarily invalidate EMH, which is an entirely separate concept from RWH. In a 2000 paper, [[Andrew Lo]] back-analyzed data from the U.S. from 1962 to 1996 and found that "several technical indicators do provide incremental information and may have some practical value".<ref name=Foundations/> Burton Malkiel dismissed the irregularities mentioned by Lo and McKinlay as being too small to profit from.<ref name=huebscher/>

Technicians argue that the EMH and random walk theories both ignore the realities of markets, in that participants are not completely rational and that current price moves are not independent of previous moves.<ref name=Kahn/><ref>Poser, Steven W. (2003). ''Applying Elliott Wave Theory Profitably'', John Wiley and Sons, p. 71. {{ISBN|0-471-42007-7}}.</ref> Some signal processing researchers negate the random walk hypothesis that stock market prices resemble [[Wiener process]]es, because the statistical moments of such processes and real stock data vary significantly with respect to window size and [[similarity measure]].<ref>Eidenberger, Horst (2011). "Fundamental Media Understanding" Atpress. {{ISBN|978-3-8423-7917-6}}.</ref> They argue that feature transformations used for the description of audio and [[biosignal]]s can also be used to predict stock market prices successfully which would contradict the random walk hypothesis.

The random walk index (RWI) is a technical indicator that attempts to determine if a stock's price movement is random in nature or a result of a statistically significant trend.  The random walk index attempts to determine when the market is in a strong uptrend or downtrend by measuring price ranges over N and how it differs from what would be expected by a random walk (randomly going up or down).  The greater the range suggests a stronger trend.<ref>{{cite web|url=http://www.asiapacfinance.com/trading-strategies/technicalindicators/RandomWalkIndex|title=AsiaPacFinance.com Trading Indicator Glossary|access-date=1 August 2011|archive-url=https://web.archive.org/web/20110901022339/http://www.asiapacfinance.com/trading-strategies/technicalindicators/RandomWalkIndex|archive-date=1 September 2011|url-status=dead}}</ref>

Applying Kahneman and Tversky's [[prospect theory]] to price movements, Paul V. Azzopardi provided a possible explanation why fear makes prices fall sharply while greed pushes up prices gradually.<ref>Azzopardi, Paul V. (2012), "Why Financial Markets Rise Slowly but Fall Sharply: Analysing market behaviour with behavioural finance", Harriman House, ASIN: B00B0Y6JIC</ref>  This commonly observed behaviour of securities prices is sharply at odds with random walk.  By gauging greed and fear in the market,<ref>{{Cite web|url=https://money.cnn.com/data/fear-and-greed/|title=Fear & Greed Index - Investor Sentiment}}</ref> investors can better formulate long and short portfolio stances.