Portfolio Manage

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Portfolio Management is used to select a portfolio of new product development projects to achieve thfollowing goals:

Maximize the profitability or value of the portfolio Provide balance Support the strategy of the enterprise

Portfolio Management is the responsibility of the senior management team of an organization or businessunit. This team, which might be called the Product Committee, meets regularly to manage the productpipeline and make decisions about the product portfolio. Often, this is the same group that conducts thestage-gate reviews in the organization.

A logical starting point is to create a product strategy - markets, customers, products, strategy approach,competitive emphasis, etc. The second step is to understand the budget or resources available tobalance the portfolio against. Third, each project must be assessed for profitability (rewards), investmentrequirements (resources), risks, and other appropriate factors.

The weighting of the goals in making decisions about products varies from company. But organizationsmust balance these goals: risk vs. profitability, new products vs. improvements, strategy fit vs. reward,

market vs. product line, long-term vs. short-term. Several types of techniques have been used to supportthe portfolio management process:

Heuristic models Scoring techniques Visual or mapping techniques

The earliest Portfolio Management techniques optimized projects' profitability or financial returns usingheuristic or mathematical models. However, this approach paid little attention to balance or aligning theportfolio to the organization's strategy. Scoring techniques weight and score criteria to take into accountinvestment requirements, profitability, risk and strategic alignment. The shortcoming with this approachcan be an over emphasis on financial measures and an inability to optimize the mix of projects. Mapping

techniques use graphical presentation to visualize a portfolio's balance. These are typically presented inthe form of a two-dimensional graph that shows the trade-off's or balance between two factors such asrisks vs. profitability, marketplace fit vs. product line coverage, financial return vs. probability of success,etc.

Portfolio Management

What Does Portfolio ManagementMean?The art and science of making decisions about investment mix and policy, matching investments toobjectives, asset allocation for individuals and institutions, and balancing risk against. performance.

Portfolio management is all about strengths, weaknesses, opportunities and threats in the choice of debtvs. equity, domestic vs. international, growth vs. safety, and many other tradeoffs encountered in theattempt to maximize return at a given appetite for risk.

Investopedia explains Portfolio ManagementIn the case of mutual and exchange-traded funds (ETFs), there are two forms of portfolio management:passive and active. Passive management simply tracks a market index, commonly referred to as indexing


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or index investing. Active management involves a single manager, co-managers, or a team of managerswho attempt to beat the market return by actively managing a fund's portfolio through investmentdecisions based on research and decisions on individual holdings. Closed-end funds are generallyactively managed.

is a tool provides some basic benefits such as giving a holistic view of the variousinvestmentsand thealignment of the investments with the long term goals of the individual. HoweverPortfoliois one of themost challenging jobs and therefore isn't easy. Portfolio Management can help you gain control of yourinvestments and deliver some meaningful value to your earnings from the investments. PortfolioManagement takes a holistic view of the overall earning strategy of the individual.

While managing the investment portfolio; it is important to remember that the riskier strategic investmentsshould always be balanced with more conservative investments. The investment mix should be constantlymonitored to assess which investments are on track, and which are the ones that need help and whichare the ones that need to be shut down.

However, the key of successful portfolio management lies in the execution. A strong portfoliomanagement program can turn any sinking investment around and do the following:

-Maximize value of investments while minimizing the risk-Allowinvestorsto schedule resources more efficiently-Reduce the number of redundant investments and make it easier to kill loss making investments.

And of course portfolio management definitely means that you are left with more money in your pockets.Efficient portfolio management also reduces overall expenditures by 20% by saving the losses that areotherwise made on loss making investments.

So far in India, most of the middle class earners have been risk-averse and therefore park most of theirsavings in Fixed Deposits and Other SavingsAccounts, though the yield from such investment avenues isvery low. However, the recent trend has been such that more people have been attracted towardsinvestment in Mutual Funds and Equities. It is in this light that Portfolio Management Companies have

been gaining prominence in India. The trend is only set to go upwards in the years to come, as the Indianmiddle class becomes more risk friendly.

All of us want to earn money and there are thousand of ways to earn. Investment is one ofthem. Investment is basically postponement of present consumption for the future benefits.It involves two major factors. Postponement of present consumption is certain but thebenefit of future is uncertain, and that uncertainty is known as risk. Risk is the chances ofloosing or not getting the expected return. All of us take risk in some form when we invest.But some investment avenues involve huge risk and some less risk. Risk is measured interms of variability of returns from its expected return i.e. standard deviation or variance.

Risk can also be defined as the risk arising from the market forces which is known assystematic risk and measured in terms of beta and the unique risk known as unsystematicrisk.

The basic objective of any investor is to reduce risk to minimum and maximize the return.Investments can be in form of Bank deposit, Post office, Shares and in any other form butall investments involve risk.

As an investor the various strategies for investments are
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1. To look for the economic, industry and company fundamentals to find out theintrinsic value of the stock and see weather the stock is selling cheap in the marketor not.

2. To look at various statistical graphs and historical price movements to identifytrends for future.

3. Go for the noise as following what others are doing in the market.

4. Believing that the prices are moving in random and then try to pick stocks onrandom.

A professional investor generally go for more then one investment i.e. the investor go for acollection of investment, which is known as a portfolio. Investor by construction of portfoliotries to use the effect of diversification and reduces the unsystematic risk to a great extent.

Portfolio theory was originally proposed by Harry Markowitz in 1950`s was the first formalattempt to quantify the risk of a portfolio and developed a model for determining optional

portfolio. Prior to the development of portfolio model investors dealt with the concept of riskand return somewhat loosely. Intuitively smart investors knew the benefit of diversificationwhich reflected in the traditional edge "Do not put all your eggs in one basket". HarryMarkowitz was the first person to show quantitatively why and how diversification reducesrisk. In recognition of its seminal contribution in this field he was awarded the Nobel Prize ineconomics in 1990.

Markowitz model was highly information intensive. If one is considering a portfolio of nsecurities it requires n expected returns, n variances, n(n-1)/2 covariance and in total itrequires n(n+3)/2 information.

In his contribution Markowitz had suggested that an index, to which securities are related,

may be used for the purpose of generating the covariance terms. Taking clue from thisWilliam sharpe developed his single Index model.

The number of information required reduces significantly i.e. to (3n+2) in total from n(n+3)/2 in the model suggested by William sharpe.

A major breakthrough in the field of portfolio management was the development of CAPM(Capital asset pricing model) which is concerned with

1. What is the relationship between risk and return of an efficient portfolio?

2. What is the relationship between risk and return for individual security?

The CAPM in essence, predicts the relationship between the risk of a security and its return.This relationship is useful in producing a benchmark. It also helps us to make an informedguess about the return that can be expected from a security that has not yet been traded inthe market.

Although the empirical evidence on the CAPM is mixed, it is widely used because of thevaluable insights. William Sharpe its principal originator was awarded the Nobel Prize ineconomics for his work.


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Once the portfolios are constructed the optimal and the efficient portfolios are selected. Thisis done through construction of efficient frontier. All the superior portfolios lie on theefficient frontier.

The selection of best portfolio is done on the basis of indifference curves of investor'schoice. Indifference curve represents a set of risk and expected return combinations that

provide an investor with the same amount of utility. The investor is indifferent about therisk expected return combinations on the same indifference curve. The portfolio which suitsthe requirement of investor is selected even though all portfolios on the efficient frontier arebest ones.

The above presented methods of selecting portfolio need investor to calculate expectedreturns and variances for all the securities under consideration. Furthermore, all thecovariances among these securities need to be estimated, and the risk free rate needs to bedetermined. Once this is done, the investor can identify the composition of the tangencyportfolio as well as its expected return and standard deviation. The investor can thenidentify the optimal portfolio by noting where one of his or her indifference curves touchesbut does not intersect the efficient frontier. This portfolio involves an investment in the

tangency portfolio along with a certain amount of either risk free borrowing or lendingbecause the efficient set is linear.

Such an approach to investing is an exercise in normative economics, wherein investors aretold what they should do. Thus, the approach is prescriptive in nature. In the realm ofpositive economics a descriptive model is presented, how assets are priced? CAPM is widelyused model in this. The CAPM reduces the situation to an extreme case. Everyone has thesame information and agrees about the future prospectus for securities. Implicitly thismeans that investors analyze and process information in the same way. There are perfectmarkets for securities because potential impediments such as finite divisibility, taxes,transaction costs, and different risk free borrowing and lending rates have been assumedaway. This approach allows the focus to shift from how an individual should invest to whatwould happen to security price if everyone invested in a similar manner. Examining the

collective behavior of all investors in the market place enables one to develop the resultingequilibrium relationship between each security's risk and return.

Technical analysis

Infinance,technical analysis is asecurity analysisdiscipline for forecasting the direction of prices through the

study of past market data, primarily price and volume.[1]Behavioral economicsandquantitative

analysisincorporate substantial aspects of technical analysis,[2][page needed]

which being an aspect ofactivemanagementstands in contradistinction to much ofmodern portfolio theory. According to the weak-

formefficient-market hypothesis, such forecasting methods are valueless, since prices follow arandom walkor

are otherwise essentially unpredictable.
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cannot move the market higher, and a well heeled bear won't!; investors need to know which they are facing. In

the end, stock prices are only what investors think; therefore determining what they think is every bit as critical

as an earnings estimate.

Technicians using charts search for archetypal price chart patterns, such as the well-knownhead and

shouldersordouble top/bottomreversal patterns, studytechnical indicators,moving averages, and look for

forms such as lines of support, resistance, channels, and more obscure formations such asflags,pennants,

balance days andcup and handlepatterns.

Technical analysts also widely use market indicators of many sorts, some of which are mathematical

transformations of price, often including up and down volume, advance/decline data and other inputs. These

indicators are used to help access whether an asset is trending, and if it is, its probability of its direction and of

continuation. Technicians also look for relationships between price/volume indices and market indicators.

Examples include therelative strength index, andMACD. Other avenues of study include correlations between

changes inoptions(implied volatility) and put/call ratios with price. Also important are sentiment indicators such

as Put/Call ratios, bull/bear ratios, short interest and Implied Volatility, etc.

There are many techniques in technical analysis. Adherents of different techniques (for example,candlestick

charting,Dow Theory, andElliott wave theory) may ignore the other approaches, yet manytraderscombine

elements from more than one technique. Some technical analysts use subjective judgment to decide which

pattern(s) a particular instrument reflects at a given time, and what the interpretation of that pattern should be.

Others employ a strictly mechanical or systematic approach to pattern identification and interpretation.

Technical analysis is frequently contrasted withfundamental analysis, the study ofeconomicfactors that

influence the way investors price financial markets. Technical analysis holds that prices already reflect all such

trends before investors are aware of them. Uncovering those trends is what technical indicators are designed to

do, imperfect as they may be. Fundamental indicators are subject to the same limitations, naturally. Some

traders use technical or fundamental analysis exclusively, while others use both types to make trading

decisions which conceivably is the most rational approach.

Users of technical analysis are often called technicians or market technicians. Some prefer the term technical

market analyst or simply market analyst. An older term, chartist, is sometimes used, but as the discipline has

expanded and modernized, the use of the term chartist has become less popular, as it is only one aspect of

technical analysis.[citation needed]

[edit]Characteristics

Technical analysis employs models and trading rules based on price and volume transformations, such as

therelative strength index,moving averages,regressions, inter-market and intra-market price correlations,

cycles or, classically, through recognition of chart patterns.
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Technical analysis stands in contrast to thefundamental analysisapproach to security and stock analysis.

Technical analysis analyses price, volume and other market information, whereas fundamental analysis looks

at the actual facts of the company, market, currency or commodity. Most large brokerage, trading group, or

financial institution will typically have both a technical analysis and fundamental analysis team.

Technical analysis is widely used among traders and financial professionals, and is very often used by

activeday traders, market makers, and pit traders. In the 1960s and 1970s it was widely dismissed by

academics. In a recent review, Irwin and Park[7]reported that 56 of 95 modern studies found it produces

positive results, but noted that many of the positive results were rendered dubious by issues such asdata

snoopingso that the evidence in support of technical analysis was inconclusive; it is still considered by many

academics to bepseudoscience.[8]Academics such asEugene Famasay the evidence for technical analysis is

sparse and is inconsistent with theweak formof theefficient-market hypothesis.[9][10]Users hold that even if

technical analysis cannot predict the future, it helps to identify trading opportunities.[11]

In theforeign exchange markets, its use may be more widespread thanfundamental analysis.[12][13]This does

not mean technical analysis is more applicable to foreign markets, but that technical analysis is more

recognized there as to its efficacy there than elsewhere. While some isolated studies have indicated that

technical trading rules might lead to consistent returns in the period prior to 1987,[14][15][16][17]most academic work

has focused on the nature of the anomalous position of the foreign exchange market.[18]It is speculated that

this anomaly is due to central bank intervention, which obviously technical analysis is not designed to

predict.[19]Recent research suggests that combining various trading signals into a Combined Signal Approach

may be able to increase profitability and reduce dependence on any single rule.[20]

[edit]Principles

Stock chart showing levels of support (4,5,6, 7, and 8) and resistance (1, 2, and 3); levels of resistance tend to become

levels of support and vice versa.

Technicians say that a market's price reflects all relevant information, so their analysis looks at the history of a

security's trading pattern rather than external drivers such as economic, fundamental and news events. Price
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action also tends to repeat itself because investors collectively tend toward patterned behavior hence

technicians' focus on identifiable trends and conditions.

[edit]Market action discounts everything

Based on the premise that all relevant information is already reflected by prices, technical analysts believe it isimportant to understand what investors think of that information, known and perceived; studies such as by

Cutler,Poterba, andSummerstitled "What Moves Stock Prices?" do not cover this aspect of investing.

[edit]Prices move in trends

See also:Market trend

Technical analysts believe that prices trend directionally, i.e., up, down, or sideways (flat) or some combination.

The basic definition of a price trend was originally put forward byDow Theory.[6]

An example of a security that had an apparent trend is AOL from November 2001 through August 2002. Atechnical analyst or trend follower recognizing this trend would look for opportunities to sell this security. AOL

consistently moves downward in price. Each time the stock rose, sellers would enter the market and sell the

stock; hence the "zig-zag" movement in the price. The series of "lower highs" and "lower lows" is a tell tale sign

of a stock in a down trend.[21]In other words, each time the stock moved lower, it fell below its previous relative

low price. Each time the stock moved higher, it could not reach the level of its previous relative high price.

Note that the sequence of lower lows and lower highs did not begin until August. Then AOL makes a low price

that doesn't pierce the relative low set earlier in the month. Later in the same month, the stock makes a relative

high equal to the most recent relative high. In this a technician sees strong indications that the down trend is at

least pausing and possibly ending, and would likely stop actively selling the stock at that point.

[edit]History tends to repeat itself

Technical analysts believe that investors collectively repeat the behavior of the investors that preceded them.

"Everyone wants in on the next Microsoft," "If this stock ever gets to $50 again, I will buy it," "This company's

technology will revolutionize its industry, therefore this stock will skyrocket" these are all examples of investor

sentiment repeating itself. To a technician, the emotions in the market may be irrational, but they exist.

Because investor behavior repeats itself so often, technicians believe that recognizable (and predictable) price

patterns will develop on a chart.

[6]

Technical analysis is not limited to charting, but it always considers price trends. For example, many

technicians monitor surveys of investor sentiment. These surveys gauge the attitude of market participants,

specifically whether they arebearishorbullish. Technicians use these surveys to help determine whether a

trend will continue or if a reversal could develop; they are most likely to anticipate a change when the surveys

report extreme investor sentiment. Surveys that show overwhelming bullishness, for example, are evidence
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that an uptrend may reverse the premise being that if most investors are bullish they have already bought the

market (anticipating higher prices). And because most investors arebullish and invested, one assumes that few

buyers remain. This leaves more potential sellers than buyers, despite the bullish sentiment. This suggests that

prices will trend down, and is an example ofcontrarian trading.

[edit]Industry

This section does notciteanyreferences or sources.

Please helpimprove this articleby adding citations toreliable sources. Unsourced material may

bechallengedandremoved.(January 2011)

The industry is globally represented by the International Federation of Technical Analysts (IFTA), which is a

Federation of regional and national organizations and theMarket Technicians Association(MTA). In the United

States, the industry is represented by both theMarket Technicians Association(MTA) and the American

Association of Professional Technical Analysts (AAPTA). The United States is also represented by the

Technical Security Analysts Association of San Francisco (TSAASF). In the United Kingdom, the industry is

represented by the Society of Technical Analysts (STA). In Canada the industry is represented by the

Canadian Society of Technical Analysts. Some other national professional technical analysis organizations are

noted in theexternal linkssection below.

Professional technical analysis societies have worked on creating a body of knowledge that describes the field

of Technical Analysis. A body of knowledge is central to the field as a way of defining how and why technical

analysis may work. It can then be used by academia, as well as regulatory bodies, in developing proper

research and standards for the field. TheMarket Technicians Association(MTA) has published a body ofknowledge, which is the structure for the MTA'sChartered Market Technician(CMT) exam.

[edit]Use

Traders generally share the view that trading in the direction of the trend is the most effective means to be

profitable infinancialorcommoditiesmarkets.John W. Henry,Larry Hite,Ed Seykota,Richard Dennis,William

Eckhardt,Victor Sperandeo,Michael MarcusandPaul Tudor Jones(some of the so-called wizards in the

popular book,Market WizardsbyJack D. Schwager) have each amassed massive fortunes via the use of

technical analysis and its concepts.[citation needed]George Lane, a technical analyst, coined one of the most

popular phrases on Wall Street, "The trend is your friend!"[citation needed]

Many non-arbitragealgorithmic tradingsystems rely on the idea of trend-following, as do manyhedge funds. A

relatively recent trend, both in research and industrial practice, has been the development of increasingly

sophisticated automated trading strategies. These often rely on underlying technical analysis principles

(seealgorithmic tradingarticle for an overview).
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a.org/wiki/Hedge_fundshttp://en.wikipedia.org/wiki/Algorithmic_tradinghttp://en.wikipedia.org/wiki/Algorithmic_tradinghttp://en.wikipedia.org/wiki/Algorithmic_tradinghttp://en.wikipedia.org/wiki/Algorithmic_tradinghttp://en.wikipedia.org/wiki/Hedge_fundshttp://en.wikipedia.org/wiki/Algorithmic_tradinghttp://en.wikipedia.org/wiki/Wikipedia:Citation_neededhttp://en.wikipedia.org/wiki/George_Lane_(technical_analysis)http://en.wikipedia.org/wiki/Wikipedia:Citation_neededhttp://en.wikipedia.org/wiki/Jack_D._Schwagerhttp://en.wikipedia.org/wiki/Market_Wizardshttp://en.wikipedia.org/wiki/Paul_Tudor_Joneshttp://en.wikipedia.org/wiki/Michael_Marcus_(trader)http://en.wikipedia.org/wiki/Victor_Sperandeohttp://en.wikipedia.org/wiki/William_Eckhardt_(trader)http://en.wikipedia.org/wiki/William_Eckhardt_(trader)http://en.wikipedia.org/wiki/Richard_Dennishttp://en.wikipedia.org/wiki/Ed_Seykotahttp://en.wikipedia.org/wiki/Larry_Hitehttp://en.wikipedia.org/wiki/John_W._Henryhttp://en.wikipedia.org/wiki/Commodity_markethttp://en.wikipedia.org/wiki/Financial_marketshttp://en.wikipedia.org/w/index.php?title=Technical_analysis&action=edit&section=9http://en.wikipedia.org/wiki/Chartered_Market_Technicianhttp://en.wikipedia.org/wiki/Market_Technicians_Associationhttp://en.wikipedia.org/wiki/Technical_analysis#External_linkshttp://en.wikipedia.org/wiki/Market_Technicians_Associationhttp://en.wikipedia.org/wiki/Market_Technicians_Associationhttp://en.wikipedia.org/wiki/Wikipedia:Verifiability#Burden_of_evidencehttp://en.wikipedia.org/wiki/Template:Citation_neededhttp://en.wikipedia.org/wiki/Wikipedia:Identifying_reliable_sourceshttp://en.wikipedia.org/w/index.php?title=Technical_analysis&action=edithttp://en.wikipedia.org/wiki/Wikipedia:Verifiabilityhttp://en.wikipedia.org/wiki/Wikipedia:Citing_sourceshttp://en.wikipedia.org/w/index.php?title=Technical_analysis&action=edit&section=8http://en.wikipedia.org/wiki/Contrarian_investing


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[edit]Systematic trading

[edit]Neural networks

Since the early 1990s when the first practically usable types emerged,artificial neural networks(ANNs) have

rapidly grown in popularity. They areartificial intelligenceadaptive software systems that have been inspired by

how biological neural networks work. They are used because they can learn to detect complex patterns in data.

In mathematical terms, they are universalfunction approximators,[22][23]meaning that given the right data and

configured correctly, they can capture and model any input-output relationships. This not only removes the

need for human interpretation of charts or the series of rules for generating entry/exit signals, but also provides

a bridge tofundamental analysis, as the variables used in fundamental analysis can be used as input.

As ANNs are essentially non-linear statistical models, their accuracy and prediction capabilities can be both

mathematically and empirically tested. In various studies, authors have claimed that neural networks used for

generating trading signals given various technical and fundamental inputs have significantly outperformed buy-hold strategies as well as traditional linear technical analysis methods when combined with rule-based expert

systems.[24][25][26]

While the advanced mathematical nature of such adaptive systems has kept neural networks for financial

analysis mostly within academic research circles, in recent years more user friendlyneural network

softwarehas made the technology more accessible to traders. However, large-scale application is problematic

because of the problem of matching the correct neural topology to the market being studied.

[edit]Rule-based trading

This section does notciteanyreferences or sources.Please helpimprove this articleby adding citations toreliable sources. Unsourced material may

bechallengedandremoved.(January 2011)

Rule-based trading is an approach intended to create trading plans using strict and clear-cut rules. Unlike some

other technical methods and the approach of fundamental analysis, it defines a set of rules that determine all

trades, leaving minimal discretion. The theory behind this approach is that by following a distinct set of trading

rules you will reduce the number of poor decisions, which are often emotion based.

For instance, atradermight make a set of rules stating that he will take a long position whenever the price of a

particular instrument closes above its 50-daymoving average, and shorting it whenever it drops below.

[edit]Combination with other market forecast methods

John Murphystates that the principal sources of information available to technicians are price, volume

andopen interest.[27]Other data, such as indicators andsentiment analysis, are considered secondary.
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al_network_softwarehttp://en.wikipedia.org/wiki/Technical_analysis#cite_note-25http://en.wikipedia.org/wiki/Technical_analysis#cite_note-23http://en.wikipedia.org/wiki/Technical_analysis#cite_note-23http://en.wikipedia.org/wiki/Fundamental_analysishttp://en.wikipedia.org/wiki/Technical_analysis#cite_note-21http://en.wikipedia.org/wiki/Technical_analysis#cite_note-21http://en.wikipedia.org/wiki/Function_approximationhttp://en.wikipedia.org/wiki/Artificial_intelligencehttp://en.wikipedia.org/wiki/Artificial_neural_networkhttp://en.wikipedia.org/w/index.php?title=Technical_analysis&action=edit&section=11http://en.wikipedia.org/w/index.php?title=Technical_analysis&action=edit&section=10


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However, many technical analysts reach outside pure technical analysis, combining other market forecast

methods with their technical work. One advocate for this approach isJohn Bollinger, who coined the

term rational analysisin the middle 1980s for the intersection of technical analysis and fundamental

analysis.[28]Another such approach, fusion analysis,[29]overlays fundamental analysis with technical, in an

attempt to improve portfolio manager performance.

Technical analysis is also often combined withquantitative analysisandeconomics. For example, neural

networks may be used to help identify intermarket relationships.[30]A few market forecasters combinefinancial

astrologywith technical analysis. Chris Carolan's article "Autumn Panics and Calendar Phenomenon", which

won the Market Technicians Association Dow Award for best technical analysis paper in 1998, demonstrates

how technical analysis and lunar cycles can be combined.[31]Calendar phenomena, such as theJanuary

effectin the stock market, are generally believed to be caused by tax and accounting related transactions, and

are not related to the subject offinancial astrology.

Investor and newsletter polls, and magazine cover sentiment indicators, are also used by technical analysts.[32]

[edit]Empirical evidence

Whether technical analysis actually works is a matter of controversy. Methods vary greatly, and different

technical analysts can sometimes make contradictory predictions from the same data. Many investors claim

that they experience positive returns, but academic appraisals often find that it has littlepredictive

power.[33]Modern studies may be more positive: of 95 modern studies, 56 concluded that technical analysis

had positive results, althoughdata-snooping biasand other problems make the analysis difficult.[7]Nonlinear

prediction usingneural networksoccasionally producesstatistically significantprediction results.

[34]

AFederalReserveworking paper[15]regardingsupport and resistancelevels in short-term foreign exchange rates "offers

strong evidence that the levels help to predict intraday trend interruptions," although the "predictive power" of

those levels was "found to vary across the exchange rates and firms examined".

Technical trading strategies were found to be effective in the Chinese marketplace by a recent study that

states, "Finally, we find significant positive returns on buy trades generated by the contrarian version of the

moving average crossover rule, the channel breakout rule, and the Bollinger band trading rule, after accounting

for transaction costs of 0.50 percent."[35]

An influential 1992 study by Brock et al. which appeared to find support for technical trading rules was tested

for data snooping and other problems in 1999;[36]the sample covered by Brock et al. was robust to data

snooping.

Subsequently, a comprehensive study of the question by Amsterdam economist Gerwin Griffioen concludes

that: "for the U.S., Japanese and most Western European stock market indices the recursive out-of-sample

forecasting procedure does not show to be profitable, after implementing little transaction costs. Moreover, for
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sufficiently high transaction costs it is found, by estimatingCAPMs, that technical trading shows no statistically

significant risk-corrected out-of-sample forecasting power for almost all of the stock market

indices."[10]Transaction costs are particularly applicable to "momentum strategies"; a comprehensive 1996

review of the data and studies concluded that even small transaction costs would lead to an inability to capture

any excess from such strategies.[37]

In a paper published in theJournal of Finance, Dr. Andrew W. Lo, director MIT Laboratory for Financial

Engineering, working with Harry Mamaysky and Jiang Wang found that "Technical analysis, also known as

"charting," has been a part of financial practice for many decades, but this discipline has not received the same

level of academic scrutiny and acceptance as more traditional approaches such asfundamental analysis. One

of the main obstacles is the highly subjective nature of technical analysisthe presence of geometric shapes in

historical price charts is often in the eyes of the beholder. In this paper, we propose a systematic and automatic

approach to technical pattern recognition using nonparametrickernel regression, and apply this method to a

large number of U.S. stocks from 1962 to 1996 to evaluate the effectiveness of technical analysis. By

comparing the unconditional empirical distribution of daily stock returns to the conditional distribution

conditioned on specific technical indicators such as head-and-shoulders or double-bottomswe find that over

the 31-year sample period, several technical indicators do provide incremental information and may have some

practical value."[38]In that same paper Dr. Lo wrote that "several academic studies suggest that ... technical

analysis may well be an effective means for extracting useful information from market prices."[39]Some

techniques such asDrummond Geometryattempt to overcome the past data bias by projecting support and

resistance levels from differing time frames into the near-term future and combining that with reversion to the

mean techniques.[40]

[edit]Efficient market hypothesis

Theefficient-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. EconomistEugene Famapublished the seminal paper on the EMH in the Journal of Financein 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."[41]EMH advocates say that if prices quickly reflect all relevant

information, no method (including technical analysis) can "beat the market." Developments which influence

prices occurrandomlyand are unknowable in advance.

Technicians say that EMH ignores the way markets work, in that many investors base their expectations on

past earnings or track record, for example. Because future stock prices can be strongly influenced by investor

expectations, technicians claim it only follows that past prices influence future prices.[42]They also point to

research in the field ofbehavioral 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
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behavior leads to predictable outcomes.[43]Author David Aronson says that the theory of behavioral finance

blends with the practice of technical analysis:

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.[42]

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).[44]Likewise, complete information is reflected in the price because all market participants bring

their own individual, but incomplete, knowledge together in the market.[44]

[edit]Random walk hypothesis

Therandom walk hypothesismay 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 bookA Random Walk Down Wall Street,

Princeton economistBurton Malkielsaid 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."[45]

In the late 1980s, professors Andrew Lo and Craig McKinlay published a paper which casts doubt on therandom walk hypothesis. In a 1999 response to Malkiel, Lo and McKinlay collected empirical papers that

questioned the hypothesis' applicability[46]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, an entirely separate concept from RWH.

Technicians say 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.[21][47]

Fundamental Analysis

What Does Fundamental AnalysisMean?A method of evaluating a security that entails attempting to measure its intrinsic value by examiningrelated economic, financial and other qualitative and quantitative factors. Fundamental analysts attemptto study everything that can affect the security's value, including macroeconomic factors (like the overalleconomy and industry conditions) and company-specific factors (like financial condition andmanagement).
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The end goal of performing fundamental analysis is to produce a value that an investor can compare withthe security's current price, with the aim of figuring out what sort of position to take with that security(underpriced = buy, overpriced = sell or short).

This method of security analysis is considered to be the opposite of technical analysis.

Investopedia explains Fundamental Analysis

Fundamental analysis is about using real data to evaluate a security's value. Although most analysts use

fundamental analysis to value stocks, this method of valuation can be used for just about any type of

security.

For example, an investor can perform fundamental analysis on a bond's value by looking at economic

factors, such as interest rates and the overall state of the economy, and information about the bond

issuer, such as potential changes in credit ratings. For assessing stocks, this method uses revenues,

earnings, future growth, return on equity, profit margins and other data to determine a company'sunderlying value and potential for future growth. In terms of stocks, fundamental analysis focuses on the

financial statements of the company being evaluated.

One of the most famous and successful fundamental analysts is the Oracle of Omaha, Warren

Buffett, who is well known for successfully employing fundamental analysis to pick securities. His abilities

have turned him into a billionaire.

What Does Technical AnalysisMean?A method of evaluating securities by analyzing statistics generated by market activity, such as past pricesand volume. Technical analysts do not attempt to measure a security's intrinsic value, but instead usecharts and other tools to identify patterns that can suggest future activity.

Watch: Fundamental Vs. TechnicalAnalysis

Investopedia explains Technical AnalysisTechnical analysts believe that the historical performance of stocks and markets are indications of futureperformance.

In a shopping mall, a fundamental analyst would go to each store, study the product that was being sold,and then decide whether to buy it or not. By contrast, a technical analyst would sit on a bench in the malland watch people go into the stores. Disregarding the intrinsic value of the products in the store, thetechnical analyst's decision would be based on the patterns or activity of people going into each store.
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Fundamental analysisFrom Wikipedia, the free encyclopedia

Financial markets

Public market

Exchange

Securities

Bond market

Fixed income

Corporate bond

Government bond

Municipal bond

Bond valuation

High-yield debt

Stock market

Stock

Preferred stock

Common stock

Registered share

Voting share

Stock exchange

Derivatives market

Securitization

Hybrid security
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Credit derivative

Futures exchange

OTC, non organized

Spot market

Forwards

Swaps

Options

Foreign exchange

Exchange rate

Currency

Other markets

Money market

Reinsurance market

Commodity market

Real estate market

Practical trading

Participants

Clearing house

Financial regulation

Financeseries

Banks and banking

Corporate finance

Personal finance

Public finance

vde

Fundamental analysis of a business involves analyzing itsfinancial statementsand health, its management

and competitive advantages, and itscompetitorsandmarkets. When applied tofuturesandforex, it focuses on
http://en.wikipedia.org/wiki/Credit_derivativehttp://en.wikipedia.org/wiki/Credit_derivativehttp://en.wikipedia.org/wiki/Futures_exchangehttp://en.wikipedia.org/wiki/Futures_exchangehttp://en.wikipedia.org/wiki/Over-the-counter_(finance)http://en.wikipedia.org/wiki/Over-the-counter_(finance)http://en.wikipedia.org/wiki/Spot_markethttp://en.wikipedia.org/wiki/Spot_markethttp://en.wikipedia.org/wiki/Forward_contracthttp://en.wikipedia.org/wiki/Forward_contracthttp://en.wikipedia.org/wiki/Swap_(finance)http://en.wikipedia.org/wiki/Swap_(finance)http://en.wikipedia.org/wiki/Option_(finance)http://en.wikipedia.org/wiki/Option_(finance)http://en.wikipedia.org/wiki/Foreign_exchange_markethttp://en.wikipedia.org/wiki/Exchange_ratehttp://en.wikipedia.org/wiki/Exchange_ratehttp://en.wikipedia.org/wiki/Currencyhttp://en.wikipedia.org/wiki/Currencyhttp://en.wikipedia.org/wiki/Money_markethttp://en.wikipedia.org/wiki/Money_markethttp://en.wikipedia.org/wiki/Reinsurance_markethttp://en.wikipedia.org/wiki/Reinsurance_markethttp://en.wikipedia.org/wiki/Commodity_markethttp://en.wikipedia.org/wiki/Commodity_markethttp://en.wikipedia.org/wiki/Real_estate_markethttp://en.wikipedia.org/wiki/Real_estate_markethttp://en.wikipedia.org/wiki/Trader_(finance)http://en.wikipedia.org/wiki/Financial_market_participantshttp://en.wikipedia.org/wiki/Financial_market_participantshttp://en.wikipedia.org/wiki/Clearing_house_(finance)http://en.wikipedia.org/wiki/Clearing_house_(finance)http://en.wikipedia.org/wiki/Financial_regulationhttp://en.wikipedia.org/wiki/Financial_regulationhttp://en.wikipedia.org/wiki/Financehttp://en.wikipedia.org/wiki/Financehttp://en.wikipedia.org/wiki/Bankhttp://en.wikipedia.org/wiki/Bankhttp://en.wikipedia.org/wiki/Corporate_financehttp://en.wikipedia.org/wiki/Corporate_financehttp://en.wikipedia.org/wiki/Personal_financehttp://en.wikipedia.org/wiki/Personal_financehttp://en.wikipedia.org/wiki/Public_financehttp://en.wikipedia.org/wiki/Public_financehttp://en.wikipedia.org/wiki/Template:Financial_marketshttp://en.wikipedia.org/wiki/Template:Financial_marketshttp://en.wikipedia.org/wiki/Template:Financial_marketshttp://en.wikipedia.org/wiki/Template_talk:Financial_marketshttp://en.wikipedia.org/wiki/Template_talk:Financial_marketshttp://en.wikipedia.org/wiki/Template_talk:Financial_marketshttp://en.wikipedia.org/w/index.php?title=Template:Financial_markets&action=edithttp://en.wikipedia.org/w/index.php?title=Template:Financial_markets&action=edithttp://en.wikipedia.org/w/index.php?title=Template:Financial_markets&action=edithttp://en.wikipedia.org/w/index.php?title=Template:Financial_markets&action=edithttp://en.wikipedia.org/wiki/Financial_statementshttp://en.wikipedia.org/wiki/Financial_statementshttp://en.wikipedia.org/wiki/Financial_statementshttp://en.wikipedia.org/wiki/Competitorshttp://en.wikipedia.org/wiki/Competitorshttp://en.wikipedia.org/wiki/Competitorshttp://en.wikipedia.org/wiki/Marketshttp://en.wikipedia.org/wiki/Marketshttp://en.wikipedia.org/wiki/Marketshttp://en.wikipedia.org/wiki/Futures_contracthttp://en.wikipedia.org/wiki/Futures_contracthttp://en.wikipedia.org/wiki/Futures_contracthttp://en.wikipedia.org/wiki/Foreign_exchange_markethttp://en.wikipedia.org/wiki/Foreign_exchange_markethttp://en.wikipedia.org/wiki/Foreign_exchange_markethttp://en.wikipedia.org/wiki/Foreign_exchange_markethttp://en.wikipedia.org/wiki/Futures_contracthttp://en.wikipedia.org/wiki/Marketshttp://en.wikipedia.org/wiki/Competitorshttp://en.wikipedia.org/wiki/Financial_statementshttp://en.wikipedia.org/w/index.php?title=Template:Financial_markets&action=edithttp:/

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Portfolio Manage