A Revision 0n FA & TA...Boring stuff.

F A = Fundamental Analysis: Fundamental analysis
Fundamental analysis of a business involves analyzing its income statement, financial statements and health, its management and competitive advantages, and its competitors and markets.

The analysis is performed on historical and present data, but with the goal to make financial projections. There are several possible objectives:

to calculate a company's credit risk,
to make projection on its business performance,
to evaluate its management and make internal business decisions,
to make the company's stock valuation and predict its probable price evolution.
Contents
1 Two analytical models
2 Use by different portfolio styles
3 Top-down and Bottom-up
4 Procedures
5 Criticisms

Two analytical models
When the objective of the analysis is to determine what stock to buy and at what price, there are two basic methodologies.

Fundamental analysis maintains that markets may misprice a security in the short run but that the "correct" price will eventually be reached. Profits can be made by trading the mispriced security and then waiting for the market to recognize its "mistake" and reprice the security.

Technical analysis maintains that all information is reflected already in the stock price, so fundamental analysis is a waste of time. Trends 'are your friend' and sentiment changes predate and predict trend changes. Investors' emotional responses to price movements lead to recognizable price chart patterns. Technical analysis does not care what the 'value' of a stock is. Their price predictions are only extrapolations from historical price patterns.
Investors can use both these different but somewhat complementary methods for stock picking. Many fundamental investors use technical for deciding entry and exit points. Many technical investors use fundamentals to limit their universe of possible stock to 'good' companies.

The choice of stock analysis is determined by the investor's belief in the different paradigms for "how the stock market works". See the discussions at efficient market hypothesis , random walk hypothesis, Capital Asset Pricing Model, Fed model Theory of Equity Valuation, and behavioral finance. Use by different portfolio styles Investors may use fundamental analysis within different portfolio management styles.
Buy and hold investors believe that latching onto good businesses allows the investor's asset to grow with the business. Fundamental analysis lets them find 'good' companies, so they lower their risk and probability of wipe-out.
Managers may use fundamental analysis to correctly value 'good' and 'bad' companies. Even 'bad' company's stock goes up and down, creating opportunities for profits.

Contrarian’s investors distinguish "in the short run, the market is a voting machine, not a weighing machine"[1]. Fundamental analysis allows you to make your own decision on value, and ignore the market.
Value investors restrict their attention to under-valued companies, believing that 'it's hard to fall out of a ditch'. The value comes from fundamental analysis.
Managers may use fundamental analysis to determine future growth rates for buying high priced growth stocks.
Managers may also include fundamental factors along with technical factors into computer models (quantitative analysis).

Top-down and Bottom-up
Investors can use either a top-down or bottom-up approach.

The top-down investor starts his analysis with global economics, including both international and national economic indicators, such as GDP growth rates, inflation, interest rates, exchange rates, productivity, and energy prices. He narrows his search down to regional/industry analysis of total sales, price levels, the effects of competing products, foreign competition, and entry or exit from the industry. Only then does he narrow his search to the best business in that area.
The bottom-up investor starts with specific businesses, regardless of their industry/region.

Procedures
The analysis of a business' health starts with financial statement analysis that includes ratios. It looks at dividends paid, operating cash flow, new equity issues and capital financing. The earnings estimates and growth rate projections published widely by Thomson Financial and others can be considered either 'fundamental' (they are facts) or 'technical' (they are investor sentiment) based on your perception of their validity.

The determined growth rates (of income and cash) and risk levels (to determine the discount rate) are used in various valuation models. The foremost is the discounted cash flow model, which calculates the present value of the future
Dividends received by the investor, along with the eventual sale price. (Gordon model) earnings of the company or cash flows of the company.

The simple model commonly used is the Price/Earnings ratio. Implicit in this model of a perpetual annuity (Time value of money) is that the 'flip' of the P/E is the discount rate appropriate to the risk of the business. The multiple accepted is adjusted for expected growth (that is not built into the model).

Growth estimates are incorporated into the PEG ratio but the math does not hold up to analysis. [Neutrality disputed] Its validity depends on the length of time you think the growth will continue.

Computer modeling of stock prices has now replaced much of the subjective interpretation of fundamental data (along with technical data) in the industry. Since about year 2000, with the power of computers to crunch vast quantities of data, a new career has been invented. At some funds the manager's decisions have been replaced by proprietary mathematical models. [Citation needed]

Criticisms
Some economists such as Burton Malkiel suggest that neither fundamental analysis nor technical analysis is useful in outperforming the markets [2].

T.A. =Technical Analysis

Technical analysis is the study of past financial market data, primarily through the use of charts, to forecast price trends and make investment decisions. [1] In its purest form, technical analysis considers only the actual price behavior of the market or instrument, based on the premise that price reflects all relevant factors before an investor becomes aware of them through other channels.

Technical analysis is widely used among traders and financial professionals, and some studies say its use is more widespread than is "fundamental" analysis in the foreign exchange market.[2][3] Academics such as Eugene Fama say the evidence for technical analysis is sparse and is refuted by the efficient market hypothesis,[4][5] yet some Federal Reserve and academic studies include evidence that supports technical analysis.[6][7][8] MIT finance professor Andrew Lo argues that "several academic studies suggest that technical analysis may well be an effective means for extracting useful information from market prices."[9] But as Burton Malkiel argues, "Technical analysis is anathema to the academic world."[10]

General description

Technical analysts (or technicians) identify non-random price patterns and trends in financial markets and attempt to exploit those patterns.[1] While technicians use various methods and tools, the study of price charts is primary. Technicians especially search for archetypal patterns, such as the well-known head and shoulders reversal pattern, and also study such indicators as price, volume, and moving averages of the price. Many technical analysts also follow indicators of investor psychology (market sentiment).

Technicians seek to forecast price movements such that large gains from successful trades exceed more numerous but smaller losing trades, producing positive returns in the long run through proper risk control and money management.

There are several schools of technical analysis. Adherents of different schools (for example, candlestick charting, Dow Theory, and Elliott wave theory) may ignore the other approaches, yet many traders combine elements from more than one school. Technical analysts use judgment gained from experience to decide which pattern a particular instrument reflects at a given time, and what the interpretation of that pattern should be. Technical analysts may disagree among themselves over the interpretation of a given chart.

Technical analysis is frequently contrasted with fundamental analysis; the study of economic factors that some analysts say can influence prices in financial markets. Pure technical analysis holds that prices already reflect all such influences before investors are aware of them, hence the study of price action alone. Some traders use technical or fundamental analysis exclusively, while others use both types to make trading decisions.

History
The principles of technical analysis derive from the observation of financial markets over hundreds of years.[citation needed] The oldest known example of technical analysis was a method used by Japanese traders as early as the 18th century,[citation needed] which evolved into the use of candlestick techniques, and is today a main charting tool.[11][12]
Dow Theory is based on the collected writings of Dow Jones co-founder and editor Charles Dow, and inspired the use and development of modern technical analysis from the end of the 19th century. Modern technical analysis considers Dow Theory its cornerstone. [13]

Many more technical tools and theories have been developed and enhanced in recent decades, with an increasing emphasis on computer-assisted techniques.

Principles of technical analysis
Technicians say that a market's price reflects all relevant information, so their analysis looks more at "internals" than at "externals" such as news events. Price action also tends to repeat itself because investors collectively tend toward patterned behavior -- hence technicians' focus on identifiable trends and conditions.

Market action discounts everything
Based on the premise that all relevant information is already reflected by prices, technical analysts believe it is redundant to do fundamental analysis -- they say news and news events do not significantly influence price, and cite supporting research such as the study by Cutler, Poterba, and Summers titled "What Moves Stock Prices?"

On most of the sizable return days [large market moves] the information that the press cites as the cause of the market move is not particularly important. Press reports on adjacent days also fail to reveal any convincing accounts of why future profits or discount rates might have changed. Our inability to identify the fundamental shocks that accounted for these significant market moves is difficult to reconcile with the view that such shocks account for most of the variation in stock returns. [14]

Prices move in trends

Technical analysts believe that prices trend. Technicians say that markets trend up, down, or sideways (flat). This basic definition of price trends is the one put forward by Dow Theory. [1]

AOL Time Warner price action.
An example of a security that had an apparent trend is AOL from November 2001 through August 2002. A technical 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.[15] In other words, each time the stock edged 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.

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 does repeat itself so often, technicians believe that recognizable (and predictable) price patterns will develop on a chart. [1]

Technical analysis is not limited to charting, yet is always concerned with price trends. For example, many technicians monitor surveys of investor sentiment. These surveys gauge the attitude of market participants, specifically whether they are bearish or bullish. 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 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 are bullish 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 of contrarian trading.

Criticism
The Wall Street Journal Europe states "Whether technical analysis is really useful ... is a matter of some dispute on Wall Street. Some investors believe that it is impossible to forecast the market's ups and downs. Academic studies have shown that when most people, professionals and amateurs alike, try to move money in and out of stocks to beat market fluctuations, they tend to wind up with losses."[16] The same article shows how several technical analysts can simultaneously make contradictory predictions.
Lack of evidence
Critics of technical analysis include well known fundamental analysts. For example, Peter Lynch once commented, "Charts are great for predicting the past." Warren Buffett has said, "I realized technical analysis didn't work when I turned the charts upside down and didn't get a different answer" and "If past history was all there was to the game, the richest people would be librarians."[1]

Some academic studies say technical analysis has little predictive power, but other studies say it may produce excess returns. For example, measurable forms of technical analysis, such as non-linear prediction using neural networks, have been shown to occasionally produce statistically significant prediction results.[17] A Federal Reserve working paper[7] regarding support and resistance levels 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."

Cheol-Ho Park and Scott H. Irwin reviewed 95 modern studies on the profitability of technical analysis and said 56 of them find positive results, 20 obtain negative results, and 19 indicate mixed results: "Despite the positive evidence...most empirical studies are subject to various problems in their testing procedures, e.g., data snooping, ex post selection of trading rules or search technologies, and difficulties in estimation of risk and transaction costs. Future research must address these deficiencies in testing in order to provide conclusive evidence on the profitability of technical trading strategies."[18]

However, 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 sufficiently high transaction costs it is found, by estimating CAPMs, that technical trading shows no statistically significant risk-corrected out-of-sample forecasting power for almost all of the stock market indices."[5]

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." [19] EMH advocates say that if prices quickly reflect all relevant information, no method (including technical analysis) can "beat the market." Developments which influence prices occur randomly and are unknowable in advance.

Technicians say that EMH ignores the way markets work, in that many investors base their expectations on past earnings, track record, etc. Because future stock prices can be strongly influenced by investor expectations, technicians claim it only follows that past prices influence future prices. [20] 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. [21] 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. [20]

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).[22] Likewise, complete information is reflected in the price because all market participants bring their own individual, but incomplete, knowledge together in the market.[22]

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 regularity is known to market participants, people will act in such a way that prevents it from happening in the future." [23]

Technicians say the EMH and Random Walk theories both ignore the realities of markets, in that participants are not completely rational (they can be greedy, overly risky, etc.) and that current price moves are not independent of previous moves (technicians point to charts similar to AOL above.)[15][24] Critics reply that one can find virtually any chart pattern after the fact, but that this does not prove that such patterns are predictable. Technicians maintain that both theories would also invalidate numerous other trading strategies such as index arbitrage, statistical arbitrage and many other trading systems. [20]

Industry
Globally, the industry is represented by The International Federation of Technical Analysts (IFTA). In the United States the industry is represented by two national organizations: the Market Technicians Association (MTA), and the American Association of Professional Technical Analysts (AAPTA). In Canada the industry is represented by the Canadian Society of Technical Analysts.

Use of technical analysis
Many traders say that trading in the direction of the trend is the most effective means to be profitable in financial or commodities markets. John W. Henry, Larry Hite, Ed Seykota, Richard Dennis, William Eckhardt, Victor Sperandeo, Michael Marcus and Paul Tudor Jones (some of the so-called Market Wizards in the popular book of the same name by Jack D. Schwager) have each amassed massive fortunes via the use of technical analysis and its concepts. George Lane, a technical analyst, coined one of the most popular phrases on Wall Street, "The trend is your friend!"

Many non-arbitrage algorithmic trading systems rely on the idea of trend-following, as do many hedge 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 (see algorithmic trading article for an overview).

Systematic trading and technical analysis

Neural networks
Since the early 90's when the first practically usable types emerged, artificial neural networks (ANNs) have rapidly grown in popularity. They are artificial intelligence adaptive software systems that have been inspired by how biological neural networks work. Their use comes in because they can learn to detect complex patterns in data. In mathematical terms, they are universal non-linear function approximators[25] [26] 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 to fundamental analysis as the variables used in fundamental analysis can be used as input.

In addition, as ANNs are essentially non-linear statistical models, their accuracy and prediction capabilities can be both mathematically and empirically tested. In various studies neural networks used for generating trading signals have significantly outperformed buy-hold strategies as well as traditional linear technical analysis methods.[27] [28] [29]

While the advanced mathematical nature of such adaptive systems have kept neural networks for financial analysis mostly within academic research circles, in recent years more user friendly neural network software has made the technology more accessible to traders.

Rule-based trading
Rule-based trading is an approach to make one's trading plans by strict and clear-cut rules. Unlike some other technical methods or most fundamental analysis, it defines a set of rules that determines all trades, leaving minimal discretion.

For instance, a trader might make a set of rules stating that he will take a long position whenever the price of a particular instrument closes above its 50-day moving average, and shorting it whenever it drops below.

Charting terms and indicators
Widely-known technical analysis concepts include:

Accumulation/distribution index based on the close within the day's range
Average true range - averaged daily trading range
Bollinger bands - a range of price volatility
Breakout - when a price passes through and stays above an area of support or resistance
Commodity Channel Index - identifies cyclical trends
Elliott wave principle and the golden ratio to calculate successive price movements and retracements
Hikkake Pattern - pattern for identifying reversals and continuations
MACD - moving average convergence/divergence
Momentum - the rate of price change
Money Flow - the amount of stock traded on days the price went up
Moving average - lags behind the price action
On-balance volume - the momentum of buying and selling stocks
PAC charts - two-dimensional method for charting volume by price level
Parabolic SAR - Wilder's trailing stop based on prices tending to stay within a parabolic curve during a strong trend
Pivot point - derived by calculating the numerical average of a particular currency's or stock's high, low and closing prices
Point and figure charts - charts based on price without time
Relative Strength Index (RSI) - oscillator showing price strength
Resistance - an area that brings on increased selling
Rahul Mohindar Oscillator - a trend indentifying indicator
Stochastic oscillator, close position within recent trading range
Support - an area that brings on increased buying
Trend line - a sloping line of support or resistance
Trix - an oscillator showing the slope of a triple-smoothed exponential moving average, developed in the 1980s by Jack Hutson

My view is that you cannot wholly rely on TA. Some input from FA is necessary to select which stock to invest.TA will come in useful if you are a short term investor or punter as some would like to call it. If you want to use TA, you'll need a lot of practice to see which indicators among the huge number of them that gives you the desired result. Compare your forecasting based on TA and what really happens and then you get the hang of it TA and charting goes hand in hand and studying patterns is useful.

Japanese Candlesstick Charting Techniques is useful and I like it. If you like to learn more get hold the this book"Japanese Candlestick Charting Techniques" by Steve Nison published by New York Institute of Finance.

I always like to compare TA & Charting to brass balls use by some people to exercise their hand and fingers. The more you use it, the brighter it becomes.

Cheers