Concepts

Average True Range

Average True Range (ATR) is a technical analysis indicator developed by J. Welles Wilder, based on trading ranges smoothed by an N-day exponential moving average.

The range of a day's trading is simply high − low. The true range extends it to yesterday's closing price if it was outside of today's range:

true range = max(high,close_prev) − min(low,close_prev)

The average true range is then an N-day exponential moving average of the true range values. Wilder recommended a 14-period smoothing. Note this is by his reckoning of EMA periods (see the EMA article on that), meaning an α=2/(1+14)=0.1333.

The idea of ranges is that they show the commitment or enthusiasm of traders. Large or increasing ranges suggest traders prepared to continue to bid up or sell down a stock through the course of the day. Decreasing range suggests waning interest.

Chart pattern

A chart pattern is a pattern that is formed within a chart when prices are graphed. In stock and commodity markets trading, chart pattern studies play a large role during technical analysis. When data is plotted there is usually a pattern which naturally occurs and repeats over a period of time. Chart patterns are used as either reversal or continuation signals.

Some people claim that by recognizing chart patterns they are able to predict future stock prices and profit by this prediction; other people respond by quoting "past performance is no guarantee of future results" and argue that chart patterns are merely illusions created by people's subconscious. Certain theories of economics hold that if there were a way to predict future stock prices and profit by it then when enough people used these techniques they would become ineffective and cease to be profitable. On the other hand, if you can predict what other people will predict the market to do then that would be valuable information.

Coppock curve

The Coppock curve or Coppock indicator is a technical analysis indicator for long-term stock market investors created by E.S.C. Coppock, first published in Barron's magazine in October 15, 1962.

The indicator is designed for use on a monthly time scale. It's the sum of a 14-month rate of change and 11-month rate of change, smoothed by a 10-period weighted moving average.

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Coppock, the founder of Trendex Research in San Antonio, Texas, was an economist. He had been asked by the Episcopal church to identify buying opportunities for long-term investors. He thought market downturns were like bereavements and required a period of mourning. He asked the church bishops how long that normally took for people, their answer was 11 to 14 months and so he used those periods in his calculation.

A buy signal is generated when the indicator is below zero and turns upwards from a trough. No sell signals are generated (that not being its design). The indicator is trend-following, and based on averages, so by its nature it doesn't pick a market bottom, but rather shows when a rally has become established.

Coppock designed the indicator (originally called the "Trendex Model") for the S&P 500 index, and it's been applied to similar stock indexes like the Dow Jones Industrial Average. It's not regarded as well-suited to commodity markets, since bottoms there are more rounded than the spike lows found in stocks.

Dead cat bounce

A dead cat bounce is a firugative term used by traders in the finance industry to describe a pattern wherein a spectacular decline in the price of a stock is immediately followed by a moderate and temporary rise before resuming its downward movement, with the connotation that the rise was not an indication of improving circumstances in the fundamentals of the stock. It is derived from the notion that "even a dead cat will bounce if it falls from a great height".

The phrase has been used on the trading floors for many years. However the earliest recorded use of the phrase dates from 1985 when the Singaporean and Malaysian stock markets bounced back after a hard fall during the recession of that year. Journalist Christoper Sherwel of the Financial times reported a stock broker as saying the market rise was a "dead cat bounce". It has also been used in reference to political polling numbers.

The reasons for such a bounce can be technical, as investors may have standing orders to buy shorted stocks if they fall below a certain level or to cover certain option positions. Once those limits are reached, the buy orders are activated and the sudden rise in demand causes the price of the stock to rise as well. The bounce may also be the result of speculation. Since bounces often occur, traders buy into what they hope is the bottom of the market, expecting a bounce and thereby reaping a quick profit. Thus, the very act of anticipating a bounce can create and magnify it.

A market rise after a sharp fall can only really be seen to be a "dead cat bounce" with the benefit of hindsight. If the stock starts to fall again in the following days and weeks, then it was a true dead cat bounce. If the market starts to climb again after the first short bounce, then the continued rise in price action would be considered a trend reversal and not a dead cat bounce. Since this distinction only becomes obvious in hindsight, the evaluation may vary depending upon the initial and final points of reference.

Elliott wave principle

The Elliott wave principle is a form of technical analysis that attempts to forecast trends in the financial markets and other collective activities. It is named after Ralph Nelson Elliott (1871–1948), an accountant who developed the concept in the 1930s: he proposed that market prices unfold in specific patterns, which practitioners today call Elliott waves. Elliott published his views of market behavior in the book The Wave Principle (1938), in a series of articles in Financial World magazine in 1939, and most fully in his final major work, Nature’s Laws – The Secret of the Universe (1946). Elliott argued that because humans are themselves rhythmical, their activities and decisions could be predicted in rhythms, too. Critics argue that the Elliott wave principle is pseudoscientific and contradicts the efficient market hypothesis.

Hikkake Pattern

The Hikkake Pattern (or Hikkake), is a technical analysis pattern used for determining market turning-points and continuations. It is a simple pattern that can be observed in market price data, using traditional bar chart, or Japanese Candlestick Chart.

The phrase "Hikkake" is a Japanese verb which means to "trick" or "ensnare." The pattern is comprised of a measurable period of rest and volatility contraction in the market, followed by a relatively brief price move that encourages unsuspecting traders and investors to adopt a false assumption regarding the likely future direction of price. Some technical analysts may also refer to the hikkake pattern as an "inside day false breakout," however this term has never been formally adopted. The pattern, once formed, yields its own set of trading parameters for the time and price of market entry, the dollar risk amount (i.e., where to place protective stops), and the expected profit target. The pattern is not meant as a stand alone "system" for market speculation, but rather as an ancillary technique to traditional technical and fundamental market analysis methods.

Due to its popularity among institutional traders, the hikkake pattern has been adopted for use by INTSTREAM, the Nordic power trading software company, in their E2 Energy Market Analysis Platform.

Growing interest in the hikkake pattern among traders and investors has also spawned attention from various book authors. See: "Technical Analysis: The Complete Resource for Financial Market Technicians" by Charles D. Kirkpatrick and Julie R. Dahlquist, and "Long/Short Market Dynamics: Trading Strategies for Today's Markets" by Clive M. Corcoran.

The hikkake pattern was first discovered and introduced to the financial community through a series of published articles written by technical analyst Daniel L. Chesler, CMT .

Momentum (technical analysis)

Momentum and rate of change (ROC) are simple technical analysis indicators showing the difference between today's closing price and the close N days ago. Momentum is the absolute difference:

Rate of change scales by the old close, so as to represent the increase as a fraction,

"Momentum" in general refers to prices continuing to trend. The momentum and ROC indicators show trend by remaining positive while an uptrend is sustained, or negative while a downtrend is sustained.

A crossing up through zero may be used as a signal to buy, or a crossing down through zero as a signal to sell. How high (or how low when negative) the indicators get shows how strong the trend is.

The way momentum shows an absolute change means it shows for instance a $3 rise over 20 days, whereas ROC might show that as 0.25 for a 25% rise over the same period. One can choose between looking at a move in dollar terms, relative point terms, or proportional terms. The zero crossings are the same in each, of course, but the highs or lows showing strength are on the respective different bases.

Point and figure chart

Point and figure is a charting technique used in technical analysis, a form of heterodox economics used to attempt to predict financial market prices. Point and figure charting is unique in that it does not plot price against time as all other techniques do. Instead in plots price against changes in direction by plotting a column of Xs as the price rises and a column of Os as the price falls.

Types of Charts

Open-high-low-close chart

An open-high-low-close chart (also OHLC chart, or simply bar chart) is a type of chart typically used to illustrate movements in the price of a financial instruments over time. Each vertical line on the chart shows the price range (the highest and lowest prices) over one unit of time, e.g. one day or one hour. Tick mark project from each side of the line indicating the opening price (e.g. for a daily bar chart this would be the starting price for that day) on the left, and the closing price for that time period on the right. The bars may be shown in different hues depending on whether prices rose or fell in that period.

The Japanese candlestick chart is another way of displaying market price data, with the opening and closing prices defining a rectangle within the range for each time unit. Both charts show the exact same data, i.e. the opening, high, low, and closing prices during a particular time frame. Some traders find the candlestick chart easier to read.

Candlestick chart

A candlestick chart is a style of bar-chart used primarily to describe price movements of a security (finance), derivative, or currency over time.

It is a combination of a line-chart and a bar-chart, in that each bar represents the range of price movement over a given time interval. It is most often used in technical analysis of equity and currency price patterns. They appear superficially similar to error bars, but are unrelated.

Line chart

A line chart or line graph is a type of graph created by connecting a series of data points together with a line.

Charting terms and indicators

Types of Charts

• OHCL - Open High Low Close charts plot the high and low of the price movement vertically and the open and close horizontally. Used to graph range and outliers.
• Cnadlestick Chart- Similar to OHLC, but open and close are filled. Often Black or Red candles represent a close lower than the open. While White, Green or Blue candles represent a close higher than the open.
• Line chart- Connects each closing interval together on a line

Concepts

• Average true range- averaged daily trading range, adjusted for price gaps
• Chart pattern
  
• Coppock curve - Edwin coppock developed the Coppock Indicator to identify the commencement of bull markets
  
• Dead cat bounce- the phenomenon whereby a spectacular decline in the price of a stock is immediately followed by a moderate and temporary rise before resuming its downward movement
• Elliott wave principle and the golden ratio to calculate successive price movements and retracements
• Hikkake pattern- pattern for identifying reversals and continuations
• Momentum- the rate of price change
• Point and figure charts - charts based on price without time

Overlays

Overlays are generally superimposed over the main price chart.

• Resistance - an area that brings on increased selling
• Support- an area that brings on increased buying
• Breakout - when a price passes through and stays above an area of support or resistance
• Trend line - a sloping line of support or resistance
• Channel - a pair of parallel trend lines
• Moving average - lags behind the price action but filters out short term movements
• Bollinger bands - a range of price volatility
• Pivot point- derived by calculating the numerical average of a particular currency's or stock's high, low and closing prices

Price-based indicators

These indicators are generally shown below or above the main price chart.

• Accumulation/distribution index—based on the close within the day's range
• Advance decline line — a popular indicator of market breadth
• Average directional index — a widely used indicator of trend strength
• Commodity channel index - identifies cyclical trends
• MACD - moving average convergence/divergence
• Parabolic SAR- Wilder's trailing stop based on prices tending to stay within a parabolic curve during a strong trend
• Relative Strength Index (RSI)- oscillator showing price strength
• Stochastic oscillator, close position within recent trading range
• Trix - an oscillator showing the slope of a triple-smoothed exponential moving average, developed in the 1980s by Jack Hutson

Volume based indicators

• Money flow - the amount of stock traded on days the price went up
• On- Balance volume - the momentum of buying and selling stocks
• PAC Charts- two-dimensional method for charting volume by price level

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." In a 1999 response to Malkiel, Andrew Lo and Craig McKinlay collected empirical papers that questioned the hypothesis' applicability 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.

Technicians say 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. 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.

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." 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. The vast majority of academic papers find that technical trading rules, after consideration for trading costs, are not profitable.

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. 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. 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.

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

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 little predictive power. Modern studies may be more positive, however –- of 95 modern studies, 56 concluded that technical analysis had positive results, although data snooping and other problems make the analysis difficult. Nonlinear prediction using neural networks occasionally produces statistically significant prediction results. A Federal Reserve working paper 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."

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." Nauzer J. Balsara, Gary Chen and Lin Zheng The Chinese Stock Market: An Examination of the Random Walk Model and Technical Trading Rule

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."

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; 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 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." 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.

In a paper published in the Journal 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 as fundamental analysis. One of the main obstacles is the highly subjective nature of technical analysis---the 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 nonparametric kernel 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-bottoms---we find that over the 31-year sample period, several technical indicators do provide incremental information and may have some practical value." 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.

Combination with other market forecast methods

John Murphy says that the principal sources of information available to technicians are price, volume and open interest. Other data, such as indicators and sentiment analysis, are considered secondary.

However, many technical analysts reach outside pure technical analysis, combining other market forecast methods with their technical work. One advocate for this approach is John Bollinger, who coined the term rational analysis in the middle 1980s for the intersection of technical analysis and fundamental analysis. Another such approach, fusion analysis, overlays fundamental analysis with technical, in an attempt to improve portfolio manager performance.

Technical analysis is also often combined with quantitative analysis and economics. For example, neural networks may be used to help identify intermarket relationships. A few market forecasters combine financial astrology with 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. It is worth noting, however, that some of the calendar related phenomena, such as the January effect in the stock market, have been associated with tax and accounting related reasons.

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

Systematic trading

Neural networks

Since the early 1990s 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. They are used because they can learn to detect complex patterns in data. In mathematical terms, they are universal function approximators, 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.

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.

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 friendly neural networks sofware has 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.

Rule-based trading

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, 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 averages, and shorting it whenever it drops below.

Use

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 Markets 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.

Industry

Globally, the industry is represented by the International Federation of Technical Analysts (IFTA). In the United States, there are two national organizations: the Market 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 Fransisco (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. Additional major professional technical analysis organizations are noted in the External Links section 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. The Market Technicians Association (MTA) has published a Body of Knowledge and the International Federation of Technical Analysts and the Nippon Technical Analysis Association are reported to be working on knowledge base projects.

Principles

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, pure 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.

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.

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. 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 repeats itself so often, technicians believe that recognizable (and predictable) price patterns will develop on a chart.

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 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.

History

The principles of technical analysis derive from the observation of financial markets over hundreds of years. The oldest known example of technical analysis was a method developed by Homma Munehisa during early 18th century which evolved into the use of candlestick techniques, and is today a main charting tool.

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. Other pioneers of analysis techniques include Ralph Nelson Elliot and William Delbert Gann who developed their respective techniques in the early 20th century.

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

General description

Technical analysts seek to identify price patterns and trends in financial markets and attempt to exploit those patterns. 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 or double top reversal patterns, study indicators such as moving averages, and look for forms such as lines of support, resistance, channels, and more obscure formations such as flags, pennants or balance days.

Technical analysts also extensively use indicators, which are typically mathematical transformations of price or volume. These indicators are used to help determine whether an asset is trending, and if it is, its price direction. Technicians also look for relationships between price, volume and, in the case of futures, open interest. Examples include the relative strength index, and MACD. Other avenues of study include correlations between changes in options (implied volatility) and put/call ratios with price. Other technicians include sentiment indicators, such as Put/Call ratios and Implied Volatility in their analysis.

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 Elliot 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 analysis is frequently contrasted with fundamental analysis, the study of economic factors that influence prices in financial markets. 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.

Titles: Chartists and Technical analysts

Users of technical analysis are most 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 the term chartist has become rare.

Technical analysis

Technical analysis is a security analysis discipline for forecasting the future direction of prices through the study of past market data, primarily price and volume. In its purest form, technical analysis considers only the actual price and volume behavior of the market or instrument. Technical analysts may employ models and trading rules based on price and volume transformations, such as the relatives strength index, moving averages, regressions, inter-market and intra-market price correlations, cycles or, classically, through recognition of chart patterns.

Technical analysis stands in distinction to fundamental analysis. Technical analysis "ignores" the actual nature of the company, market, currency or commodity and is based solely on "the charts," that is to say price and volume information, whereas fundamental analysis does look at the actual facts of the company, market, currency or commodity. For example, any 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 active day traders, market makers, and pit traders. In the 1960s and 1970s it was widely dismissed by academics. In a recent review, Irwin and Park 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 as data snooping so that the evidence in support of technical analysis was inconclusive; it is still considered by many academics to be psedoscience. Academics such as Eugene Fama say the evidence for technical analysis is sparse and is inconsistent with the weak form of the efficient market hypothesis. Users hold that even if technical analysis cannot predict the future, it helps to identify trading opportunities.

In the foreign exchange markets, its use may be more widespread than fundamental analysis. While some isolated studies have indicated that technical trading rules might lead to consistent returns in the period prior to 1987, most academic work has focused on the nature of the anomalous position of the foreign exchange market. It is speculated that this anomaly is due to central bank intervention. 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.

Speculation

Controversy about currency speculators and their effect on currency devaluations and national economies recurs regularly. Nevertheless, economists including Milton Friedman have argued that speculators ultimately are a stabilizing influence on the market and perform the important function of providing a market for hedgers and transferring risk from those people who don't wish to bear it, to those who do. Other economists such as Joseph Stiglitz consider this argument to be based more on politics and a free market philosophy than on economics.

Large hedge funds and other well capitalized "position traders" are the main professional speculators. According to some economists, individual traders could act as "noise traders" and have a more destabilizing role than larger and better informed actors.

Currency speculation is considered a highly suspect activity in many countries. While investment in traditional financial instruments like bonds or stocks often is considered to contribute positively to economic growth by providing capital, currency speculation does not; according to this view, it is simply gambling that often interferes with economic policy. For example, in 1992, currency speculation forced the Central Bank of Sweden to raise interest rates for a few days to 500% per annum, and later to devalue the krona. Former Malaysian Prime Minister Mahathir Mohamad is one well known proponent of this view. He blamed the devaluation of the Malaysian ringgit in 1997 on George Soros and other speculators.

Gregory J. Millman reports on an opposing view, comparing speculators to "vigilantes" who simply help "enforce" international agreements and anticipate the effects of basic economic "laws" in order to profit.

In this view, countries may develop unsustainable financial bubbles or otherwise mishandle their national economies, and foreign exchange speculators allegedly made the inevitable collapse happen sooner. A relatively quick collapse might even be preferable to continued economic mishandling. Mahathir Mohamad and other critics of speculation are viewed as trying to deflect the blame from themselves for having caused the unsustainable economic conditions. Given that Malaysia recovered quickly after imposing currency controls directly against International Monetary Fund advice, this view is open to doubt.

Financial instruments

Spot

A spot transaction is a two-day delivery transaction (except in the case of trades between the US Dollar, Canadian Dollar, Turkish Lira and Russian Ruble, which settle the next business day), as opposed to the futures contract, which are usually three months. This trade represents a “direct exchange” between two currencies, has the shortest time frame, involves cash rather than a contract; and interest is not included in the agreed-upon transaction. The data for this study come from the spot market. Spot transactions has the second largest turnover by volume after Swap transactions among all FX transactions in the Global FX market. NNM

Forward

One way to deal with the foreign exchange risk is to engage in a forward transaction. In this transaction, money does not actually change hands until some agreed upon future date. A buyer and seller agree on an exchange rate for any date in the future, and the transaction occurs on that date, regardless of what the market rates are then. The duration of the trade can be a one day, a few days, months or years. Usually the date is decided by both parties.

Future

Foreign currency futures are exchange traded forward transactions with standard contract sizes and maturity dates — for example, $1000 for next November at an agreed rate. Futures are standardized and are usually traded on an exchange created for this purpose. The average contract length is roughly 3 months. Futures contracts are usually inclusive of any interest amounts.

Swap

The most common type of forward transaction is the currency swap. In a swap, two parties exchange currencies for a certain length of time and agree to reverse the transaction at a later date. These are not standardized contracts and are not traded through an exchange.

Option

A foreign exchange option (commonly shortened to just FX option) is a derivative where the owner has the right but not the obligation to exchange money denominated in one currency into another currency at a pre-agreed exchange rate on a specified date. The FX options market is the deepest, largest and most liquid market for options of any kind in the world..

Exchange-Traded Fund

Exchange-traded funds (or ETFs) are open ended investment companies that can be traded at any time throughout the course of the day. Typically, ETFs try to replicate a such as the stock market index such as the S&P 500 (e.g., SPY), but recently they are now replicating investments in the currency markets with the ETF increasing in value when the US Dollar weakens versus a specific currency, such as the Euro. Certain of these funds track the price movements of world currencies versus the US Dollar, and increase in value directly counter to the US Dollar, allowing for speculation in the US Dollar for US and US Dollar denominated investors and speculators.

Algorihmic trading in foreign exchange

Electronic tradingis growing in the FX market, and algorithmic trading is becoming much more common. According to financial consultancy Celent estimates, by 2008 up to 25% of all trades by volume will be executed using algorithm, up from about 18% in 2005.

Exchange rate

In finance, the exchange rates (also known as the foreign-exchange rate, forex rate or FX rate) between two currencies specifies how much one currency is worth in terms of the other. It is the value of a foreign nation’s currency in terms of the home nation’s currency. For example an exchange rate of 91 Japanese yen (JPY, ¥) to the United States dollar (USD, $) means that JPY 91 is worth the same as USD 1. The foreign exchange market is one of the largest markets in the world. By some estimates, about 3.2 trillion USD worth of currency changes hands every day.

The spot exchange rate refers to the current exchange rate. The forward exchange rate refers to an exchange rate that is quoted and traded today but for delivery and payment on a specific future date.

Quotations

An exchange system quotation is given by stating the number of units of "quote currency" (price currency, payment currency) that can be exchanged for one unit of "base currency" (unit currency, transaction currency). For example, in a quotation that says the EUR/USD exchange rate is 1.4320 (1.4320 USD per EUR), the quote currency is USD and the base currency is EUR.

There is a market convention that determines which is the base currency and which is the term currency. In most parts of the world, the order is: EUR – GBP – AUD – NZD – USD – others. Thus if you are doing a conversion from EUR into AUD, EUR is the base currency, AUD is the term currency and the exchange rate tells you how many Australian dollars you would pay or receive for 1 euro. Cyprus and Malta which were quoted as the base to the USD and others were recently removed from this list when they joined the euro. In some areas of Europe and in the non-professional market in the UK, EUR and GBP are reversed so that GBP is quoted as the base currency to the euro. In order to determine which is the base currency where both currencies are not listed (i.e. both are "other"), market convention is to use the base currency which gives an exchange rate greater than 1.000. This avoids rounding issues and exchange rates being quoted to more than 4 decimal places. There are some exceptions to this rule e.g. the Japanese often quote their currency as the base to other currencies.

Quotes using a country's home currency as the price currency (e.g., EUR 0.63 = USD 1.00 in the euro zone) are known as direct quotation or price quotation (from that country's perspective) and are used by most countries.

Quotes using a country's home currency as the unit currency (e.g., EUR 1.00 = USD 1.58 in the euro zone) are known as indirect quotation or quantity quotation and are used in British newspapers and are also common in Australia, New Zealand and the eurozone.

• direct quotation: 1 foreign currency unit = x home currency units
• indirect quotation: 1 home currency unit = x foreign currency units

Note that, using direct quotation, if the home currency is strengthening (i.e., appreciating, or becoming more valuable) then the exchange rate number decreases. Conversely if the foreign currency is strengthening, the exchange rate number increases and the home currency is depreciating.

Market convention from the early 1980s to 2006 was that most currency pairs were quoted to 4 decimal places for spot transactions and up to 6 decimal places for forward outrights or swaps. (The fourth decimal place is usually referred to as a "pip"). An exception to this was exchange rates with a value of less than 1.000 which were usually quoted to 5 or 6 decimal places. Although there is no fixed rule, exchange rates with a value greater than around 20 were usually quoted to 3 decimal places and currencies with a value greater than 80 were quoted to 2 decimal places. Currencies over 5000 were usually quoted with no decimal places (e.g. the former Turkish Lira). e.g. (GBPOMR : 0.765432 - EURUSD : 1.5877 - GBPBEF : 58.234 - EURJPY : 165.29). In other words, quotes are given with 5 digits. Where rates are below 1, quotes frequently include 5 decimal places.

In 2005 Barclays Capital broke with convention by offering spot exchange rates with 5 or 6 decimal places on their electronic dealing platform. The contraction of spreads (the difference between the bid and offer rates) arguably necessitated finer pricing and gave the banks the ability to try and win transaction on multibank trading platforms where all banks may otherwise have been quoting the same price. A number of other banks have now followed this.

Free or pegged

If a currency is free-floating, its exchange rate is allowed to vary against that of other currencies and is determined by the market forces of supply and demand. Exchange rates for such currencies are likely to change almost constantly as quoted on financial markets, mainly by banks, around the world. A movable or adjustable peg system is a system of fixed exchange rate, but with a provision for the devaluation of a currency. For example, between 1994 and 2005, the Chinese yuan renminbi (RMB) was pegged to the United States dollar at RMB 8.2768 to $1. China was not the only country to do this; from the end of World War II until 1966, Western European countries all maintained fixed exchange rates with the US dollar based on the Bretton Woods system.

Nominal and real exchange rates

• The nominal exchange rate e is the price in foreign currency of one unit of a domestic currency.
• The real exchange rate (RER) is defined as , where P^f is the foreign price level and P the domestic price level.

The RER is based on the GDP deflator measurement of the price level in the domestic and foreign countries (P,P^f), which is arbitrarily set equal to 1 in a given base year. Therefore, the level of the RER is arbitrarily set, depending on which year is chosen as the base year for the GDP deflator of two countries. The changes of the RER are instead informative on the evolution over time of the relative price of a unit of GDP in the foreign country in terms of GDP units of the domestic country. If all goods were freely tradable, and foreign and domestic residents purchased identical baskets of goods, purchasing power parity (PPP) would hold for the GDP deflators of the two countries, and the RER would be constant and equal to one.

Bilateral vs. effective exchange rate

Bilateral exchange rate involves a currency pair, while effective exchange rate is weighted average of a basket of foreign currencies, and it can be viewed as an overall measure of the country's external competitiveness. A nominal effective exchange rate (NEER) is weighted with the inverse of the asymptotic trade weights. A real effective exchange rate (REER) adjust NEER by appropriate foreign price level and deflates by the home country price level. Compared to NEER, a GDP weighted effective exchange rate might be more appropriate considering the global investment phenomenon.

Uncovered interest rate parity

Uncovered interest rate parity (UIRP) states that an appreciation or depreciation of one currency against another currency might be neutralized by a change in the interest rate differential. If US interest rates increase while Japanese interest rates remain unchanged then the US dollar should depreciate against the Japanese yen by an amount that prevents arbitrage. The future exchange rate is reflected into the forward exchange rate stated today. In our example, the foward exchange rate of the dollar is said to be at a discount because it buys fewer Japanese yen in the forward rate than it does in the spot rate. The yen is said to be at a premium.

UIRP showed no proof of working after 1990s. Contrary to the theory, currencies with high interest rates characteristically appreciated rather than depreciated on the reward of the containment of inflation and a higher-yielding currency.

This model holds that a foreign exchange rate must be at its equilibrium level - the rate which produces a stable current account balance. A nation with a trade deficits will experience reduction in its foreign exchange reserves which ultimately lowers (depreciates) the value of its currency. The cheaper currency renders the nation's goods (exports) more affordable in the global market place while making imports more expensive. After an intermediate period, imports are forced down and exports rise, thus stabilizing the trade balance and the currency towards equilibrium.

Like PPP, the balances of payment model focuses largely on tradable goods and services, ignoring the increasing role of global capital flows. In other words, money is not only chasing goods and services, but to a larger extent, financial assets such as stocks and bonds. Their flows go into the capital account item of the balance of payments, thus, balancing the deficit in the current account. The increase in capital flows has given rise to the asset market model.

Asset market model

The explosion in trading of financial assets (stocks and bonds) has reshaped the way analysts and traders look at currencies. Economic variables such as economic growth, inflation and productivity are no longer the only drivers of currency movements. The proportion of foreign exchange transactions stemming from cross border-trading of financial assets has dwarfed the extent of currency transactions generated from trading in goods and services.

The asset market approach views currencies as asset prices traded in an efficient financial market. Consequently, currencies are increasingly demonstrating a strong correlation with other markets, particularly equities.

Like the stock exchange, money can be made or lost on the foreign exchange market by investors and speculators buying and selling at the right times. Currencies can be traded at spot and foreign exchange option markets. The spot market represents current exchange rates, whereas options are derivatives of exchange rates

Fluctuations in exchange rates

A market based exchange rate will change whenever the values of either of the two component currencies change. A currency will tend to become more valuable whenever demand for it is greater than the available supply. It will become less valuable whenever demand is less than available supply (this does not mean people no longer want money, it just means they prefer holding their wealth in some other form, possibly another currency).

Increased demand for a currency is due to either an increased transaction demand for money, or an increased speculative demand for money. The transaction demand for money is highly correlated to the country's level of business activity, gross domestic product (GDP), and employment levels. The more people there are unemployed, the less the public as a whole will spend on goods and services. Central banks typically have little difficulty adjusting the available money supply to accommodate changes in the demand for money due to business transactions.

The speculative demand for money is much harder for a central bank to accommodate but they try to do this by adjusting interest rate. An investor may choose to buy a currency if the return (that is the interest rate) is high enough. The higher a country's interest rates, the greater the demand for that currency. It has been argued that currency speculation can undermine real economic growth, in particular since large currency speculators may deliberately create downward pressure on a currency in order to force that central bank to sell their currency to keep it stable (once this happens, the speculator can buy the currency back from the bank at a lower price, close out their position, and thereby take a profit).

Determinants of FX rates

The following theories explain the fluctuations in FX rates in a floating rate exchange regime (In a fixed exchange rate regime, FX rates are decided by its government):

(a) International parity conditions viz; purchasing power parity, interest rate parity, Domestic Fisher effect, International Fisher effect. Though to some extent the above theories provide logical explanation for the fluctuations in exchange rates, yet these theories falter as they are based on challengeable assumptions [e.g., free flow of goods, services and capital] which seldom hold true in the real world.

(b) Balance of payments model (see exchange rate). This model, however, focuses largely on tradable goods and services, ignoring the increasing role of global capital flows. It failed to provide any explanation for continuous appreciation of dollar during 1980s and most part of 1990s in face of soaring US current account deficit.

(c) Asset market model (see exchange rate) views currencies as an important asset class for constructing investment portfolios. Assets prices are influenced mostly by people’s willingness to hold the existing quantities of assets, which in turn depends on their expectations on the future worth of these assets. The asset market model of exchange rate determination states that “the exchange rate between two currencies represents the price that just balances the relative supplies of, and demand for, assets denominated in those currencies.”

None of the models developed so far succeed to explain FX rates levels and volatility in the longer time frames. For shorter time frames (less than a few days) algorithm can be devised to predict prices. Large and small institutions and professional individual traders have made consistent profits from it. It is understood from above models that many macroeconomic factors affect the exchange rates and in the end currency prices are a result of dual forces of demand and supply. The world's currency markets can be viewed as a huge melting pot: in a large and ever-changing mix of current events, supply and demand factors are constantly shifting, and the price of one currency in relation to another shifts accordingly. No other market encompasses (and distills) as much of what is going on in the world at any given time as foreign exchange.

Supply and demand for any given currency, and thus its value, are not influenced by any single element, but rather by several. These elements generally fall into three categories: economic factors, political conditions and market psychology.

Economic factors

These include: (a)economic policy, disseminated by government agencies and central banks, (b)economic conditions, generally revealed through economic reports, and other economic indicators.

1. Economic policy comprises government fiscal policy (budget/spending practices) and monetary policy (the means by which a government's central bank influences the supply and "cost" of money, which is reflected by the level of interest rate).
2. Economic conditions include:

   Government budget deficits or surpluses

   The market usually reacts negatively to widening government budget deficits, and positively to narrowing budget deficits. The impact is reflected in the value of a country's currency.

   Balance of trade levels and trends

   The trade flow between countries illustrates the demand for goods and services, which in turn indicates demand for a country's currency to conduct trade. Surpluses and deficits in trade of goods and services reflect the competitiveness of a nation's economy. For example, trade deficits may have a negative impact on a nation's currency.

   Inflation levels and trends

   Typically a currency will lose value if there is a high level of inflation in the country or if inflation levels are perceived to be rising [. This is because inflation erodes purchasing power, thus demand, for that particular currency. However, a currency may sometimes strengthen when inflation rises because of expectations that the central bank will raise short-term interest rates to combat rising inflation.

   Economic growth and health

   Reports such as GDP, employment levels, retail sales, capacity utilization and others, detail the levels of a country's economic growth and health. Generally, the more healthy and robust a country's economy, the better its currency will perform, and the more demand for it there will be.

   Productivity of an economy

   Increasing productivity in an economy should positively influence the value of its currency. Its effects are more prominent if the increase is in the traded sector.

Political conditions

Internal, regional, and international political conditions and events can have a profound effect on currency markets.

All exchange rates are susceptible to political instability and anticipations about the new ruling party. Political upheaval and instability can have a negative impact on a nation's economy. For example, destabilization of coalition governments in Pakistan and Thailand can negatively affect the value of their currencies. Similarly, in a country experiencing financial difficulties, the rise of a political faction that is perceived to be fiscally responsible can have the opposite effect. Also, events in one country in a region may spur positive or negative interest in a neighboring country and, in the process, affect its currency.

Market psychology

Market psychology and trader perceptions influence the foreign exchange market in a variety of ways:

Flights to quality

Unsettling international events can lead to a "flight to quality," with investors seeking a "safe haven." There will be a greater demand, thus a higher price, for currencies perceived as stronger over their relatively weaker counterparts. The Swiss franc has been a traditional safe haven during times of political or economic uncertainty.

Long-term trends

Currency markets often move in visible long-term trends. Although currencies do not have an annual growing season like physical commodities, business cycles do make themselves felt. Cycle analysis looks at longer-term price trends that may rise from economic or political trends

"Buy the rumor, sell the fact"

This market truism can apply to many currency situations. It is the tendency for the price of a currency to reflect the impact of a particular action before it occurs and, when the anticipated event comes to pass, react in exactly the opposite direction. This may also be referred to as a market being "oversold" or "overbought". To buy the rumor or sell the fact can also be an example of the cognitive bias known as anchoring, when investors focus too much on the relevance of outside events to currency prices.

Economic numbers

While economic numbers can certainly reflect economic policy, some reports and numbers take on a talisman-like effect: the number itself becomes important to market psychology and may have an immediate impact on short-term market moves. "What to watch" can change over time. In recent years, for example, money supply, employment, trade balance figures and inflation numbers have all taken turns in the spotlight.

Technical trading considerations

As in other markets, the accumulated price movements in a currency pair such as EUR/USD can form apparent patterns that traders may attempt to use. Many traders study price charts in order to identify such patterns.

Trading charactheristic

There is no unified or centrally cleared market for the majority of FX trades, and there is very little cross-border regulation. Due to the over-the-counter (OTC) nature of currency markets, there are rather a number of interconnected marketplaces, where different currencies instruments are traded. This implies that there is not a single exchange rate but rather a number of different rates (prices), depending on what bank or market maker is trading, and where it is. In practice the rates are often very close, otherwise they could be exploited by arbitrageurs instantaneously. Due to London's dominance in the market, a particular currency's quoted price is usually the London market price. A joint venture of the Chicago Mercantile Exchange and Reuters, called Fxmarketspace opened in 2007 and aspired but failed to the role of a central market clearing mechanism.

The main trading center is London, but New York, Tokyo, Hong Kong and Singapore are all important centers as well. Banks throughout the world participate. Currency trading happens continuously throughout the day; as the Asian trading session ends, the European session begins, followed by the North American session and then back to the Asian session, excluding weekends.

Fluctuations in exchange rates are usually caused by actual monetary flows as well as by expectations of changes in monetary flows caused by changes in gross domestic product (GDP) growth, inflation (purchasing power parity theory), interest rates (interest rate parity, Domestic Fisher effect, International Fisher effect), budget and trade deficits or surpluses, large cross-border M&A deals and other macroeconomic conditions. Major news is released publicly, often on scheduled dates, so many people have access to the same news at the same time. However, the large banks have an important advantage; they can see their customers' order flow.

Currencies are traded against one another. Each pair of currencies thus constitutes an individual product and is traditionally noted XXXYYY or YYY/XXX, where YYY is the ISO 4217 International three-letter code of the currency into which the price of one unit of XXX is expressed (called base currency). For instance, EURUSD or USD/EUR is the price of the euro expressed in US dollars, as in 1 euro = 1.5465 dollar. Out of convention, the first currency in the pair, the "base" currency, was the stronger currency at the creation of the pair. The second currency, counter currency or "term" currency, was the weaker currency at the creation of the pair. Currencies are occasionally incorrectly quoted with the pairs inverted e.g. EUR/USD but this is incorrect. The "/" acts the same as the divide mathematical operator and derives the actual exchange rate. e.g. an amount of $140,000 equates to €100,000. $140,000/€100,000 = $/€ = USD/EUR = a rate of 1.4 hence EURUSD or USD/EUR. See Exchange Rate

The factors affecting XXX will affect both XXXYYY and XXXZZZ. This causes positive currency correlation between XXXYYY and XXXZZZ.

On the spot market, according to the BIS study, the most heavily traded products were:

• EURUSD: 27%
• USDJPY: 13%
• GBPUSD (also called cable): 12%

and the US currency was involved in 86.3% of transactions, followed by the euro (37.0%), the yen (17.0%), and sterling (15.0%) (see table). Volume percentages for all individual currencies should add up to 200%, as each transaction involves two currencies.

Trading in the euro has grown considerably since the currency's creation in January 1999, and how long the foreign exchange market will remain dollar-centered is open to debate. Until recently, trading the euro versus a non-European currency ZZZ would have usually involved two trades: EURUSD and USDZZZ. The exception to this is EURJPY, which is an established traded currency pair in the interbank spot market. As the dollar's value has eroded during 2008, interest in using the euro as reference currency for prices in commodities (such as oil), as well as a larger component of foreign reserves by banks, has increased dramatically. Transactions in the currencies of commodity-producing countries, such as AUD, NZD, CAD, have also increased.

Most traded currencies
Currency distribution of reported FX market turnover

Rank	Currency	ISO 4217 code (Symbol)	% daily share (April 2007)
1	United States Dollar	USD ($)	86.3%
2	Euro	EUR (€)	37.0%
3	Japanese yen	JPY (¥)	17.0%
4	Pound sterling	GBP (£)	15.0%
5	Swiss franc	CHF (Fr)	6.8%
6	Australian dollar	AUD ($)	6.7%
7	Canadian dollar	CAD ($)	4.2%
8-9	Swedish krona	SEK (kr)	2.8%
8-9	Hong Kong dollar	HKD ($)	2.8%
10	Norwegian krone	NOK (kr)	2.2%
11	New Zealand dollar	NZD ($)	1.9%
12	Mexican peso	MXN ($)	1.3%
13	Singapore dollar	SGD ($)	1.2%
14	South Korean won	KRW (₩)	1.1%
Other			14.5%
Total			200%