One way many FX traders forecast future rate changes is by analysing the patterns of past movements. This is often referred to as technical analysis, a practice that has been used since the late 1800s. Since the 1990s it has gained even more importance through increased use of computer models and advanced charting techniques.
Currencies rarely spend much time in tight trading ranges and typically develop strong trends. Over 80% of volume is speculative in nature, which creates a market that frequently overshoots and corrects itself. A technically trained trader is able to identify new trends and breakouts that provide multiple opportunities to enter and exit positions.
The use of charts to identify price patterns is a classic technical analysis method. Charts are used to create historical records of price movements that provide key information needed for the analysis of the currency trends. There is no fixed methodology used to interpret chart data, but the ability to recognise basic patterns can help to predict future price movements. Pattern recognition is a hands-on and labour intensive exercise requiring careful visual examination of the price chart. The explanations below are designed to introduce various chart patterns, but should never be interpreted as complete or conclusive evidence that can be applied to a specific trade.
Price movement used in a bar chart is illustrated using a bar. The length of this bar is determined by the high and low of a trading period (e.g. a day). Small horizontal tics may be used to designate opening and closing prices for this trading period.
A candlestick chart offers a clear visual profile of market prices, making it easier to categorise market price patterns to a finer degree. The body of the candle represents the difference between the open and the close for a certain period. When the opening rate is higher than the closing rate the candlestick is solid. If the closing rate exceeds the opening rate, the candlestick is hollow.
Tops, bottoms and trend lines are a great way of identifying historically significant price levels. Trend lines are drawn to connect either a series of highs or lows in a trend. They are used to track the trend in progress.
Support and resistance levels are a simple, yet essential, component of technical analysis that signal tops and bottoms. A support level is a price at which a declining market has stopped falling and will either move sideways or begin to advance. A resistance level is a price at which a rising market has stopped advancing and will either move sideways or begin to decline.
Note: Support and resistance levels are psychological barriers that cause temporary changes in the underlying trend of the market.
Markets do not directly move up and down. The direction of any market is either bullish (up), bearish (down) or neutral (sideways). Within these trends, markets also have countertrend (backing and filling) movements. In a general sense, markets move in waves and a trader must catch the wave at the right time. Trend lines showing support and resistance boundaries may be used as buying or selling areas.
Charts can be used on an intraday (5 minutes, 15 minutes), hourly, daily, weekly or monthly basis. The chart you study depends on how long you intend to hold a position. If you are trading short-term, you may wish to refer to 5-minute or 15-minute charts. If you intend to hold a position for a few days, an hourly, 4-hour or daily chart could be preferable. Weekly and monthly charts compress price movements to allow for much longer-range trend analysis.
With the help of advanced computer systems, traders can predict future market trends based on calculated averages, relative strength of up or down trends, overbought and oversold conditions and many other mathematical models that are proven to be helpful in predicting price behaviour. The following sections will explain a few of the basic calculation methods and the application of the studies in different scenarios.
RSI estimates the market's current strength or weakness during a given period. It is an oscillator that measures the ratio of upward to downward movement for a given instrument over a specified period of time.
When applied it will directly affect the RSI; the shorter the interval used the more sensitive the corresponding movement in RSI. Conversely, the longer the period specified, the less sensitive, therefore slower, the RSI. The RSI depends solely on changes in price to quantify its momentum.
The result appears as a percentage value ranging between 0 and 100. Values between 0-30 represent oversold conditions, whereas values between 70-100 represent overbought conditions. Overbought/oversold analysis is the main thrust of the RSI. This assessment is based on the assumption that higher closes indicate strong markets, while lower closes indicate a weaker trading environment.
NOTE: RSI performs better during overbought/oversold market conditions and as a divergent indicator.
Stochastics is a popular oscillator used to judge price momentum. It measures the close of a price in relation to its range and is represented by a ratio multiplied by 100. This measure is called %K, while another measure, the %D, is a moving average of %K. A 3-period moving average applied to %K yields reasonable values. These values are plotted on a scale from 0 to 100.
The concept for stochastics is based on the premise that as prices move higher, the intraday closes will be closer to the high of the daily range. The reverse is true in downtrends. Values over 70 indicate overbought conditions, while values below 30 indicate oversold conditions.
If the %K crosses the %D line from above (below) at the upper (lower) part of the graph, a sell (buy) signal is given. A divergence between the %K and %D lines indicates a new trend may be emerging.
A moving average is a mathematical calculation that smooths or eliminates the fluctuations in data and helps to determine when to buy and sell. Moving averages clarify the long-term trend of a market while eliminating shorter-term fluctuation. They are often used by professional portfolio managers, and remain a popular tool because the trend can be determined mathematically, making computer analysis of price trends a reality.
A simple moving average is constructed by adding together the closing price of a certain number of periods (i.e. days) and dividing by that number. Each period (day), the oldest price in the series is dropped and the most recent close is added. When these values are plotted, a smooth trend is visible.
A weighted moving average emphasises the most recent data because this affects the average’s sensitivity more readily. In the moving average, current data is more relevant to the trading outlook than historical information, thus a ‘weight’ is applied to the latest data.
An exponential moving average creates an average over a constant number of observations or periods. It uses a smoothing factor to apply increasing weight to more recent periods. The exponential average uses the previous value of the exponential moving average to calculate the current value, while the weighted value drops off the oldest data point in the selected period of the moving average.