Technical Analysis with Charts
The charting of price patterns is one of the classic technical analysis techniques. Charts are historical records of price movements that provide important information needed for the analysis of the trend of currencies. There are no fixed ways to interpret charts but being able to recognize the most basic patterns can help to predict future price movements. Pattern recognition is a hands-on and labor intensive exercise requiring careful visual examination of the price chart. The explanations below are designed to introduce various chart patterns but are by no means complete or conclusive.
The Bar Chart
In a bar chart price movement is reflected by 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.
The Candlestick Chart
A Candlestick chart is visual, giving a nice picture of the profile of market prices and making it easier to categorize market price patterns to a finer degree. The body of the candle represents the difference between the open and the close for a period. When the opening rate is higher than the closing rate the candlestick is solid. When the closing rate exceeds the opening rate, the candlestick is hollow.
Trend Lines and Chart Patterns
Tops, Bottoms and Trend lines are very useful as a means of identifying historically significant price levels. Trend lines are lines drawn that connect either a series of highs or lows in a trend. They are used to track the trend in progress.
Support and Resistance Levels
Support and resistance levels are one of the most basic and an essential component of technical analysis that signal tops and bottoms. A support level is a price level at which a declining market has stopped falling and will either move sideways or begin to advance. A resistance level is a price level 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.
Trend Analysis and Timing
Markets don't move straight up and down. The direction of any market at any time is either Bullish (up), Bearish (down) or Neutral (sideways). Within these trends, markets have countertrend (backing & 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.
Applying Technical Analysis
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 plan on holding a position. If you are trading short-term, you may want to look at 5-minute or 15-minute charts. If you plan on holding a position for a few days, you would likely look at an hourly, 4-hour or daily chart. Weekly and monthly charts compress price movements to allow for much longer-range trend analysis.
With the help of computer systems, traders can now 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 have proven to be helpful in predicting price behavior. The following sections will explain a few of the basic calculation methods and the application of the studies in different scenarios.
Relative Strength Index (RSI)
RSI attempts to estimate the market's current strength or weakness during a given period. It is an oscillator which measures the ratio of upward to downward movement for a given instrument over a specified period of time. The time period used affects the RSI dramatically; the shorter the interval used the more sensitive will be the corresponding move 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 price momentum. The result appears as a percent 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 Relative Strength Index. This assessment is based on the assumption that higher closes indicate strong markets while lower closes indicate weakness.
NOTE: RSI works best during overbought/oversold market conditions and as a divergent indicator.
Stochastics is a popular oscillator 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 tendency 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 condition while values below 30 indicate oversold condition. 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 on the way.
A Moving Average is a mathematical procedure to smooth or eliminate the fluctuations in data and to assist in determining when to buy and sell. Moving averages help clarify the long-term trend of a market while eliminating shorter-term fluctuation. They are often used by professional portfolio managers and have been popular and attractive because the trend can be determined mathematically making computer analysis of price trends a reality.
A simple moving average is constructed by adding up the closing price of a certain number of periods (i.e. days) and then 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 seen.
A weighted Moving Average places more emphasis on the most recent data as this affects the averages sensitivity more readily. Current data is more relevant to the trading outlook than older data in the Moving Average, thus a ‘weight’ is applied to the nearby 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 drops off the oldest data point in the selected period of the moving average.