Technical analysis may appear somewhat subjective. Fortunately, with recent advances in charting software, it is now possible to complement chart analysis with the study of mathematical indicators, enhancing the objectivity in technical analysis.
Mathematical indicators that help describe price strength, direction, volatility and support/resistance are generated through calculations involving price and/or volume history data. You will want to understand mathematical indicators if you are learning how to trade cryptocurrency.
The price and/or volume data may be taken from any combination of the open, high, low or close over a time period. Mathematical indicators should be analyzed over a period of time, in conjunction with charting patterns and with the price itself.
When displayed graphically, mathematical indicators can help confirm and predict price action. It is a good idea to have a general understanding for how an indicator is calculated, but more critical is being able to interpret an indicator’s trading signals.
Common mathematical indicators used for crypto trading
Examples of popular mathematical indicators include:
- Simple Moving Average (SMA)
- Exponential Moving Average (EMA)
- Moving Average Convergence Divergence (MACD)
- Relative Strength Index (RSI)
- Bollinger Bands
- Fibonacci Retracements.
There are dozens of other mathematical indicators available in most trading or charting software packages, but a point of diminishing returns is reached once an optimal number of mathematical indicators have been applied.
Additional mathematical indicators overcrowd the chart display and contribute to information overload leading to paralysis during instances when you need to be nimble in decision making.
Most mathematical indicators can be divided into either leading or lagging indicators. Leading indicators are also known as momentum indicators, as they describe the amount of momentum behind price trends.