Technical Analysis Essentials
Technical Analysis Explained
Technical analysis uses proven historical trends by applying algorithmic formulas to current market conditions with a goal of predicting and evaluating future price movements of trading commodities. Professional traders often use multiple indicators and time periods to evaluate when to buy or sell an asset, instead of relying on a single indicator. Key elements to understand and track are price trend; resistance and support levels; and market volatility. Additionally, analyzing multiple time periods can provide a clearer picture of asset strength.
A note of caution, technical analysis provides a predictive range, not an exact number. Technical analysis is about probability and likelihoods, not guarantees. If something works the majority of the time, even though it doesnt work all the time, it can be helpful generating profits and preventing losses with risk analysis.
Technical Analysis in the 24/7 trading market
The fact that the global crypto market is open 24 hours a day, 365 days a year causes significant trading differences than stock exchanges that close daily. With global trading, market sentiment can vary from Asia, Europe and the United States causing independent price movements. Getting timely news updates from Asia in English is difficult; technical analysis will often detect movement due to news before the actual reporting of the news story.
The daily closing of a stock exchange serves to stops significant price movements in an upwards or downwards direction. Think of major market crisis when everything is selling off and the only thing that stops the selling is when the market closes. With cryptocurrency there is no closing bell or trading halts to stop panic selling or FOMO buying (Fear of Missing Out); this is one of the primary reasons the cryptocurrency markets have higher price volatility. Using technical analysis instead of emotion is critical during high volatility trading.
A recommended video talking about the impact the 24/365 open crypto currency exchanges have could not be found, so included is an important video that discusses the 5 stages of crypto currency learning and investing.
Relative Strength Index (RSI) - Explained
The Relative Strength Index (RSI) is one of the favorite algorithmic indicators used by analysts for trading. The RSI (ranges from 0 to 100) can give clear overbought (RSI over 70) and oversold (RSI under 30) trading signals. Sometimes the overall trend signals traders to re-adjust the RSI overbought and oversold levels when bull or bear market are occurring. For example, if the overall market has been very bullish for multiple days, a trader may wait for RSI levels over 80 before entering a sell order.
Multiple time periods can be used for clarity. If 5 minute, 30 minute and 1 hour trading periods (or candles) are all agreeing on an overbought or oversold condition this is considered stronger signal than merely one single time period measurement.
Using RSI in a Trending Market
Three market trending conditions are sideways, upwards and downwards. Often traders use RSI sequences to perform “swing trades” in up or down market conditions. The sequences are 1) a trigger condition 2) an entry point 3) an exit point.
To give an example, in an upwards trending market, the trader will use RSI to initiate a long position. Here the trader will wait for the asset to have a downswing in price resulting in an RSI oversold condition. This sequence is considered the trigger which prompts the next step, waiting for the buy sequence. Note the trader does not initiate a buy yet. Instead, they wait for the RSI value to return to a non-oversold condition. Waiting for the RSI recovery reduces the risk of buying in too early since the asset being tracked might still decline further. When the RSI changes from an oversold condition to a non-oversold condition this marks the entry point sequence. The trader will then wait until the RSI reaches an over bought condition. Opinions amoung traders vary with regard to setting the exit point, some prefer selling immediately, while others wait for the RSI to exit the oversold condition.
Note – This is a review of how some traders use the RSI indicator. Quantify Crypto is not endorsing this or any other method.
Bollinger Bands Explained
In the 1980s, John Bollinger developed the technique of using a moving average with two associated trading values. The upper value represents the moving average plus a standard deviation while the lower value represents the moving average minus a standard deviation. Standard deviation works well with the formula since it brings market volatility into the equation. When the markets are stable with little price movement the standard deviation decreases bringing the Bollinger Band values closer together. Conversely, high volatility will cause higher separation of these values. Most of the time, the price will be between the upper and lower bands. When the price breaks above the upper band it signals an overbought condition; conversely the price going below the lower band value signals an over sold condition. Multiple time periods can be used for clarity, if 5 minute, 30 minute and 1 hour trading periods (or candles) are all agreeing on an overbought or oversold condition this is considered a stronger signal than merely a single time period measurement.
Average True Range (ATR)
he Average True Range (ATR) is a measure of price volatility used by many traders and analysts. An important point is that ATR does not predict price direction, only volatility. Often the ATR value is used in combination with other algorithmic indicators, as some indicators work best during low volatility while other work best during high volatility. Price volatility is an important component for assessing risk, as higher volatility often means higher risk/reward potential.
ATR can be used as a comparison against other similar assets to detect price activity, this can be done on the Quantify Crypto home page using the sorting arrows in the ATR column heading.
Exponential Moving Average (EMA)
The Exponential Moving Average (EMA) is similar to the Simple Moving Average (SMA) with one important improvement. The SMA is an average calculation (sum of values from each price period / number of price periods) where each time period has an equal weight in the average. The EMA calculation assigns higher weights to the most recent time periods within the average calculation. Hence, EMA is used more often than the SMA for technical analysis because it is more reactionary to price movements (it lags less than the SMA).
Bullish signals occur when the EMA for a shorter time period has a greater value than the EMA for a longer time period; bearish signals occur when the EMA for a short time period is less than the EMA for a longer time period. For example, a bullish signal occurs if the 4-hour EMA price for Bitcoin is $5,445 while the 8-hour EMA price is $5,285.
EMA time comparisons are often a building block used by other algorithmic indicators. For example, the MACD and the QMA algorithmic values are both based on specific EMA calculations and comparisons. While EMA can be a trading tool itself, its most important function is showing overall trend direction and its use as a component for other algorithmic trading values.
Moving Average Convergence/Divergence (MACD)
The Moving Average Convergence / Divergence (MACD) indicator is a momentum oscillator used for making trades based on pricing trends. Two values are considered for the MACD indicator, the MACD value and the Signal value. These values are used in multiple ways to give bullish and bearish signals. Below are two examples.
Method 1: The MACD value going from a negative value to a positive value indicates an upwards bullish crossover, conversely changing from a positive value to a negative value is considered bearish.
Method 2: The MACD value and Signal value are used for comparison. If the MACD value changes from being lower than the Signal value to higher than the Signal value, then this marks a bullish trend signal. A graph representation would show the MACD line crossing above the Signal line. Conversely, if the MACD value changes from being higher than the Signal value to lower than the Signal value, it marks a bearish trend. The greater the difference between the MACD value and the Signal value the stronger the bullish or bearish signal.
Please note that the MACD algorithmic indicators are considered lagging indicators. The Signal value is the nine time period Exponential Moving Average (EMA); The MACD value is calculated by subtracting the value of a 26 time period EMA from a 12 period EMA value.
Fundamental Analysis and Technical Analysis for Cryptocurrency
Question: Is it better to use Fundamental Analysis or Technical Analysis? Our answer at Quantify Crypto: Using both is best.
This is especially true for the cryptocurrency market. Compared to stocks traded on regulated exchanges, the companies working on leading cryptocurrency projects are not nearly as well established. Its is best to think of cryptocurrency assets, except for Bitcoin, as part of the venture capital stage. Performing research and execrising due diligence is critical before investing in a start up company. Applying fundamental analysis to a variety of cryptocurrency projects will help prioritize a list of favorable prospects to research further. It is best to apply technical analysis to assets that have passed your fundamental analysis screening.
Technical Analysis works best for cryptocurrency assets with higher liquidity, higher volume and trading on multiple exchanges. Today, there are over 2,000 cryptocurrency assets that are traded globally. Many of these assets do not have the necessary volume to support informative technical analysis. The Quantify Crypto platform currently focuses on 125 digital assets that meet higher liquidity and trading volume standards.